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62e10043a8e4dcaa571ecb69 | 2 | The SOPMA program was used following the default parameters (output width = 8; the number of conformational states = 4; helix, sheet, turn, and coil; similarity threshold = 8, and window width = 17) to determine the secondary structural parameters. Moreover, the SPIPRED program (v.4.0) was used the determination of the secondary features and topology of the selected protein. |
62e10043a8e4dcaa571ecb69 | 3 | The three-dimensional structure of the selected protein was anticipated by using the Modeller with HHpred interface . Moreover, the PROCHECK program of the SAVES program (v.6.0) was used for the structural validation of the modeled 3D structure of the protein. Also, the ProSA-web program was used to determine the Z-score of the modeled structure for structural assessment. |
62e10043a8e4dcaa571ecb69 | 4 | The protein sequence retrieved from the NCBI database contains 546 amino acid residues (Table ). The fusion protein (accession no. QBQ56722, version no. QBQ56722.1) is found in the QBQ56722 locus of Nipah henipavirus. The physicochemical parameters of a protein are defined by the characteristics of its constituent amino acids. The alpha-carbon unit of all amino acids, except for glycine, is asymmetric, indicating that it is connected to four distinct chemical constituents (atoms or atom pairs) . Consequently, amino acids, except glycine, can appear in two distinct spatial or geometric configurations (i.e., isomers), which resemble left and right hands . ExPASy ProtParam tool identified the physicochemical characteristics of the protein, such as amino acid compositions, atomic composition, and protein half-life calculation (Figure ). Leucine is the most abundant amino acid (61, 11.2%) compared to others in the amino acid sequence. Moreover, the atomic composition of the protein demonstrated that hydrogen is the most abundant element (4361, 50.8%), following oxygen (817, 9.5%), nitrogen (693, 8.1%), and sulfur (26, 0.3%). |
62e10043a8e4dcaa571ecb69 | 5 | The protein has a molecular weight of about 60280.90 Da (Table ) with a theoretical pI of 6.08 (6.30*). The protein has the total number of positively charged residues (Arg + Lys), the whole number of atoms, and the absolute number of negatively charged residues (Asp + Glu) as of 46, 8584, and 48, respectively. As more protein therapies are being developed, many of which have a short plasma half-life, the biotech and pharmaceutical industries are focusing more and more on methods to lengthen that half-life . The therapeutic and cost benefits of a longer half-life are apparent. Numerous recognized or in-development biotherapeutics have a short half-life, needing numerous administrations to sustain a therapeutic level over a long period . The use of half-life extension techniques permits the production of medicines with enhanced pharmacokinetic and pharmacodynamic characteristics that have a prolonged half-life. Incorporating half-life extension methods into developing numerous biotherapeutics is now standard practice. Various options are available for fine-tuning half-life and adaptation to the desired treatment method and condition . The anticipated protein half-life as of 30 hours (mammalian reticulocytes, in vitro); >20 hours (yeast, in vivo); and >10 hours (Escherichia coli, in vivo). |
62e10043a8e4dcaa571ecb69 | 6 | Efforts are undertaken to establish a relationship between the metabolic stability of proteins and aspects of their primary sequence and to use weight estimates of instability for a protein of established sequence to determine its resilience properties . Proteins may be evaluated for viability in vitro using the 'Instability index.' If the index is under 40, the substance will likely be stable in the test tube. It is presumably not sustainable if it is more significant . The instability index of the selected protein is 38.05 (less than 40.00), resulting in a stable nature. The aliphatic index measures how much space is taken up by a protein's aliphatic side chains compared to its total volume . The thermal stability of proteins is related to their aliphatic index. Proteins with a high aliphatic index are less likely to denature when heated. Hydrophobicity is a property shared by aliphatic amino acids . The aliphatic index of the selected protein is demonstrated as 112.27. GRAVY is the value employed to demonstrate a protein's hydrophobicity. This value is computed by accepting the absolute hydropathy values of all amino acids (aa) and splitting that whole by the entire sequence length . The estimated GRAVY of the protein is 0.177. 0.177 *pI calculated by the SMS v2.0 tool. |
62e10043a8e4dcaa571ecb69 | 7 | In the context of a polypeptide chain, the term "secondary structure" refers to the standard and recurrent spatial configurations of neighboring amino acid residues. Hydrogen bonds between amide hydrogens as well as carbonyl oxygens of the peptide backbone are responsible for its stability. Alpha-helices (α-helices) and beta-structures (β-structures) are the two most important types of secondary structures . The SOPMA program demonstrated that the protein contains alpha helix (239, 43.77%), extended strand (112, 0.51%), beta turn (23, 4.21%), and random coil (172, 31.50%). No Pi helix, beta bridge, bend region, and ambiguous states were present in the protein (Figure ). The selected protein contains polar, non-polar, aromatic groupcontaining, and hydrophobic amino acid residues in its structure (Figure ). Moreover, the sequence plot demonstrated the protein parameters, including the protein's helical, coil, and extracellular properties (Figure ). The secondary structure of the selected protein is illustrated in Figure . |
62e10043a8e4dcaa571ecb69 | 8 | The three-dimensional form of a protein is known as its tertiary structure. One primary 'backbone' polypeptide chain in the tertiary structure comprises one or more protein secondary structures (PSSs) called domains . There are a variety of possible interactions and bonds between amino acid side chains. The sequence-structure gap (SSG) is a significant obstacle in computational biology and chemistry, and protein structure anticipation is one strategy to close this gap. Accurately predicting the structure of a protein is critical since protein structure dictates its function . The most favored protein templated (HHpred ID: 2B9B_A) was selected for anticipation of the three-dimensional protein structure by the Modeller program with the HHpred interface with the probability of 100%, E-value 2.8 × 10 -132 , and target length of 497 (Figure ). |
62e10043a8e4dcaa571ecb69 | 9 | The estimated Ramachandran plot calculations of the selected protein were as residues in most favored regions (411, 91.9%), residues in additional allowed regions (30, 6.7%), residues in generously allowed regions (6, 1.3%), number of non-glycine and non-proline residues (447, 100.0%), and there was no residue in disallowed regions (Figure ). Moreover, the local model assessment and the overall model quality by Z-score (-7.26) assessed the anticipated protein model quality and validated the structure of the protein. |
62e10043a8e4dcaa571ecb69 | 10 | NiV has developed as a fatal zoonotic disease. Bats, the natural reservoir of the virus, are adept at viral propagation and human outbreaks continue to be documented routinely. Since bats may be found worldwide, we might expect to see new epidemics in previously unaffected regions. Acute illness progression and a high death rate make a correct diagnosis challenging. The absence of accessible, affordable diagnostic tests and laboratories to process viral samples makes the situation worse. The total caseload is low, and the course of infection is rapid. Thus there is a dearth of investigations into human subjects that might yield effective therapy and prevention. The selected protein's secondary and tertiary characteristics demonstrated the protein structure-based relationships and, therefore, more comprehending properties of the protein. The protein is a fusion protein deeply associated with viral infection. Therefore, the selected protein can be a target for both protein-based drug and vaccine design against the protein to minimize viral infections. |
65bbc654e9ebbb4db9741f5c | 0 | Metal organic frameworks (MOFs) have attracted considerable interest due to their high porosity and tunability, making them ideal for applications related to gaseous species, such as gas storage, 4,5 capture, separation, and catalysis. In designing MOFs for applications involving gases, both the absolute and relative strengths of gas binding are crucial for material selectivity. MOFs featuring open metal sites are particularly promising in this regard. The interaction between the metal and a gas molecule at these sites can be finely tuned through the chemical environment of the metal, enhancing selectivity for specific gases. To effectively design the selective interaction, quantum chemistry calculations are indispensable. They provide a deep understanding of the metal-gas molecule interactions, enabling the tailored design of MOFs with desired selectivity for certain gases. Computational studies of MOFs are commonly performed using their periodic structures through density functional theory (DFT) employing the semi-local generalized gradient approximation (GGA) functional. DFT provides a practical balance between computational efficiency and accuracy, facilitating the calculation of large unit cells of MOFs. However, DFT is notably prone to self-interaction errors, which cause excessive delocalization of electron density. Self-interaction error can significantly impact the study of MOFs, leading to inaccuracies in reaction barriers, adsorption energies, , and electronic properties. Moreover, as DFT operates as a single-reference method, approximating the many-electron wavefunction with a single Slater determinant, it incurs static correlation errors, which are particularly pronounced in strongly correlated systems. There is a notable tradeoff between selfinteraction and static correlation error, where methods that fix the delocalization error (e.g., incorporating an admixture of Hartree-Fock exchange) are known to be more prone to static correlation errors. For a more accurate analysis of gas molecule binding, post-DFT methods such as coupled cluster singles and doubles with perturbative triples (CCSD(T)) are necessary. While CCSD(T) remains a single-reference method and is subject to static correlation error, it demonstrates sufficient accuracy for systems exhibiting moderate correlation (e.g., systems with low multireference character indicated by diagnostics). CCSD(T) is typically limited to molecular systems, and MOFs can be conveniently decomposed into molecular components like secondary building unit (SBU) and organic linkers. Such decomposition allows the application of post-DFT methods to individual MOF components. While these approaches offer detailed insights into molecular interactions, they fall short in accurately representing the complete periodic structure of MOFs. Consequently, accurately calculating adsorption energies, while is vital for understanding selectivity, remains challenging due to the difficulties in extending post-DFT methods to full periodic MOFs. To overcome this challenge, we investigate the application of the Hubbard U parameter to a GGA functional (here, PBE) in DFT calculations for full periodic MOFs, primarily focusing on correcting the self-interaction error. The Hubbard U correction can effectively correct DFT's self-interaction error, provided the U parameter is appropriately chosen, without incurring additional computational costs. The U parameter has previously been adjusted to match experimental data for tuning oxidation energies , electronic structure properties, and catalytic activity. Leveraging the reticular structure of MOFs and the correlation between the multireference character of MOFs and their molecular counterparts, we introduce a scheme that determines the U parameter by fitting GGA+U gas molecule adsorption energy results of an SBU to the results of post-DFT calculations, and applies the same U parameter to GGA+U (specifically, PBE+U) calculations of the full MOF. The effectiveness of this U parameter determination scheme is evaluated using two benchmark data sets: DFT calculation results using the HSE06 functional and experimental heats of adsorption. To validate a hypothesis that a U parameter that is effective for correcting SBU energetics will similarly apply to the MOF system, we initially benchmark against HSE06 calculation results. The local hybrid HSE06 was selected because it is the highest-level method for solid-state systems that remains computationally feasible for MOFs that typically have large unit cells. Upon confirming that the U parameter capable of matching the HSE06 result for the SBU also increases agreement between PBE+U and HSE06 for the periodic MOF, we proceed to fit the U parameter to the CCSD(T) results of SBU. Finally, we compare the outcomes of PBE+U, employing the U parameter fitted to CCSD(T), with the experimental data. |
65bbc654e9ebbb4db9741f5c | 1 | All DFT calculations of MOFs and DFT+U calculations of SBUs were performed using Quantum-ESPRESSO version 7.0 62 with projector-augmented wave pseudopotentials and an 80 Ry kinetic energy cutoff. An empirical dispersion correction of Grimme's DFT-D3 with Becke-Johnson damping was applied. Geometry optimization and DFT+U calculations of MOFs were performed with the PBE functional 66 on a 3x2x2 k-point mesh for M2(OH)2-BBTA and M2Cl2-BBTA, and a 4x2x2 k-point mesh for M-DOBDC and M-DSBDC. HSE06 calculations 56 of MOFs were performed only at the G point due to the high computational cost of these calculations. DFT+U calculations of SBUs for Hubbard U parameter fitting were performed by adding 20 Å of vacuum in all directions and applying the Martyna-Tuckerman correction for an isolated molecule. |
65bbc654e9ebbb4db9741f5c | 2 | The initial orientations of N2 and O2 molecules were based on Ref. , and those of CO2 on Ref. , which were determined through DFT calculations. Subsequently, the positions of both MOF atoms and the gas molecule were fully relaxed, with the cell parameters kept constant. SBU calculations using Gaussian type orbital basis sets were performed using ORCA version 5.0.1. DFT calculations employed the def2-TZVP basis set. To ensure consistency with MOF calculations, Grimme's DFT-D3 correction with Becke-Johnson damping was applied as well. However, as ORCA does not have default Becke-Johnson parameters for the HSE06 functional, the parameters used by Quantum-ESPRESSO were used, which are s6 = 1, a1 = 0.383, s8 = 2.310, and a2 = 5.685. We employed cc-pVDZ and cc-pVTZ for the CCSD(T) calculations and extrapolated these to approach the complete basis set limit following a recommended two-point formula. Given the large number of atoms in the SBUs ranging from 44 to 85, domain-based local pair natural orbital (DLPNO) CCSD(T) with "Normal" PNO thresholds was used to make CCSD(T) calculations feasible. |
65bbc654e9ebbb4db9741f5c | 3 | The heat of adsorption was obtained by adding 5/2RT to the calculated adsorption energy to account for the translational and rotational degree of freedom of the gas molecule, where R is the gas constant and T is the temperature. The median temperature of the range used in the relevant experiment was employed (Supporting Information Table ). The temperature variation during the experiment only influences the heat of adsorption by at most 3 kJ/mol. We neglect the zero-point vibrational (i.e., phonon) energy contribution to the adsorption energy, which is less than 5 kJ/mol and should not significantly impact the comparison with experimental data. The energy difference between the ferromagnetic and antiferromagnetic phase of the bare MOF's metal centers is also not expected to have a substantial effect on the results. For example, the difference is 4 kJ/mol for Co2(OH)2-BBTA 60 and 10 kJ/mol for Fe-DOBDC. |
65bbc654e9ebbb4db9741f5c | 4 | We investigate a total of 24 MOFs that are derived from the combination of six 3d metals (Cr, Mn, Fe, Co, Ni, Cu) and four MOF structures: M-DOBDC (DOBDC = 2,5-dioxido-1,4benzenedicarboxylate), M-DSBDC (DSBDC = 2,5-disulfhydryl-1,4-benzenedicarboxylate), M2(OH)2-BBTA (BBTA = 1H,5H-benzo(1,2-d:4,5-d')bistriazole), and M2Cl2-BBTA (Supporting Information Figure ). We selected these MOFs based on the availability of corresponding experimental data for benchmarking. These MOFs possess a hexagonal array of onedimensional channels that facilitate the diffusion of gas molecules within the pores. Their undercoordinated metal sites serve as adsorption sites that can be tailored by switching the metal to selectively capture specific types of molecules. These features make these MOFs particularly promising for gas storage, capture, and separation, where selectivity is a critical factor in device performance. The SBUs of these MOFs were identified by modifying the extraction scheme implemented in MOFSimplify. Each metal atoms and all non-metal atoms up to two bonds away from it were first added to the SBU. Distinct from our previous approach, in the case where any non-metal atom is a member of a ring, all atoms within the ring are included as part of the SBU. Since the MOFs in our data set have metal clusters that are infinitely extended in one dimension, they were truncated to a repeat of three metal atoms, and the adsorbate was aligned with the central metal atom (Figure ). To avoid dangling bonds or strongly negative charges, truncated bonds were capped with hydrogen. All metals were assumed to have oxidation states of +2 with metals in high-spin states and ferromagnetically coupled. The triplet spin of O2 was assumed to be parallel with the spin of the metal atoms unless specified otherwise. The charge of the SBU was determined by summing the charge of the metal and the ligands. The full list of charge and magnetization state of MOF and SBU are provided in Supporting Information Table . The U parameter is only applied to the 3d orbitals of metal atoms. The binding energy (Eb) of a gas molecule to an SBU is calculated using PBE+U as follows: |
65bbc654e9ebbb4db9741f5c | 5 | The range of U values considered is from 0 eV to 15 eV, with stepwise increments of 0.1 eV. Our study focuses on the adsorption energy of N2, O2, and CO2. This enables us to compare the impact of U on the redox-dependent adsorption of N2, the additional spin effect of O2, and physisorption characteristics of CO2. In particular, for CO2, we study only the end-on Obased adsorption of CO2 and do not consider binding between the metal center and C that is common in chemisorption, following the geometry determined by DFT in ref. . |
65bbc654e9ebbb4db9741f5c | 6 | We first assess the sensitivity of the adsorption energy of the SBU to the calculation method by comparing PBE, HSE06, and CCSD(T) results (Figure ). PBE and HSE06 calculations were performed for the full data set of 72 MOF-molecule systems. CCSD(T) calculations were limited to a subset of 19 MOF-molecule systems, chosen based on the availability of experimental data related to the heat of adsorption for direct benchmarking. In line with previous findings, PBE consistently predicts a stronger binding affinity between gas molecules and SBUs compared to HSE06 and CCSD(T). For the entire data set, the mean absolute difference (MAD) in the adsorption energy calculated using PBE compared to HSE06 is 0.14 eV. For the subset of systems with available experimental data, the adsorption energies calculated using PBE show a larger deviation from HSE06 results, giving a MAD of 0.23 eV. |
65bbc654e9ebbb4db9741f5c | 7 | The deviation is even larger when comparing PBE with CCSD(T) over this same set of 19 MOFs, where the MAD reaches 0.31 eV. While HSE06 gives adsorption energy values that align more closely with CCSD(T) and are particularly accurate for CO2, it is not sufficient to provide an accurate representation of adsorption behavior of N2 and O2 (Supporting Information Figure ). |
65bbc654e9ebbb4db9741f5c | 8 | For example, while HSE06 overestimates the O2 binding strength to Fe-DOBDC, yielding an adsorption energy of -0.39 eV, CCSD(T) predicts it to be repulsive (i.e., unbound) at 0.16 eV. Incorporating exact exchange in DFT calculations significantly alters the adsorption energy range for all of the molecules on SBUs. The adsorption energy calculated using PBE ranges from -0.93 eV to -0.06 eV, while the adsorption energy calculated using HSE06 is shifted upward ranging from -0.39 eV to 0.41 eV, meaning that some interactions are repulsive even when the DFT-D3 dispersion correction is applied. For the HSE06 calculations, the adsorption energy of CO2 exhibits the narrowest range, from -0.37 eV to -0.14 eV. N2 displays a slightly wider range, spanning from -0.36 eV to 0.06 eV. And O2 shows the broadest range, varying from -0.39 eV to 0.41 eV, i.e., the same as the total range over all molecules. Molecules that show small ranges of binding energies tend to display better agreement between PBE and HSE calculations. That is, CO2 adsorption energies have a MAD of only 0.03 eV, the MAD for N2 is higher at 0.13 eV, and O2 demonstrates the largest deviation at 0.26 eV. It is worth noting that the adsorption of O2 is particularly susceptible to self-interaction error arising from a considerable charge transfer from the metal atom to the O2 molecules, 82 leading to erroneous conclusions regarding adsorption behavior. For example, PBE calculations suggest a strong binding of O2 to Fe2Cl2-BBTA with an absorption energy of -0.48 eV, whereas HSE06, which corrects for the impact of SIE, indicates a repulsive interaction, estimating an adsorption energy of 0.17 eV. |
65bbc654e9ebbb4db9741f5c | 9 | We explore two approaches to determine the U parameter for the data set consisting of 72 MOF/adsorbate systems. Firstly, taking into account the specific characteristics of the SBU composition, we individually fit the U parameter for each SBU/gas-molecule system. We refer to this customized U value as the SBU-specific U, or USBU. Secondly, focusing solely on the chemistry between the metal atom and the gas molecule, we fit the U parameter for a group of SBUs that share the same metal/gas-molecule pair. In this case, we determine the U parameter by minimizing the MAD of each grouping. We refer to this calibrated U value as the metal-specific U, or Umetal (Supporting Information Table ). Even though we refer to this as the metal-specific U, it also is unique for each adsorbate (i.e., CO2, N2, or O2). |
65bbc654e9ebbb4db9741f5c | 10 | By fitting the U parameter to each SBU/gas-molecule system, it is possible to align the adsorption energy of the molecule on the SBU model calculated with PBE+USBU to that of HSE06 within a maximum deviation of 0.2 eV for all systems under consideration. Deviations between PBE+USBU and HSE06 persist primarily if the adsorption energy is insensitive to the U correction or if the effect of U is to tune the adsorption in the wrong direction with respect to HSE06. The MAD of the adsorption energy of SBUs calculated with respect to HSE06 decreases from 0.15 eV with PBE to 0.02 eV when the SBU-specific U is used in a PBE+U calculation (Figure ). Even when fitting the U parameter for a group of SBUs that share the same metal/gas-molecule pair, we found that only two cases, N2 and O2 binding on Co2Cl2-BBTA, exhibit PBE+Umetal errors exceeding 0.2 eV. The MAD of the adsorption energy of SBUs calculated using PBE+Umetal with respect to HSE06 remains at 0.04 eV, which is comparable to the previous scenario where the SBU-specific U is applied, with the benefit of making the approach more general (Supporting Information Figure ). The two sets of U parameters show comparable performance even though the USBU and Umetal parameters that would be used for a MOF-adsorbate complex differ by 3.1 eV across the set of MOFs studied here. They differ because Umetal is fit to reduce errors on average across all MOFs with that metal and adsorbate, whereas USBU is fit to each SBU (Supporting Information Figure ). The small difference in performance of the two U parameter fitting approaches can be attributed to the relatively low sensitivity of the adsorption energy to changes in the U parameter. In fact, the adsorption energy of 43 of 72 cases show a deviation of less than 0.1 eV when the U parameter is varied from 0 eV to 15 eV (Supporting Information Figure ). The value of the calibrated U parameters is influenced by the sensitivity of the adsorption energies to the U parameters and by the magnitude of the original deviation between the two functionals. Both the SBU-specific and metal-specific U parameters exhibit a distribution centered around 3-4 eV (Figure ). For SBU-specific U parameters in the most extreme cases, the calibrated U parameters reach 15 eV for 9 out of 72 cases, and, in the opposite direction, the PBE results of another 10 cases already agree well with HSE06 without the need for the U parameter. The highest values of the U parameter are observed mainly for the cases of O2 and CO2 adsorption. A large U parameter is required when the adsorption energy demonstrates relatively low sensitivity to the U parameter, as is the case for CO2, or when there is a significant difference between PBE and HSE06 results, as is the case for O2 (Figure ). For example, the SBU-specific U parameter is set at 15 eV for both O2 on Ni2(OH)2-BBTA and CO2 on Fe2Cl2-BBTA. While the adsorption energy of O2 on Ni2(OH)2-BBTA exhibits a notable variation of 0.26 eV when the U parameter is varied from 0 eV to 15 eV, the adsorption energy of CO2 on Fe2Cl2-BBTA experiences a much smaller variation of 0.06 eV. |
65bbc654e9ebbb4db9741f5c | 11 | To rationalize differences in needed U parameters, the sensitivity of the adsorption energy to the U parameter can be estimated by the difference in the PBE fractionality of the bare SBU and SBU/gas-molecule system, ΔTr[𝒏(𝟏 -𝒏)], which is directly proportional to the Hubbard energy correction term. Here, 𝒏 is the occupation matrix of the orbitals where the U parameter is applied, i.e., the metal 3d orbitals. For each orbital, the term 𝑛(1 -𝑛) takes on a value of 0 when the orbital is either completely filled or empty. Its value increases to a maximum of 0.25 when the orbital is half-filled, the regime in which the system is maximally impacted by corrections from the U parameter. The PBE fractionality analysis shows that, in general, the adsorption energy of CO2 exhibits the least sensitivity, whereas the adsorption energy of O2 is the most sensitive (Figure ). |
65bbc654e9ebbb4db9741f5c | 12 | We tested the effectiveness of the U parameter calibrated from the SBU by using it to perform PBE+U calculations of the full periodic MOF structure. The MAD of PBE+U calculations, when compared to HSE06 results on the full periodic MOF, is found to be 0.06 eV for both the SBU-specific and metal-specific U parameters, exhibiting a substantial improvement over the MAD of 0.13 eV when using standard PBE (Figure and Supporting Information Figure ). Consequently, our findings confirm the hypothesis that a U value calibrated using a truncated SBU model will successfully correct properties of the periodic MOF structure. PBE+U calculations using an SBU-calibrated U value match adsorption energies from periodic hybrid calculations better than hybrid calculations on SBU models do (MAD = 0.06 eV vs 0.07 eV, Supporting Information Figure ). Therefore, the calibrated U parameter enables the GGA-level calculation on the periodic MOF to achieve similar accuracy to the hybrid-GGA-level calculation on the SBU, while also benefitting from the incorporation of the environment effects of incorporating periodicity. |
65bbc654e9ebbb4db9741f5c | 13 | Given the promise of U parameters calibrated on SBU models to improve the energetics of full periodic MOFs, we investigated whether we could increase the fidelity with which we model the SBU. CCSD(T) is widely regarded as the gold standard in quantum chemistry, and thus we selected it as our reference method for SBU calculations obtained at a higher level of theory. We confirmed the reliability of CCSD(T) calculations using the T1 diagnostic, which estimates the multireference character through the single-excitation amplitude vector from CCSD calculations. Apart from one exception, all systems of interest were shown to have a T1 value below 0.02 (Supporting Information Table ). The cutoff value of 0.02 is generally accepted as indicating that static correlation errors are manageable for single-reference methods. The one system exhibiting a high T1 value is Co2OH2-BBTA with an O2 adsorbate, which will be discussed in detail below. Nevertheless, the ultimate test for theoretical calculations should be experimental reference data. As a more stringent test, we investigated the effectiveness of the U parameter fitted to SBU CCSD(T) calculation results, U CCSD(T) , in predicting the experimental heat of adsorption for the periodic MOF. This corresponds to the same approach as USBU fitting where each adsorbate and MOF gets its own U parameter but in this case the tuning is carried out to match CCSD(T) results. For systems where experimental heat of adsorption data was available, we calculated the adsorption energy for N2, CO2, and O2 using PBE and PBE+U CCSD(T) |
65bbc654e9ebbb4db9741f5c | 14 | For N2, PBE gives a mean absolute error (MAE) of 8.4 kJ/mol, which drops to 4.9 kJ/mol with the application of the U CCSD(T) correction (Figure ). In the cases of Mn-DOBDC, Ni-DOBDC, and Co2Cl2-BBTA, the heat of adsorption calculated using PBE is already small, within 3 kJ/mol of the experimentally measured value. Here, introducing the U CCSD(T) parameter does not greatly alter the results. For Co-DOBDC and Co2(OH)2-BBTA, PBE overbinds N2, giving errors of 10.7 kJ/mol and 16.4 kJ/mol, respectively. The U CCSD(T) parameter proves to be effective for these systems, decreasing the error to 4.1 kJ/mol for Co-DOBDC and 2.0 kJ/mol for Co2(OH)2-BBTA. In contrast, with Cu-DOBDC and Fe-DOBDC, PBE exhibits underbinding for N2. Given that the U parameter tends to weaken the adsorption strength, 90 it amplifies the error for Cu-DODBC. While the heat of adsorption of Fe-DOBDC atypically gets stronger upon applying the U CCSD(T) parameter, the increase in heat of adsorption for PBE+U is insufficient to achieve good agreement with the experimental heat of adsorption. For CO2, the interaction between the metal atom and the CO2 molecule in these MOFs is primarily driven by the dispersion interaction, with minimal hybridization. Therefore, the U CCSD(T) parameter has little impact on the heat of adsorption, as discussed previously. In summary, while the U CCSD(T) correction is effective in improving the accuracy for N2 in cases of PBE overbinding, it does not enhance the accuracy of CO2 adsorption values, which are primarily due to physisorption processes. O2 adsorption presents additional challenges. There is an uncertainty associated with whether the O2 molecule retains its spin when adsorbing and if that magnetic moment is coupled ferromagnetically (FM) or antiferromagnetically (AFM) to the metal center to which it binds. For all the studied MOFs, PBE exhibits a significant overbinding with AFM coupling, leading to a substantial MAE of 41.3 kJ/mol with respect to experiment. The U CCSD(T) parameter corrects much of this overbinding, reducing the MAE to 12.9 kJ/mol when choosing the coupling case with the lower energy for computing the heat of adsorption (Figure and Supporting Information Table ). When the U CCSD(T) parameter is applied, FM coupling shows stronger adsorption than AFM coupling for Cu-DOBDC, Fe-DOBDC, Co2Cl2-BBTA, and Co2(OH)2-BBTA. However, the U CCSD(T) parameter overcompensates for two outlier systems, resulting in errors of 21.9 |
65bbc654e9ebbb4db9741f5c | 15 | loses the extra stabilization it had from the hydrogen bonding with the nearby hydroxy group, leading to even weaker adsorption of O2 (Supporting Information Figure ). In stark contrast, experimental measurements place the metal-O2 distance at 1.9 Å , aligning with the PBE results. The observed discrepancy between PBE+U CCSD(T) and the experiment can likely be attributed to two primary factors. Firstly, as previously mentioned, this system may be prone to significant static correlation errors, evidenced by the high T1 value of 0.0202, suggesting that CCSD(T) results may not be sufficiently reliable. Secondly, our current U CCSD(T) is fitted only to the SBU with an FM spin configuration. The potential energy curve of the FM spin configuration calculated using CCSD(T) exhibits a notably flat and repulsive energy curve, contrary to the experimental observations (Supporting Information Figure ). It is important to note that while our current U CCSD(T) value is fitted only to the SBU with an FM spin configuration, the optimal U CCSD(T) value varies based on the spin configuration. Consequently, the CCSD(T) result of the FM spin configuration is not likely to estimate the U value needed to calculate the adsorption energy for the Co2(OH)2-BBTA-O2 system with an AFM spin configuration. Systems with ambiguous spin coupling are therefore not good candidates for this calibration approach and rather require a comprehensive broken symmetry calculation to thoroughly understand their adsorption processes. Overall, the quality of the CCSD(T) evaluation on SBUs in comparison to experimental adsorption energies on the full MOF suggest some limitations for gas adsorption (Figure ). |
65bbc654e9ebbb4db9741f5c | 16 | Nevertheless, there is still an important role for the U CCSD(T) parameter in yielding more accurate results for the full MOF system. Optimizing the geometry of a periodic MOF using a GGA such as PBE and then employing CCSD(T) calculations on a cluster SBU model of the MOF, a typical approach in MOF studies, can misrepresent the heat of adsorption. PBE tends to overbind the gas molecules, leading to an underestimation of the metal-molecule distances (Supporting Information Tables ). Especially for Co2(OH)2-BBTA and Co2Cl2-BBTA, the short metal-molecule distance of PBE-optimized structure causes the CCSD(T)-evaluated single-point energy to indicate a positive (repulsive) N2 adsorption energy. The potential energy curve for Co2(OH)2-BBTA interacting with N2 exemplifies the efficacy of the U CCSD(T) parameter in correcting the overbinding tendency of PBE. Indeed, the potential energy curve of the SBU calculated using PBE+U CCSD(T) aligns closely with that calculated using CCSD(T) (Supporting Information Figure ). Still, potential energy curves from both PBE and PBE+U calculations reveal that relying solely on the SBU can underestimate the adsorption strength compared to the MOF. Therefore, a full periodic MOF model combined with the U CCSD(T) correction can offer a more accurate representation of the gas adsorption, especially when the CCSD(T) results are unambiguous regarding the spin of MOF metal nodes. |
65bbc654e9ebbb4db9741f5c | 17 | In summary, we examined the calibration of the Hubbard U parameter for use in MOFs that we achieve by tuning properties of corresponding SBU cluster models. We applied this calibration approach to the prediction of adsorption energies on both the cluster and the full periodic MOF and demonstrated the utility of this approach for accurately calculating the adsorption energies of N2, CO2, and O2 on 24 well-known MOF systems. We evaluated the sensitivity of calculated adsorption energies of isolated SBU cluster models across three different methods: the semi-local GGA PBE, local-hybrid HSE06, and CCSD(T). While PBE generally predicted higher binding affinities than HSE06 and CCSD(T), incorporating exact exchange through HSE06 brought the adsorption energies closer to those obtained with CCSD(T). We verified the applicability of the U parameter calibrated against the SBU in improving the accuracy of the calculation of the full periodic MOF system by comparing PBE+U and HSE06 results. The U parameter was calibrated to align the PBE+U adsorption energies with those calculated using HSE06 for SBUs in two calibration approaches. In the first approach, a USBU was tailored to each specific SBU/gas-molecule system, and, in the second approach a Umetal was obtained by fitting a single U value for the metal-gas chemistry across SBUs sharing the same metal/gas pair. Both USBU and Umetal successfully reduced the MAD of PBE compared to HSE06. |
65bbc654e9ebbb4db9741f5c | 18 | Further, we investigated whether fitting the U parameter to calculations performed on isolated SBUs at the CCSD(T) level of theory, considered the gold standard, could help in predicting the experimental heat of adsorption. The calibrated parameter, termed U CCSD(T) , showed varying degrees of success. For N2 adsorption, the PBE+U CCSD(T) calculations exhibited improved accuracy over the standard PBE calculations in cases where PBE was prone to overbinding. However, the impact of U CCSD(T) was minimal for CO2 adsorption, which is primarily driven by physisorption. O2 adsorption presented additional challenges, particularly due to uncertainties in spin states upon adsorption. The U CCSD(T) parameter, while correcting the overbinding in PBE calculations for O2, leads to overcorrections in certain systems, highlighting the need to consider the full spin configuration. |
65bbc654e9ebbb4db9741f5c | 19 | Lastly, our findings emphasized the necessity of using the full periodic MOF model for computing adsorption energies robustly. Although the cluster model cannot provide a quantitative estimation of gas molecule adsorption on MOFs, we nevertheless showed that it is useful for calibrating the U parameter. Thus, the proposed strategy provides a path to overcoming the computational limitations of full periodic MOFs, where the accuracy of calculations is typically limited to the GGA level, by calibrating methods at higher accuracy on the cluster model to predict accurate adsorption in the full system. We expect this approach to generalize well to other adsorbates and properties such as catalysis. |
65bbc654e9ebbb4db9741f5c | 20 | Lattice parameters of studied MOFs; adsorption energy of SBU calculated using two basis sets; summary of calculation details; available experimental measurement data for the heat of adsorption; structure of studied MOFs; magnetic moment and charge of the extracted SBU; U parameters fitted to the HSE06 calculations results of the SBU; magnetization of the metal atom calculated using PBE and PBE+USBU; adsorption energy of SBU calculated using HSE06 and CCSD(T); adsorption energy of SBU calculated using PBE, PBE+Umetal, and HSE06; the SBUspecific U parameters and the metal-specific U parameters; change in the adsorption energy of SBUs with the U parameter; adsorption energy of MOF calculated using HSE06 and PBE+Umetal; adsorption energy of MOF and SBU calculated using HSE06; T1 values from CCSD(T) calculations of the SBU; U parameters fitted to the CCSD(T) calculation results of the SBU; O2 |
60c744e8ee301c513dc791ea | 0 | Conjugated microporous polymers (CMPs) attract marked attention as sustainable, noble metal free materials in a wide range of applications such as heterogeneous catalysis, gas storage and separation, energy storage, optoelectronics, photovoltaics, and sensors. Thanks to their high chemical modularity, exceptional thermal and chemical stability, and a wide array of synthetic approaches, several classes of CMPs have emerged over the last two decades, like polymers of intrinsic microporosity (PIMs), hyper-cross-linked polymers (HCPs), covalent organic frameworks (COFs) and their nitrogen-containing analogues -covalent triazine-based frameworks (CTFs). Arguably, the most important parameters for the performance of these materials in optoelectronics and catalysis is their bandgap energy and their band structure. These will not only depend on the size and co-planarity of the π-conjugated domains in the polymer backbone, but also on the chemical composition of the building blocks. The most common strategy to vary the bandgap of CMPs relies on changes of the size of the carbon-based, polycyclic building blocks. Although this bottom-up approach can indeed lead to networks with variable pore sizes and bandgaps, it can also have detrimental effects on the pore structure once pore channels get sufficiently large for inter-penetration of polymer strands to occur. One further strategy to tune the optical bandgap of a conjugated polymer is the incorporation of heteroatom-containing donor-acceptor (D-A) motifs into its backbone. Recently, we have introduced a family of sulfur-and nitrogen-containing porous polymers (SNPs) that make use of D-A interactions between neighboring electron-deficient triazine (C3N3) cores and electron-rich aryl thiophene building blocks of the polymer to achieve control over the bandgap energy without large changes to the pore structure. In addition, incorporation of aromatic spacers between the donor-and the acceptor-domains enabled us to predictively control the strength of donor-acceptor interactions and -by proxy -the extent of charge-carrier recombination in these networks. This has implications for the fluorescence life-times and the outstanding performance in photocatalytic hydrogen evolution from water of these D-A materials. In this study, we make use of four key-properties of our conjugated, porous D-A polymersnamely, (1) their strong, covalent backbones, (2) their intrinsic Lewis acidity and basicity, (3) their permanently accessible pore channels to gaseous guest molecules, and (4) their optical bandgaps in the visible part of the spectrum -and we use them as optical and electronic sensors and switches that are triggered by volatile acid vapors and re-set by gaseous ammonia. While colorimetric chemical probes are known from molecular systems in solutions, or work on the basis of chemical transformations, the here-presented study shows one of the first instances of amorphous porous conjugated polymers used as fully-reversible, colorimetric chemical probes. Recently, we showed, that triazine-containing COFs, made by the same principle, can be also exploited as acid/base chemosensors, thus, highlighting the significance of our approach in view of making multifunctional smart materials. Herein, we choose four previously reported SNP systems as reference: SNP-NDT1, SNP-NDT2, SNP-BTT1 and SNP-BTT2 that consist of electron-donating thiophene-based naphthodithiophene (NDT) and benzotrithiophene (BTT) moieties, and electron-withdrawing 1,3,5-triazine (Tz) and tris-phenyltriazine moieties (Scheme 1). In addition, we expand the family of SNPs by three networks, two of which contain a benzodithiophene (BDT) moiety -SNP-BDT1 and SNP-BDT2. To study the effect of D-A dyads versus sheer heterocycle content, we further prepare one polymer comprised from electron-rich BTT-building blocks only -SP-BTT. All polymers were prepared using the robust, Pd-catalyzed Stille cross-coupling to link the readily available, stannylated derivatives of thiophene-based molecules with halogenated triazine (TzCl3) and tris-bromophenyltriazine (Tz(PhBr)3) or sulfur-containing benzotrithiophene (BTT-Br3) monomers (see SI and Table ). Scheme 1. Synthetic pathway towards sulfur-and nitrogen-containing polymers (SNPs) and sulfur-only polymer, SP-BTT. Electron-donating thiophene-based linkers (in red) are coupled with electron-accepting triazine-based monomers (in blue) via Pd-catalyzed Stille cross-coupling. |
60c744e8ee301c513dc791ea | 1 | The respective stannylated monomer, brominated monomer, and Pd(PPh3)4 (3:2:5% mol ratio; in case of benzo[1,2-b:3,4-b':5,6-b'']trithiophene (BTT) -1:1:5% mol ratio) were dissolved in anhydrous toluene under inert atmosphere and refluxed for 3 days. In a short time period (1-2 h) the precipitate of polymer started to appear in the reaction flask. After completion of the reaction the precipitate was filtered and washed with hot toluene, DMF, chloroform, THF and methanol (3 times each solvent). Subsequently, Soxhlet extraction was performed using chloroform, THF, and methanol (24 h each solvent). Afterwards the solid was dried in a vacuum drying oven at 120 o C for 24 h. More detailed reaction parameters can be found in Table . |
60c744e8ee301c513dc791ea | 2 | Both the triazine-and thiophene-containing SNP-BDT1 and SNP-BDT2 polymers have characteristic signals at 167-169 ppm in solid-state C CP-MAS spectra which belong to C3N3ring carbons. Signals in the range from 110-150 ppm are attributed to sp 2 -hybridised carbon atoms within aromatic phenyl and thiophene units (Figure ). The sulfur-containing polymer, SP-BTT, shows three distinct signals at 136, 131 and 118 ppm, which correspond to quaternary carbons in thiophene and phenyl rings, and to tertiary thiophene carbons. Details of the bulk analysis of the as-received polymers are found in the SI (Table , S4-S7, Figure ). For all polymer systems, we detect residual Pd-content (0.03 to 1.05 wt%) and P atoms (0.09 to 0.36 wt%) trapped in the polymer matrix after the cross-coupling reaction, as well as Sn (0.39 to 1.07 wt%) and halogen atoms (Cl: 0.57 to 3.72 wt%, Br: 2.25 to 5.74 wt%) arising from unreacted end-groups. These findings correlate with results from TGA measurements under an oxidative atmosphere that show a residual content of non-combustible inorganics between 3 and 7 wt% (Figure ). Irrespective, the high degree of cross-linking we achieve in all networks confers high thermal stability up to 750 °C under an inert atmosphere (Figure ). Powder X-ray diffraction (PXRD) shows that the SNP-BDT1, SNP-BDT2 and SP-BTT networks are -just like the previously reported SNPs -amorphous with broad features at around 10 and 25° 2θ which correlate with in-plane distances between aromatic building blocks and π-stacking distances of approx. 3.6 Å, 11 respectively (Figure ). Scanning electron microscopy (SEM) images of SNP-BDT1 and SNP-BDT2 networks confirm a 'cauliflower'-like morphology typical for nucleation-growth polymers, while the SP-BTT polymer grows in rodlike aggregates of 20 to 100 μm length (Figure ). Transmission electron microscopy (TEM) and selected-area electron-diffraction (SAED) for these three polymers confirm a similar degree of internal, microscopic structure as seen in PXRD data with visible, concentric rings indicative of polycrystalline materials (Figure ). Cross-linking of C2 and C3 symmetric building blocks suggests a regular bonding pattern with hexagonal, "honeycomb"-shaped pores on paper, and the low number of unreacted end-groups in our polymers suggests just that. However, as structural analysis reveals and as we established previously, Pd-catalyzed Stille cross-coupling favors the formation of the disordered, kinetic product, presumably with some degree of interpenetration of adjacent pore structures. We investigated these pore channels by nitrogen gas adsorption/desorption analysis performed at 77 K. All polymers show Type I isotherms with a pronounced hysteresis indicative of micro-and mesopores (Figure ). The guest accessible surface area was calculated according to Brunauer-Emmett-Teller (BET) and varies in the range from 79 to 698 m 2 g -1 (Table ). |
60c744e8ee301c513dc791ea | 3 | So far, we have established the covalent bonding pattern of our networks and their permanent micro-and mesoporosity. Further, we make use of their intrinsic π-aromaticity and heteroatom content by exposing these polymers to a trigger: corrosive HCl vapors. In principle, SNPs have two Lewis-basic sites that can be protonated -triazine-ring nitrogens and thiophene sulfur atoms. SP-BTT plays a particular role in this study, since it contains thiophene-moieties only (Scheme S5). The as-received powders of SNPs show a rapid color change and marked red-shift of the absorption edge in solid-state UV-Vis spectra (Figure , S18-22, Video S1). These values correspond to a decrease of the direct optical bandgap by 0.45 to 0.66 eV and indirect optical bandgap by 0.42 to 0.76 eV according to the Kubelka-Munk function (Figure , S18-S22). The most sensitive network, SNP-NDT1, is triggered by hydrochloric acid concentrations as low as 54 ppm (dosing limit of the current setup, see SI); a response that can still be distinguished by the naked eye within 30 seconds (Figure , Table ). In contrast, sulfur-containing SP-BTT does not show any appreciable color change when exposed to HCl vapors, hence, no marked changes in UV-Vis absorption (Figure ) and in optical bandgaps (Figure ), respectively. One conceivable explanation for this phenomenon could be the difference in basicity between the triazine and the thiophene moiety. While 1,3,5-substituted triazines are readily protonated at the pyridinic ring-nitrogen, thiophenes and oligothiophenes are protonated by superacids only at the 2-position. Notably, this coloration can be fully re-set when the HCl-treated polymer is exposed to NH3 vapors from 24% aqueous ammonia solution (Figure ). This on/off response to HCl/NH3 vapors can be triggered at least five consecutive times (as shown for SNP-NDT1, Figure ) with no apparent losses in the intensity of the optical response. |
60c744e8ee301c513dc791ea | 4 | We closely examined the chemical composition of the polymer backbone during this on/off response to verify that the interaction of the polymer with corrosive HCl is indeed a reversible chemisorption process. Fourier-transform infrared (FT-IR) spectra of pristine and HCl-treated samples show characteristic C3N3-ring vibrations around 1500 cm -1 and 1360-1370 cm -1 , along with the triazine-ring breathing mode at 805-820 cm -1 (Figure -33). Moreover, there are no indicative signals in the OH-and NH-region around 3000 cm -1 that would be a tell-tale sign of irreversible hydrolysis of the polymers. Similarly, FT-IR spectra of the pristine and HCl treated SP-BTT polymer show C-S vibrations of the thiophene ring at 810 cm -1 as well as aromatic C-C stretching at 1342 cm -1 (Figure ). A comparison of FT-IR spectra over five cycles of exposure to HCl/NH3 gases shows that all reported networks remain chemically stable (Figure ). Previous DFT calculations confirm that the Lewis basic N-atoms of the triazine moieties are the preferred site of protonation. This rapid and fully-reversible detection of HCl vapors at low concentrations makes SNPs suitable candidates for naked-eye sensors. Moreover, we monitored the response of SNP-NDT1 to different acids, such as hydrobromic, nitric, sulfuric, trifluoromethylsulfonic (TFMSA), and acetic acid. Initial exposure for 1 min revealed color changes only in case of HCl. Longer exposure for up to 3 days ensured complete diffusion of acid vapors throughout the material. Accordingly, we also observed marked color change in case of HBr and HNO3, whereas vapors of TFMSA and acetic acid caused only slight shifts of the UV-Vis absorption edge (Figure ). Interestingly, sulfuric acid shifted the absorption edge of SNP-NDT1 towards the blue region by ~12 nm; an electron induction effect into the polymer network which probably stems from a strong interaction of the SO4 2-anion with the polymer network, analogous to charge-transfer complexes formed between sulfate and molecular electron acceptors. Overall, we observe that soft conjugate bases (e.g. AcO -) cause a smaller UV-Vis shift than hard conjugate bases (e.g. |
60c744e8ee301c513dc791ea | 5 | ). This phenomenon merits further study, but a conceivable explanation is that more localised charge-transfer complexes with hard conjugate bases are responsible for a larger UV-Vis shift than weaker, more delocalised CT complexes with soft conjugate bases, as observed previously. Previously we discovered, that SNPs are highly fluorescent in benzene suspensions under UVlight irradiation. Here we confirmed the fluorescence of obtained materials in solid state, including newly synthesized frameworks (Figure ). Absolute quantum yields (AQY) measured under 365 nm UV light irradiation vary from 0.3% (at 79.5% absorbance) for SNP-NDT1 to 1.0% (at 79.9% absorbance) for SNP-NDT2 (Table ). We performed solid-state photoluminescence emission (PLE) measurements in steady-state and time-correlated single photon counting (TCSPC) experiments to better understand, how the protonation event influences the optical properties of the materials. As expected, PLE spectra recorded at 440 nm excitation wavelength revealed marked red-shift of the emission maximum after protonation, with emission maxima appearing in the near IR region up to 788 nm for SNP-BDT1 (Figure ). Table . Porous, optical and electronic properties of SNPs. |
60c744e8ee301c513dc791ea | 6 | SBET (m 2 g -1 ) Eg.dir. (eV) Eg.indir. (eV) PLmax (nm) τavg (ns) 𝝆 (μS m -1 ) These findings are in a good agreement with UV-Vis study -the observed decrease of the optical bandgap width corresponds to a lower transition energy to the excited state, hence, to longer emission wavelengths in fluorescence decay. Average fluorescence life-times estimated by triple-exponential fitting from TCSPC for the pristine polymers are in the range from 0.37 ns for SNP-BTT2 and SP-BTT to 1.06 ns for SNP-NDT2 (Figure , Table , S10). After exposure to HCl, however, we observe a 2-to 3-fold increase in fluorescence life-times for triazinecontaining polymers from 1.03 ns for SNP-BDT1-HCl and SNP-BDT2-HCl up to 1.89 ns for SNP-BTT1-HCl (Figure , Table , S10). The results indicate, that after protonation charge carriers are in general more localized, which will lead to fewer non-radiative charge recombination events, and hence, longer fluorescence lifetimes. Here, we can appreciate the advantage of the modular make-up of SNPs: strong donor-acceptor interactions in SNPs that contain directly linked triazine-and thiophen-moieties enable more efficient charge transferand, hence, comparatively faster exciton decay -than their counterparts where D and A moieties are separated by an aryl spacer. Protonation of the heteroatoms has an influence on the bandgap width and photoluminescence, and it involves charge transport across the π-aromatic network as a whole. Such an increase of charge carrier mobility was reported for p-type doping of semiconducting, linear polymers. Thus, we examined the influence of protonation on the charge carrier mobility of our bulk materials using two-probe measurements (Figure ). Interestingly, there is only a slight measurable increase of conductivity within the same order of magnitude for all SNPs upon activation with HCl vapors (Table , Figure ). However, the thiophene-only SP-BTT framework showed a dramatic increase in conductivity after protonation from 0.415 to 10.371 μS m -1 (Figure ). These results support the fact that donor-acceptor interactions within polymer network will tailor not only optical, but also electronic properties of the desired materials. As seen in the UV-Vis study, protonated triazine-containing SNPs have more localized charges -presumably in the form of Cl-salts stabilized by strong D-A interactions -that do not contribute much to overall bulk conductivity, whereas SP-BTT experiences a higher degree of charge-delocalization and thus showing higher charge carrier mobility. |
60c744e8ee301c513dc791ea | 7 | In the end, we monitored the change in paramagnetic behavior of prepared polymers upon protonation using electron paramagnetic resonance (EPR) spectroscopy (Figure , S47). All pristine materials show the presence of paramagnetic species typical for polymeric networks with extended π-conjugation. The EPR signals are centered around g-values ranging from 2.0035 to 2.0045 (linewidth of about 0.47 to 1.26 mT, Table ) indicating the contribution of heteroatoms to overall charge localization. After exposure to HCl vapors all SNPs show a decrease in EPR signal intensity with the exception of SNP-NDT1 -a polymer that is made up of directly coupled, strongly interacting D-A domains. This supports the hypothesis that charge localization is enhanced by stronger donor-acceptor interactions (Figure ). Again, the homocoupled, sulfur-containing SP-BTT network is the outlier: there is a marked increase in EPR signal intensity after protonation (Figure ). Quantitative analysis of the EPR spectra of SP-BTT shows a 2-times increase of radical concentration from (7±0.2)*10 13 radicals mg -1 (0.12±0.02 nmol mg -1 ) to (1.4±0.2)*10 14 radicals mg -1 (0.23±0.03 nmol mg -1 ) in the protonated state. In the light of the I-V conductivity results, this suggests that protonation leads to an increased delocalization of paramagnetic species and that these paramagnetic species could be contributing to the conductivity of HCl-treated SP-BTT. and the protonated (orange) state. |
60c744e8ee301c513dc791ea | 8 | These observations indicate that the variations of the g-factor are not related to the increased structural mobility of the heated network, but rather to the delocalization of unpaired electrons. The g-factor of both polymers increases upon heating, and it increases further upon cooling for SNP-NDT1. Here, both polymers are switched to a "more localized" spin state. However, SP-BTT is better at delocalizing radical paramagnetic centers along the polymeric chain in comparison to SNP-NDT1 (Figure ). |
668fc32dc9c6a5c07af6baaa | 0 | mRNA acts as a carrier of genetic information and is exported from the nucleus into the cytoplasm, serving as a template for protein production by the ribosomal machinery. The efficiency of protein production is greatly dependent on mRNA stability and the turnover of mRNA in the cytoplasm is constantly regulated by numerous protein complexes to maintain proper protein levels. Eventually, after translation, all mRNA undergoes degradation, however, aberrant mRNA degradation may lead to disease. Two general mechanisms protect mRNA against premature degradation which are incorporation of a 7-methyl guanosine (m 7 G) as a 5'-cap and by connection of a poly-adenine stretch (poly(A) tail) to the 3'-terminus. The 5'-cap-binding complex provides resistance against the 5' to 3' exonucleases , whereas poly(A)-binding protein (PABP) coats the poly(A) tail to protect it from exonuclease cleavage from the 3' end. Poly(A) tails also play an important role in mRNA export to the cytoplasm and help to form a closed loop via interaction of PABPs with cap binding proteins to promote translation. The average length of poly(A) tails in mammals is ~200 nt and the length of it is directly correlated to the translational efficiency of the mRNA transcript. |
668fc32dc9c6a5c07af6baaa | 1 | Once in the cytoplasm, any mRNA will eventually undergo deadenylation in which the poly(A) tail is removed one adenine at a time and this process is considered to be the rate-limiting step of mRNA decay. Two protein complexes are responsible for mRNA deadenylation in eukaryotes: PAN2-PAN3 and CCR4-NOT. Initially, it was proposed that deadenylation is a stepwise process where PAN2-PAN3 is responsible for deadenylating longer poly(A) tails and CCR4-NOT then takes over. However, more recent findings have challenged this hypothesis and shown that CCR4-NOT subunits can displace PABP. Furthermore, sequence specific RNAbinding proteins can recruit CCR4-NOT (Fig. ) to their bound transcripts and fully bypass PAN2-PAN3 catalyzed deadenylation. Although both exonuclease complexes are important, only the depletion of the CCR4-NOT complex from mammalian cells improves overall mRNA half-life while depletion of PAN2-PAN3 seems to have no effect. Therefore, targeting the CCR4-NOT complex by chemical modulators can potentially be used in regulating poly(A) tail length and therefore mRNA half-life and stability. |
668fc32dc9c6a5c07af6baaa | 2 | Figure . Regulation of deadenylation by the NOT9 subunit of the CCR4-NOT complex. The NOT9 subunit can either be bound to RBPs that recruit their specific subsets of mRNA for deadenylation or bind mRNA directly in a non-specific manner. The helical domain used by one of these RBPs to bind NOT9 was converted into a stapled peptide inhibitor that was able to inhibit both protein-protein and protein-RNA interactions simultaneously and impair the activity of the CCR4-NOT complex. |
668fc32dc9c6a5c07af6baaa | 3 | CCR4-NOT is a multi-subdomain protein complex consisting of eight subunits (CCR4, CAF1, NOT1, NOT2, NOT3, NOT9, NOT10, and NOT11, Fig. ). NOT1 acts as the main scaffold subunit where other subunits and modules dock onto. CCR4 and CAF1 are the exonucleases responsible for the catalytic activity of the CCR4-NOT complex and this heterodimeric complex and work in the 3' to 5' direction. The NOT2/3 and 10/11 subunits are non-catalytic and provide a protein-protein interaction (PPI) platform for sequence-specific RNAbinding proteins (RBPs) as well as non-specific RNA-binding capacity. The NOT9 (also known as CNOT9 or Caf40) subunit binds to the (C)NOT9-binding domain (CN9BD) of NOT1 in close proximity to the deadenylases and similar to the NOT2/3 and NOT10/11 subunits it is both a RBP binding site and a site for non-specific RNA binding. Since poly(A) tails have a high sequence similarity across all transcripts, deadenylation selectivity is regulated by RBPs that interact with mRNA in a sequence-specific manner while the non-specific RNA binding of the various subunits provides basal non-transcript-specific deadenylation (Fig. ). Although various studies have investigated which CCR4-NOT subunits are involved in deadenylation, a clear picture of which mRNAs they regulate is still missing. Selective inhibitors for each individual site involved in mRNA recruitment could help to provide further insights into which mRNA sequences are recruited by which site using a chemical biology-based approach. Currently, the only inhibitors for the CCR4-NOT complex available are for the deadenylases which do not help to answer this question as they would shut down deadenylation in general. These include several inhibitors for the exonuclease CAF1 and the most potent molecule has an IC50 value of 0.59 μM. The only inhibitors described for CCR4 are nucleotide monophosphates with the most potent being adenosine monophosphate with an IC50 value of 453 μM. Although these compounds were demonstrated to be able to inhibit deadenylation in vitro, no cellular activity has been reported. Since two exonucleases are present, it is possible that inhibition of only one of them is not sufficient which is highlighted by the fact that inactivating CAF1 or CCR4 through mutation still allows deadenylation. To develop a first site selective inhibitor that does not target the deadenylases directly, we aimed to design inhibitory peptides using a structure-based design approach. As the NOT9 subunit was shown to promote deadenylation and its protein-protein interactions have been well studied from a structural perspective we selected it as a starting point for development of a such a compound. In Drosophila melanogaster (Dm) three RBPs (Bam, Roquin and NOT4) have been described to recruit the CCR4-NOT complex by interacting with the NOT9 subunit. In humans, RNF219 has recently been identified as a regulator of the human CCR4-NOT complex via NOT9 but rather inhibits deadenylation as it has no RNA-binding capacity. High-quality structural data showed that the majority of these RBPs have single α-helical domains to interact with NOT9 referred to as (C)NOT9 binding motifs (CBMs). In contrast to RBP regulated transcript specific deadenylation, mechanistic studies demonstrated the existence of a bulk deadenylation mechanism, where the RNA gets directly recruited to the CCR4-NOT complex via interaction with NOT9 (Fig. ). Additionally, the protein-protein and protein-RNA interactions involved in both mechanisms share the same surface on NOT9 and are mutually exclusive to each other. We hypothesized that inhibiting NOT9 and thereby simultaneously inhibiting its protein-protein and protein-RNA interactions could protect and stabilize poly(A) tail containing RNA from being digested by the CCR4-NOT complex (Fig. ). Such an approach would open a new way to modulate RNA degradation and overall gene regulation. Additionally, NOT9 was found to be overexpressed in breast cancer cells and acted as a part of the oncogenic EGFR pathway making new chemical entities to target NOT9 interesting future drug candidates. Here we report the structure-based design of hydrocarbon stapled α-helical peptides as first-in-class inhibitors of NOT9 to modulate the activity of the CCR4-NOT complex. A hydrocarbon stapled α-helical peptide (NIP-2) has been identified with low nanomolar affinity for NOT9 which competes with RNA-binding and efficiently inhibits the activity of the CCR4-NOT complex in vitro. A crystal structure of the CBM-derived stapled peptide bound to NOT9 was obtained in support of the design strategy and confirmed the helical fold adopted by the stapled peptide. Furthermore, NIP-2 exhibited excellent proteolytic stability but limited cell permeability. To overcome this last issue, specific residues were selected and mutated to alanine which led to NIP-2-H27A with high cell permeability. Treatment of HeLa cells with this compound increased the maximum length of poly(A) tail containing mRNAs by inhibiting the activity of CCR4-NOT in cellulo. |
668fc32dc9c6a5c07af6baaa | 4 | Design of Bam-derived stapled peptides. The D. melanogaster protein Bam has a conserved 22 amino acid N-terminal CBM sequence ( 13 DDQQLDHNFKQMEEHLALMVEG ) that was previously found to serve as a binding motif for the NOT9 subunit of the CCR4-NOT complex. Interestingly, it was found that it also binds human NOT9 with high affinity and co-crystal structure is available (Fig. ). The CBM domain adopts an amphipathic α-helical structure that is bound across the conserved hydrophobic surface of the crescent-shaped NOT9 ARM domain (Fig. ) that is also thought to be responsible for RNA binding. The affinity of the DmBam CBM peptide for human NOT9 was not reported but found to be in the nanomolar range for DmBam (KD = 183 nM for DmNOT9). We assumed that because of the high similarity between DmNOT9 and human NOT9 (79% sequence similarity) the affinity would be similar. Furthermore, the existence of a high resolution crystal structure of its bound state provided a good starting point for the design of a specific inhibitor via hydrocarbon stapling. An initial virtual alanine scan of the wild-type DmBam CBM (named here: NOT9 Inhibitory Peptide -wild type (NIP-WT)) peptide was conducted to identify the hotspot residues that are responsible for NOT9 binding (supplemental Table ). The analysis found that the majority of the identified hotspot residues was hydrophobic in nature (L17, N20, F21, M24, L28, M31, V32, and E33). Next, we sought to truncate the NIP-WT peptide to improve synthetic accessibility and potentially reduce the strong negative charge to promote future cell-uptake. To this end, we performed a short MD simulation (100 ns) of the CBM-NOT9 complex to identify any flexible regions of the NIP-WT peptide that are not making any productive contacts with NOT9 when bound. Indeed, we observed that the N-terminal DDQQ region of the NIP-WT peptide is unstructured during the entire duration of the simulation (Fig. and supplemental Fig. ). This result prompted us to remove this region from the NIP-WT sequence for further peptide design. Additionally, the C-terminal G34 was removed as glycine is known to disturb helix formation resulting in the linear peptide NIP-1 (Fig. ). To evaluate the binding affinity, we fluorescently labelled the full-length and truncated peptides to produce NIP-WT-F and NIP-1-F and measured their affinity for the NOT9-NOT1 complex (consisting of NOT1 1351-1588 and NOT9 19-285) using fluorescence polarization (FP). The complex was co-expressed in E. coli, purified and its formation confirmed using mass photometry (supplemental Fig. ). Interestingly, the truncation significantly affected the binding affinity when comparing NIP-WT-F (KD = 40.7 ± 4.6 nM) to the truncated NIP-1-F sequence (KD = 876 ± 43 nM) (Fig. and supplemental Fig. ). We assumed that although the DDQQ sequence doesn't make any contacts with NOT9, it still plays a key role in helix stabilization as the carbonyl groups of D14, Q15 and Q16 act as a hydrogen bond donors for intramolecular backbone hydrogen bonds and provide a nucleation site for helix propagation. Therefore, we anticipated that introducing a helical constraint in the form of a hydrocarbon staple into the truncated peptide would regain the helical fold and thus recover the binding affinity for NOT9. Furthermore, a hydrocarbon staple is known to have additional benefits such as providing stability against proteolytic cleavage and improved cell-permeation compared to the native peptide sequence. To fulfill this goal, several hydrocarbon stapling sites were explored to induce the native α-helical conformation into the NIP-1 peptide sequence. To install the hydrocarbon staple, two C α -disubstituted amino acids containing an alkene side chain were introduced at i and i+n positions of the linear peptide, followed by cyclizing them by treatment with Grubbs catalyst while the peptide was still on solid support. We initially employed the i,i+4 strategy where two (S)-2-(4-pentenyl)alanines (S5) are incorporated at the i and i+4 positions. To avoid any steric clash with NOT9, the hydrocarbon linkers were installed orthogonal to the CBM-NOT9 binding interface and three different amino acid partners (H19/Q23, K22/E26 and E26/L30) were chosen. We replaced the two methionine residues (M24 and M31) with the chemically stable analogue norleucine as we observed oxidation of the sulfur atoms during the metathesis reaction. All three peptides were fluorescently labelled at the N-terminus to determine their binding affinity for NOT9. NIP-2-F was found to have the highest affinity among all three with a KD of 60.4 ± 15.5 nM compared to NIP-3-F and NIP-4-F (2299 ± 1223 nM and 588 ± 21 nM respectively) (Fig. and supplemental Fig. ). Seeking further optimization of the peptides, NIP-2-F was selected as a starting point where we kept the first stapling position constant, but used a longer linker to connect the i and i+7 residues (H19 = (R)-2-(7-octenyl)alanine and E26 = (S)-2-(4-pentenyl)alanine) to provide peptide NIP-5-F. Furthermore, two double-stapled peptides were designed again using NIP-2-F as a starting point. In the first peptide (NIP-6-F) residue Q23 was replaced with the double alkene amino acid bis-pentenylglycine, while H27 was replaced with (R)-2-(4-pentenyl)alanine to obtain a so-called stitched peptide (Fig. and supplemental Fig. ). For NIP-7-F, the residues H19, Q23, E26 and L30 were replaced with (S)-2-(4-pentenyl)alanine to obtain a double stapled peptide. For these three analogues an accurate affinity could only be measured for NIP-5-F (KD = 601 ± 147 nM), but the determination of the direct binding affinities of NIP-6-F and NIP-7-F was not possible due to their poor solubility in aqueous buffer. Since NIP-2-F still had the highest binding affinity and good solubility properties, it was used for further studies. NIP-MUT-F, a mutant version of the NIP-WT peptide, was generated as a negative control where both L17 and M24 were substituted by glutamic acid which were previously described to disrupt the interaction. FP analysis of FITC-labelled NIP-MUT-F indeed demonstrated it had negligible binding (KD > 10000 nM) to NOT9 (Fig. and supplemental Fig. ). |
668fc32dc9c6a5c07af6baaa | 5 | Next, we measured the helicity of the N-terminally acetylated hydrocarbon-stapled peptides using circular dichroism spectroscopy (CD). In solution, all stapled peptides NIP-2-5-Ac exhibited the characteristic α-helical conformation with two negative minima at wavelengths of 208 nm and 222 nm (Fig. ). In contrast, all linear peptides (NIP-WT-Ac, NIP-1-Ac and NIP-MUT-Ac) did not show much helical character confirming that stapling increases helicity. The highest affinity stapled peptide NIP-2-Ac has the highest helicity (28%) compared to all other peptides. |
668fc32dc9c6a5c07af6baaa | 6 | To verify whether the peptides could compete with native CBM sequences bound to NOT9 we used the fluorescently labelled NIP-WT-F as a tracer in a competitive FP experiment. Increasing concentrations of unlabeled peptides were added and their IC50 values measured as reported in figure and supplemental figure S8. These results demonstrated that all stapled peptides were weak inhibitors except for NIP-2-Ac which could compete with NIP-WT-F to the same degree as the unlabeled NIP-WT-Ac itself. |
668fc32dc9c6a5c07af6baaa | 7 | With the intention of further verifying the interaction between NOT9 and NIP-2-Ac, we performed pull-down experiments using an azide-modified analogue (NIP-2-PEG-N3). The peptide was modified with an azidolysine followed by a double PEG-linker on the N-terminus (a double linker was required for efficient enrichment) and immobilized on dibenzocyclooctyne (DBCO)-magnetic beads via copper-free click chemistry followed by incubation with the purified NOT9-NOT1 complex. Satisfactorily, NIP-2-PEG-N3 was able to enrich NOT9 and NOT1, while the negative control NIP-MUT-N3 showed reduced enrichment (Fig. and supplemental Fig. ). To confirm that the NIP-2-Ac peptide was able to inhibit the interaction between the NOT9 and NIP-WT, we performed the pull-down experiment using the azide-modified analogue NIP-WT-N3 as the pull-down probe in the presence of purified NOT9-NOT1 complex. Addition of NIP-2-Ac indeed led to a significant reduction of the interaction between NIP-WT-N3 and NOT9-NOT1 (Fig. and supplemental Fig. ). Next, we repeated the in vitro pull-down experiment by incubating the beads with HeLa cell lysate, and similar enrichment of NOT9 was observed for NIP-2-PEG-N3 confirming it could interact with the target protein in a more complex biological environment (Fig. and supplemental Fig. ). In this experiment the negative control peptide NIP-MUT-N3 did not enrich NOT9 over the background. |
668fc32dc9c6a5c07af6baaa | 8 | Since the conserved groove of NOT9 has been suggested to be the binding site for both CBMs and nucleic acid, we wanted to investigate whether the NIP-2-Ac peptide could compete with RNA binding. To this end, we first investigated the binding efficiency of the previously described model RNA referred to as A20 which has the sequence UCUAAAU followed by 20 adenosine residues and a 5'-FAM label. At low salt concentrations (10 mM NaCl) A20 exhibited considerable binding (KD = 525 ± 157 nM, supplemental Fig. ) as determined by FP while the shorter A0 RNA lacking the poly(A) tail still bound but with a 3.4 fold lower affinity (KD = 1837 ± 455 nM). This seemed to indicate that RNA-binding to NOT9 is not driven by the poly(A) tail itself but rather by length of the RNA and therefore mainly by electrostatic interactions. To further confirm this, we evaluated the affinity of two RNA sequences where the poly(A) tail was exchanged for pyrimidines with either a poly(C) or poly(U) stretch (C20 and U20 respectively). For both RNAs a binding affinity similar to that of A20 was observed (C20: KD = 798 ± 212 nM; U20: KD = 569 ± 86 nM, supplemental Fig. ). The equal potency for RNAs of equal length but different identity suggests that RNA-binding by NOT9 is non-specific. Indeed, a large positively charged patch on NOT9 is thought to mediate RNA-binding which would suggest that binding occurs via the phosphate diester backbone rather than through specific interaction with RNA bases. The substantially higher affinity of NIP-2-F suggested it should be able to compete with RNA-binding and a competitive FP experiment indeed showed that NIP-2-Ac efficiently displaces the A20 RNA with an IC50 value of 333 ± 34 nM. NIP-WT-Ac was slightly more potent (IC50 = 176 ± 29 nM) while NIP-MUT-Ac (IC50 = 5682 ± 444 nM) was a lot weaker as expected (Fig. ). Nonetheless, the negative control peptide was not fully inactive potentially due to non-specific interaction between the positive patch on NOT9 and the strongly negatively charged peptide. This is in line with previous results using electrophoretic mobility shift assays where the negative control peptide also still moderately inhibited RNA binding. 24 To further validate the interaction between NIP-2-Ac and NOT9, we sought to determine the co-crystal structure. We chose the NOT9-NOT1 complex for co-crystallization as NOT9 alone tends to dimerize according to an earlier report. We obtained crystals and solved the structure of the NIP-2-Ac peptide bound to NOT9 using data until 2.64 Å (Fig. ). The asymmetric unit contained two structurally similar NOT9-NOT1-NIP-2-Ac complexes with an RMSD of 0.533 Å over the C α -atoms. In both complexes, the mode of interaction of NIP-2-Ac with the concave surface of the NOT9 is similar and no contacts between NIP-2-Ac and NOT1 were observed. Both the backbone fold of NIP-2-Ac as well as the side chain orientations closely match the reported wild type α-helical Bam CBM domain bound to the NOT9-NOT1 complex (PDB 5ONA) and the same hydrophobic core is responsible for binding with the NOT9 surface (Fig. ). The crystal structure also allowed us to detect the electron density of the hydrocarbon staple which sits at a site orthogonal to the NIP-2-Ac -NOT9 binding interface as the design intended (see supplemental Fig. ). Apart from hydrophobic interactions, the R130 guanidine from NOT9 contributes to binding via a cation-pi interaction with NIP-2-Ac F21 and a potential salt-bridge with D18 (only observed in one dimer in the asymmetric unit, Fig. ). Additionally, the side-chain amides of NIP-2-Ac N20 and NOT9 N88 form a hydrogen bond, which is also observed in the Bam-NOT9 interaction. In summary, the preorganization of the helical fold by hydrocarbon stapling in NIP-2-Ac correctly mimics the backbone fold of the CBM domain of the Bam protein. |
668fc32dc9c6a5c07af6baaa | 9 | The ability of NIP-2 to inhibit RNA binding by NOT9 suggested it could inhibit bulk deadenylation by the CCR4-NOT complex. To evaluate this, we expressed and purified a CCR4-NOTcore complex which contains NOT9, the deadenylases CCR4 and CAF1, as well as the NOT1 section (residues 1093-1607) that connects these subunits (Fig. ). We expected this complex to be suitable for the evaluation of NOT9 inhibitors as it was previously shown to be able to have increased deadenylation efficiency for poly(A) containing RNAs in comparison with CAF1/CCR4 alone. The reconstitution of the CCR4-NOTcore complex was achieved according to previously reported protocols where two individual protein complexes (CCR4-CAF1 and NOT9-NOT1) were co-expressed and purified separately. These complexes were then combined and purified to reconstitute the CCR4-NOTcore complex and its formation was confirmed by mass photometry (supplemental Fig. ). With the CCR4-NOTcore complex in hand, a gel-based deadenylation inhibition experiment was conducted where 100 nM FAM-labelled A20 RNA was incubated with a fixed concentration of core complex and increasing concentrations of NIP-2-Ac. After incubation, the samples were separated on a TBE-Urea gel to visualize the integrity of the A20 RNA. Dose-dependent inhibition was observed for NIP-2-Ac and the deadenylation process was significantly halted at a 10 μM concentration (Fig. , supplemental Fig. /18/19). As a negative control, a similar inhibition experiment was performed with the mutant peptide NIP-MUT-Ac which was not able to block RNA degradation even at high peptide concentrations (Fig. , supplemental Fig. ). Next, an in vitro deadenylation experiment was conducted in the presence of only the CCR4-CAF1 exonuclease complex. In this case, a much lower degree of degradation was observed even at a double protein concentration and double incubation time in comparison to CCR4-NOTcore confirming the role of NOT9 in increasing the deadenylation rate. However, no inhibition was found at a 10 μM concentration of NIP-2-Ac (Fig. , supplemental Fig. ) confirming that NIP-2's capacity for inhibition of RNA deadenylation occurs via NOT9. |
668fc32dc9c6a5c07af6baaa | 10 | Although we could confirm inhibition of the CCR4-NOTcore complex, it is unclear whether NIP-2 could also inhibit the full complex with all its subunits. Several of these components have been described to be able to bind RNA directly and targeting of NOT9 alone could therefore not be sufficient. The full CCR4-NOT complex can be reconstituted from purified proteins, but using this approach any adapter proteins binding to NOT9 would be absent. Since these can compete with NIP-2 we wanted to evaluate inhibition in a more biologically relevant context. It was previously shown that cell lysates can be used in combination with model RNAs to evaluate deadenylation. To verify this, we incubated the A20 RNA in HeLa cell lysate and indeed observed degradation after electrophoretic separation of the products (Fig. , supplemental Fig. ). Both NIP-WT-Ac and NIP-2-Ac were able to inhibit deadenylation of A20 while NIP-MUT-Ac did not. Interestingly, NIP-2-Ac seemed to be more potent in this assay than NIP-WT-Ac although higher concentrations were required in comparison to the experiments using CCR4-NOTcore. Hydrocarbon stapling has been known to enhance the cell permeability of α-helical peptides by two factors. First, through restricting the backbone in an α-helical conformation forcing the peptide to be amphipathic. Second, the hydrophobic nature of the linker further improves the overall amphipathic character of the helical peptide. Nonetheless, the permeability of stapled peptides is highly dependent on the position of the staple and the overall charge. To determine the cell permeability, we utilized the recently reported NanoClick assay which requires only minimal modification of the peptide with an azide and is particularly suitable for stapled peptides. When cells are treated with such peptides, and only if the peptide can reach the cytosol, the azide will react with a DBCO-modified Halotag-NanoLuc fusion protein. If this reaction occurs it inhibits the generation of a BRET signal that is generated by an azide-modified dye added after peptide treatment providing a readout for cell permeability. The cellular uptake was analyzed by incubating HeLa cells with a dilution series of the peptides starting at 10 μM for 18 hours and the output was recorded as the BRET ratio and normalized as BRET ratio inhibition. The cellular uptake was further compared with the known cell-penetrating peptide (CPP) octaarginine (R8-N3) as a positive control (Fig. , supplemental Fig. ). NIP-2-N3 had an improved EC50 value (2.44 ± 0.91 μM) in comparison to NIP-WT-N3 (EC50 > 10 μM) demonstrating that hydrocarbon stapling significantly promoted cell permeability. However, in comparison to R8-N3 (EC50 = 0.31 ± 0.03 μM), NIP-2-N3 has an almost 7-fold lower uptake. In comparison to previously reported EC50 values for stapled peptides (in the sub-micromolar range), NIP-2-N3 does not perform very well which is likely due to its limited amphipathic character. |
668fc32dc9c6a5c07af6baaa | 11 | Although the cell permeability of NIP-2 was not very high, we wondered how stable it would be against cellular proteases. Peptides can be highly susceptible to proteolytic degradation, but incorporation of unnatural modifications (e.g.: cyclization, D-amino acids, N-methylation, stapling) enforces stability as these are typically not recognized by proteases. To investigate the effect of the hydrocarbon staple on peptide stability both NIP-WT-Ac and NIP-2-Ac were incubated in HeLa cell lysate and the peptide integrity was monitored by HPLC analysis. Peptide NIP-2-Ac exhibited a 3-fold higher stability (t1/2 = 7.3 h) compared to the equivalent linear version NIP-1-Ac (t1/2 -2.3 h), confirming that hydrocarbon stapling protects against proteolytic cleavage (Fig. , supplemental Fig. ). |
668fc32dc9c6a5c07af6baaa | 12 | The results of the in vitro deadenylation experiments demonstrated that we likely needed concentrations exceeding 25 μM to assess the effect of CCR4-NOT inhibition in cells. To improve the uptake of NIP-2-N3 we prepared the octaarginine modified NIP-2-R8-N3 and evaluated it in the NanoClick assay. The conjugate had a 3.4-fold improve cell uptake but polycationic cell-penetrating peptides are known to be toxic in the micromolar range and can displace RNA-binding proteins from RNA. Indeed, when evaluated in a cell viability assay, we found that NIP-2-R8-N3 had an IC50 value of 29.2 ± 0.57 μM limiting its use (supplemental Fig. ). To improve on both cell permeability while avoiding toxicity issues we designed three variants of NIP-2 where a polar residue that was not determined to be a hot-spot in the virtual alanine scan was changed to alanine following previously reported guidelines. All three peptides were modified with an N-terminal azidolysine and evaluated using the NanoClick assay as well as fluorescently labelled to measure their affinity for the NOT9-NOT1 complex. Mutation of aspartic acid in position 18 or glutamic acid in position 26 did result in a moderate 2.1 or 1.6-fold increase in uptake respectively (Fig. ) but the affinity of these compounds was decreased (NIP-2-D18A-F: KD = 393 ± 180 nM, NIP-2-E26A-F: KD = 195 ± 147 nM). Mutation of histidine in position 27 (NIP-2-H27A-N3/F) led to a much stronger increase in uptake of nearly 7-fold (Fig. , supplemental Fig. ). In combination with a moderate 2-fold loss of affinity in comparison to the parent peptide NIP-2-F with a KD of 122 ± 8 nM (supplemental Fig. ) we deemed this sufficient for cellular experiments. Furthermore, we found that the peptide was non-toxic to HeLa cells (IC50 value > 100 μM) (supplemental Fig. ) and was able to inhibit deadenylation by the CCR4-NOTCORE complex at 10 μM (supplemental Fig. ). |
668fc32dc9c6a5c07af6baaa | 13 | To confirm that NIP-2-H27A-N3 was able to engage the target, we performed a thermal shift assay in HeLa cell lysate. In this experiment, the peptide consistently led to a decrease in the melting temperature of NOT9 (Fig. , supplemental Fig. ). Although stabilization is commonly observed in such experiments, destabilization can also occur and in the case of NOT9 inhibition we speculate that this is due to the displacement of protein binding partners or RNA. |
668fc32dc9c6a5c07af6baaa | 14 | To investigate the effect of NIP-2-H27A-N3 on the poly(A) tails of cellular mRNA, we utilized a commercially available poly(A) tail assay that relies on G/I tailing. In this assay, RNA is extracted from treated cells followed by the addition of alternating guanosine and inosine residues using a yeast poly(A) polymerase to the 3'-ends of poly(A)-containing RNA (supplemental Fig. ). The G/I tailed RNA is then converted to cDNA by reverse transcription using the newly added G/I tails as the priming sites. Next, the cDNA is analyzed via RT-PCR using two sets of primers. The first set has a forward primer selective for the gene of choice and a universal reverse primer which anneals to the junction between the poly(A) tail and the G/I tract. The second set of primers contains the same gene specific forward primer while the reverse primer anneals just before the poly(A) tail in the 3' UTR. After PCR amplification, both products are separated on an agarose gel and the difference in length correlates to the length of the poly(A) tail. HeLa cells were treated with the peptides for 24 hours followed by a treatment with actinomycin D to halt new RNA synthesis and subsequent RNA extraction after 1.5 hours. To select suitable genes for analysis we used the mRNA half-life dataset generated by Poetz et al. based on RNAseq analyses in the presence of an RNF219 mutant. This mutant protein is able to bind NOT9 and inhibit deadenylation by the CCR4-NOT complex but has no E3 ligase activity anymore and is therefore expected to have a similar effect as NIP-2. Two genes (RHOB and NR4A1) that had suitable expression levels in HeLa cells were selected and their poly(A) tails were analyzed in the absence or presence of NIP-2-H27A-N3. For RHOB, a significant decrease in the poly(A) tail is observed after new RNA synthesis is halted (compare 0 hours to 1.5 hours) (Fig. , supplemental Fig. ). When the cells are treated with compound, this decrease in the maximum poly(A) tail length was reversed. For NR4A1 the decrease in length between the DMSO treated 0 hour and 1.5 hours analyses is not significant but a strong increase in poly(A) tail length is observed in the compound treated cells (Fig. , supplemental Fig. ). For RHOB the poly(A) tail length increased with 13.1 ± 2.5 nucleotides while for NR4A1 the increase was 15.9 ± 4.5 nucleotides consistent with the findings of Poetz et al. that NOT9 inhibition stabilizes these mRNAs. |
668fc32dc9c6a5c07af6baaa | 15 | Here we demonstrate that peptidic inhibitors can be designed based on the α-helical CBM domain of the DmBam protein which binds the NOT9 subunit. The 22 amino acid long NIP-WT was truncated to a 17-residue peptide and subsequently, a panel of hydrocarbon-stapled peptides was designed to improve affinity and permeability. Among the different stapled peptides, NIP-2 exhibited the highest binding affinity based on the FP experiments, which correlated with high α-helicity as measured by CD spectral analysis. As expected, NIP-2 was able to compete with RNA for binding to NOT9 which is an essential requirement for the inhibition of the deadenylation process and confirms the overlap between the protein and RNA binding sites on NOT9. Furthermore, NIP-2 was able to inhibit deadenylation of a model RNA by the minimal CCR4-NOTcore complex. These results confirm that NOT9 enhances deadenylation rates by inducing proximity between the target RNA and the active deadenylases. When inhibition of deadenylation was tested using lysates that contain the full CCR4-NOT complex we found that NIP-2 did not fully inhibit poly(A) tail removal of the model RNA even at micromolar concentrations. The residual deadenylation activity potentially indicates that various other subunits are involved in non-specific RNA recruitment to the CCR4-NOT complex or it is an indication of PAN2-PAN3 complex activity. |
668fc32dc9c6a5c07af6baaa | 16 | Optimization of the cell permeability of NIP-2 proved most feasible by point mutation rather than through appending a cell-penetrating peptide. The mutation approach has various advantages such as reduced toxicity and a more straightforward synthesis in comparison to preparing conjugates with CPPs. Using the most optimal NIP-2-H27A-N3 peptide we could demonstrate that poly(A) removal by the CCR4-NOT complex can indeed be affected by NOT9 targeting inhibitors in the cellular environment as treatment led to an increase of the maximum poly(A) tail length of NR4A1 and RHOB. The nuclear receptor NR4A1 plays a role in DNA repair mechanisms and increasing its levels has been proposed as a therapeutic strategy in the treatment of various aging related diseases such as diabetes, Parkinson and cardiovascular disease. The small GTPase RHOB has been described as a tumor suppressor and increasing its levels could therefore be beneficial in cancer. Both examples highlight that modulating poly(A) tail length could pose a novel therapeutic strategy that has remained unexplored. |
668fc32dc9c6a5c07af6baaa | 17 | Altogether, we were able to demonstrate that poly(A) tail length modulation can be achieved using chemical inhibitors. Indeed, our inhibitors confirm that NOT9 plays a role in the deadenylation of specific mRNAs either through binding to them in a non-specific fashion for general bulk deadenylation or by recruitment of RNAbinding proteins for which the inhibitory peptides do not discriminate. Future work will aim at developing ligands for other binding sites on the CCR4-NOT complex to further dissect their roles and therapeutic value. We envision that different sites will have effects on different mRNA subsets and that treating cells with different inhibitors will be able to highlight their individual roles in healthy physiology as well as pathogenesis and thereby provide novel therapeutic strategies. |
60c757e4ee301c183ec7b660 | 0 | The release of cargo from soft vesicles is an essential step for chemical delivery related to various processes, including liposome drug delivery, exosome-mediated cell signaling, vesicular transport, intracellular vesicular trafficking, exocytosis, etc. Among these, exocytosis, with a key role in cell communication and possibly a therapeutic target for disease of the nervous or endocrine system, has attracted increasing attention even though its mechanism and dynamics has been investigated for decades. Electrochemical techniques, especially amperometry in combination with ultramicroelectrodes, have been developed as an approach to monitor the release of chemical cargo during the exocytotic event with high sensitivity and spatial-temporal resolution. The experimental signals of monitoring exocytosis, in the form of amperometric "spikes," usually contain complex information about vesicle geometry, cargo quantity, and release dynamics through the exocytotic pore driven and controlled by the SNARE protein complex, actin, and dynamin. For those vesicles isolated from cells, we can also trigger their cargo release (simulate exocytosis) and record the release signal again as "spikes" with our previously reported approach, called vesicle impact electrochemical cytometry (VIEC). However, some difficulties still exist in the dynamic analysis of these spike signals, especially for those involving complex release processes which are difficult to quantitatively describe. Usually, the exocytotic spike is observed as an asymmetrical peak, different in the rising and falling time. The spike decay lasts a longer time and for some spikes this current decay can be fit to a single exponential (I=Ae -αt ), whereas for other spikes to a double exponential (I=A 1 e -αt +A 2 e -βt ) function. The single exponential (SigExp) decay can be easily explained with a diffusion model where the release pore is static. In contrast, the widely observed double exponential (DblExp) decay events during exocytotic release appear to indicate that additional processes besides simple diffusion are involved. and Yue et al. suggested that the DblExp mode of vesicular release might result from the exocytotic pore closing mediated by membrane proteins. Oleinick et al. showed that the interaction of catecholamines with the protein dense core matrix in vesicles can lead to spikes with DblExp in the latter part of the spike. Interaction between chemical cargo and vesicle dense core is certainly important, however, interactions have been shown between the chemical cargo and membranes and these might play a broader role in vesicle release dynamics. These interactions could be broadly applicable as they will be observed in all vesicles, not only in the vesicles with a dense core. To the best of our knowledge this has not been investigated to date. Interaction between the chemical cargo and the membrane, i.e. an adsorption-desorption process, adds an element of complication to the release process model and provide a mechanism of biological regulation. Numerical approaches, represented by the finite element simulation, provide a powerful tool for solving the problems related to complex processes which are difficult with direct analytical approaches. Based on the numerical analysis of the spike signals recorded through the VIEC technique, we can reconstruct the physical model of the entire vesicle release process 28 and include an inverse estimation of the relative specific physical parameters, such as the vesicular pore size, diffusion coefficient of cargo chemicals, desorption rate constant, etc. These parameters can clearly describe the dissociation of cargo from the membrane and how it alters general vesicle release dynamics. |
60c757e4ee301c183ec7b660 | 1 | In this paper, we used similarly sized liposomes but containing different monoamines, dopamine (DA) and serotonin (5-HT) to simulate vesicular release. The use of liposomes avoids the influence of the vesicular dense core. We observed statistically different dynamics of release for the different monoamines. A finite element method, combined with Monte Carlo optimization, was adopted to estimate the dynamic parameters for release of monoamines from the liposomes during VIEC. We provide evidence that these amines differentially adsorb to the membrane lipids in the liposomes or vesicles changing the dynamics by which they exit the vesicle. By fitting to a desorption model, we calculated the desorption rate constants of these two monoamines from the vesicular membrane lipids. DA has a lower desorption rate constant from the liposome membrane, which leads to slower DA release than that observed for 5-HT, while there is little difference in pore size. Although this work describes the desorption-release process for transmitters exiting vesicles during VIEC, the fundamental aspects can be applied to many aspects of chemical or biological vesicle transport. The results experimentally indicate that the process of vesicular release is complicated by interaction between the chemical cargo and the vesicular membrane, thereby altering exocytotic release dynamics. |
60c757e4ee301c183ec7b660 | 2 | In order to study the interaction between different neurotransmitters and the vesicle membrane, we chose to study dopamine-loaded vesicles (DLL) and serotonin-loaded vesicles (SLL). These are both transmitters that are widely distributed in the nervous systems of mammals. These transmitters were loaded into liposomes of similar size as a model of biological vesicles without proteins and cargo with different membrane adsorption properties. The preparation process followed our previous work. Briefly, a mixed solution of phospholipids in chloroform was dried and formed a lipid film in a round-bottom flask. The lipid film was then hydrated in a hydration solution containing 150 mM DA or 5-HT, To prepare a population of DLL or SLL with various sizes. The sizes of vesicles were narrowed by use of reciprocating extrusion through double polycarbonate filter membranes in the same hydration solution and were measured to be 188 nm (polydispersity index=0.13) as the average radius via dynamic light scattering (see more details in Supporting Information). The DLL or SLL are stable in isotonic solution. To trigger and record the release of contents, VIEC was used according as described previously 33 (see Figure , and more details in Supporting Information). When a vesicle settles on the electrode, the high electric field near the surface induces electroporation of the liposome membrane allowing the contents to diffuse out through the pore in membrane at the electrode surface. Released DA and 5-HT are rapidly electrooxidized at the electrode generating a spike shaped current. Using Faraday's law, the charge passed for each current spike (Q, the charge) is proportional to the number of molecules oxidised. In addition, the dynamic parameters of each spike, including the rise time (t rise ), fall time (t fall ), and width at half spike height (t half ) can be used to evaluate release dynamics. 17 |
60c757e4ee301c183ec7b660 | 3 | By applying the VIEC approach to each group of DLL and SLL, the dynamics of release from the vesicles in each group were statistically analysed (2182 spikes for DLL and 2301 spikes for SLL, 10 traces for each, see details in Supporting Information). Typical amperometry traces for DLL and SLL and the spike analysis parameters are shown in Figure and Figure , respectively. The results reveal that the average quantities of both monoamine molecules within each individual liposome and the height of the spike (I max ) of both groups are similar, while a significant increase in t half and also a relative decrease in fall time (t fall ) is observed in the SLL compared to the DLL. Typical spikes (in the form of logarithmic dimensionless current) for each of DLL and SLL are shown to the right of Figure . The decay of the DLL spike has been fit to a rapid decay (~1 ms) and subsequent slow long decay (~10 ms), and it is better fit to a DblExp decay function than a SigExp function, whereas the spike of SLL fits better to only a a SigExp function. We further compared the number of spikes having DblExp vs. SigExp decay for all spikes from DLL and SLL. Indeed, when the ratio of χ 2 (single)/χ 2 (double)>1 set as a cutoff, the percentage of spikes that have a better fit to DblExp decay in the DLL group (~70%) is higher than for the SLL group (~60%). This result shows that dopamine release from the liposomes is more complex and generally slower than 5-HT, which might result from the slower desorption of DA from membrane lipids (liposomes have no dense core). |
60c757e4ee301c183ec7b660 | 4 | Theoretically, as discussed previously, the dynamics of release from liposomes (or vesicles) is thought to be mainly controlled by the product of diffusional flux and the pore area. In contrast to exocytosis where pore opening and closing is driven by the cell, the liposome pore cannot close under a constant strong electric field. Thus, the outflow flux should fit to a SigExp decay following the diffusion model of Cottrell. But if a rate-limiting desorption process is added before release through the pore, the entire release rate becomes a combination of desorption rate and diffusion (via pore) rate, and both can be fit to SigExp decay with different scaling factors. |
60c757e4ee301c183ec7b660 | 5 | If the desorption rate is faster, the release rate will be controlled only by the slower diffusion rate and fit to a single exponential decay (similar to the apparent rate of a multi-step reaction controlled by the rate-determining step). This is shown conceptually in Figure . However, when the rates of the two processes are similar, the apparent rate of the combined process will be expressed as a DblExp mode. |
60c757e4ee301c183ec7b660 | 6 | Fig. A schematic of the desorption-release process. The adsorbed species dissociates from the lipid membrane creating a freely diffusing species. These species are free to exit via the pore as released species. This mechanism is analogous to a 1 st order chemical reaction or one that is further combined as two consecutive reactions and the rate limiting step determines the apparent rate and whether the fall tie is a single of double exponential. The r des is the desorption rate of absorbed species. The r diff is the diffusion rate (i.e. flux) of freely diffusing species. |
60c757e4ee301c183ec7b660 | 7 | We constructed a finite element model to simulate this desorption-release process. The finite element model depicts a spherical liposome (radius 188 nm, experimental average) with a round pore in its membrane. On the other side, the total quantity of chemical cargo was set as 151000 molecules (according to the average experimental current spikes of charge Q=48 fC), but divided into absorbed species (Q s , where s indicates the membrane inner surface) and freely diffusing species (Q f , f indicates the freely moving species). Species need to reach an adsorption-desorption equilibrium before release. If we pre-set parameters describing the adsorption-desorption process, such as the adsorption rate constant (k ads ), of adsorbed molecules in the saturated state (Γ s ), then the Q s and Q f can be calculated by use of Langmuir's adsorption equation and converted into an initial concentration on the membrane (C s,0 ) and in the liposome cavity (C f,0 ). After pore generation, the freely diffusing species exit the pore, while the absorbed species require time to dissociate from the membrane and transfer into the solution phase. The flux of molecules flowing out the pore is converted into current that is then used to fit to the experimental spike and estimate the key parameters in the desorption-release process, including the desorption rate constant (k des ) and radius of the pore (R p ). The Monte Carlo optimization method was used to facilitate these estimates owing to its advantages such as high efficiency to solve complex problems and exemption of any a priori hypothetical relationship between current spikes and initial parameters (see calculation protocol and details in Supporting Information). Four groups of typical DA and 5-HT spikes were analyzed by the finite element simulation. A pair of the experimental spikes and their best fit results are shown in Figure . The DLL spikes show a better fit with a DblExp decay, whereas the SLL spikes fit better to a SigExp decay. By comparing the estimated desorption rate constant (k des ) and pore radius (R p ) corresponding to DA or 5-HT spikes, the pore sizes of both groups (see Table ) cover a similar range (40~90 nm for DLL vs. 40~80 nm for SLL), while the k des of DA is obviously smaller than 5-HT (10 2.3~3.0 s -1 for DA vs. 10 3.5~5.1 s -1 for 5-HT). This smaller k des leads to the slower desorption rate (r des ) and longer time to end of the release, which is consistent with a longer decay for DLL spikes. The smaller k des of DA may result from the greater number of H-bonds (~3 bonds) formed between dopamine and the polar neutral lipid compared to serotonin which can form only 2. The higher free energy of DA to lipid binding (~21 kJ/mol) compared to 5-HT (~14 kJ/mol) 27 make it harder for DA to dissociate. These results support our assumption that different desorption rates alter the release dynamics between these two monoamines (Figure ). It also provides a new perspective for the DblExp decay in the study of bio-vesicular release by the VIEC experiment or exocytosis measured by single cell amperometry. However, it is worth noting that, in the VIEC analysis of native biological vesicles, the proportion of DblExp fitting (empirically 40%~60%) is much higher than that of liposomes (empirically <10%, when the ratio of χ 2 (single)/χ 2 (double)>2 set as the cutoff). This phenomenon likely indicates that the dense core in the bio-vesicles still also plays an important role in regulating release from the vesicle. |
60c757e4ee301c183ec7b660 | 8 | In summary, we employed the VIEC technique to monitor the differential dynamics of chemical cargo release from liposomes loaded with two different electroactive neurotransmitters (DA and 5-HT). Liposomes were used to simulate bio-vesicles without a dense core or proteins. A finite element simulation with Monte Carlo optimization was adopted to estimate the kinetic parameters of chemical desorption and suggests that the rate constant of DA desorbing from the lipids inside the vesicle Is smaller than that for 5-HT. The slower desorption alters the release rate as recognized by a mode of best fit (SigExp or DblExp) for spike signal decay. Our models suggest this might be induced by a stronger interaction between cargo and vesicle membrane lipids, as more hydrogen bonding between DA and membrane lipid molecules can occur than for 5-HT. Hence, the existence of adsorption-desorption behaviour for transmitter molecules and the lipid membrane could be a basic component of the vesicular release process. Although the dense core might also play a crucial role in regulating chemical release from the cells having vesicles containing protein dense cores, regulation via adsorption-desorption from the vesicle wall can occur in all biological vesicles with or without a dense core. A better understanding of the interaction between transmitters and the vesicle membrane might provide strategies to regulate neurotransmitter, hormone, protein or drug release related to cellular communication, intracellular vesicular transport, and controlled delivery of liposomal drugs. EXPERIMENTAL DETAILS Chemicals 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC, >99%), 1,2-dioleoyl-sn-glycero-3phosphethanolamine (DOPE, >99%) and cholesterol (ovine wool, >98%) were purchased from Avanti Polar Lipids, USA. Serotonin hydrochloride (≥98.0%), dopamine hydrochloride (98.0%), chloroform (≥99.9%), methanol (≥99.9%) were obtained from Sigma-Aldrich. All aqueous solutions were prepared using 18 MΩ•cm -1 water from Purelab Classic purification system (ELGA, Sweden). |
60c757e4ee301c183ec7b660 | 9 | Neurotransmitter-loaded liposomes were prepared passively by thin lipid film hydration. A solution of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), 1,2dioleoyl-sn-glycero-3-phosphethanolamine (DOPE) and cholesterol (60:20:20 mole ratio) in chloroform was dried in a round-bottom flask by rotary evaporation until a lipid film was obtained (~3 h). The dried lipid cake was re-hydrated to obtain a liposome suspension by gently mixing with 1.5 mL of the hydration buffer and then left to stand for 30 min under argon gas at room temperature. The liposome suspension was freeze-thawed in liquid nitrogen 3 to 5 times to form multilamellar vesicles, and then extruded 11 times through double polycarbonate membranes of 0.4μm pore size with an Avanti Mini-Extruder (Avanti Polar Lipids, Inc., USA). This procedure yielded liposomes with a mean diameter of 376 nm, as measured by dynamic light scattering (DLS) on a Malvern Zetasizer Nano ZS (Malvern Inc., Malvern, UK). Removal of free DA or 5-HT outside liposomes was achieved by gel filtration on a Sephadex G-25 column which was pre-equilibrated in advance. |
60c757e4ee301c183ec7b660 | 10 | Monitoring the cargo released was accomplished by vesicle impact electrochemical cytometry to detect DA or 5-HT stored in liposomes. A 33-μm carbon fiber electrode was placed in a liposome suspension as shown in Figure of the main text. Liposomes adsorbed on the microelectrode and ruptured via electroporation, the proposed mechanism for vesicle opening in the VIEC. The electrochemical recording of release of individual liposome content was performed by applying a constant positive potential (700 mV vs. Ag/AgCl) to the carbon fiber microelectrode in the form of spikes (a plot of current versus time). By analysis of each spike, important kinetic information about the release event can be obtained. Several parameters used for spike analysis in this work are depicted in the schematic in Figure of the main text including the width of spike at half maximum (thalf) as an indicator of duration of release events; the rise-time (trise), the time from 10% to 90% of amplitude on the rising part of each spike, which reflects fusion pore opening; the fall-time (tfall), the time from 90% to 10% of amplitude on the falling part of each spike that represents the time needed for chemical contents to exit the liposome, and the amplitude of spike (Imax) representing the maximum flux of molecules through the open pore. Additionally, the amount of monoamines (N) released from a single liposome was evaluated with Faraday's law: N=Q/zeF, where Q is the charge calculated by integrating current of each amperometric spike, ze is the number of electrons transferred during the redox reaction (2 for DA or 5-HT) and F is Faraday's constant (96 485 C•mol -1 ). |
60c757e4ee301c183ec7b660 | 11 | Vesicle impact electrochemical cytometry (VIEC) measurements were performed using amperometry at a carbon fiber microelectrode placed in a liposome suspension. The microelectrodes were prepared by aspirating a 33-μm carbon fiber into a glass capillary (o.d. 1.2 mm; i.d. 0.69 mm; no filament; Sutter Instrument Co., USA). A commercial micropipette puller (PE-21, Narishige, Japan) was used to heat and pull the capillary producing two carbon fiber-containing pipettes. A scalpel was used to cut the protruding carbon fiber close to the glass tip and it was then dipped into freshly made epoxy (EpoTek 301, Epoxy Technology, USA) for 3 min. The glued electrodes were cured at 100 °C overnight and subsequently cut at the glass junction. The electrodes were consequently polished at a 45° angle on a commercial micro grinder (EG-400, Narishige, Japan) and backfilled with 3 M KCl. Each electrode was then tested in a 0.1 mM solution of dopamine in phosphate-buffered saline (PBS; pH 7.4) by performing cyclic voltammetry. Only electrodes with proper I-E curves were used for experiments. |
60c757e4ee301c183ec7b660 | 12 | The electrode was kept at 700 mV vs. a Ag/AgCl reference/counter electrode (World Precision Instruments, Inc., USA) using an amplifier instrument (Axopatch 200B, Axon Instruments, USA). The signal was digitized at 10 kHz and filtered with an internal low pass Bessel filter at 2 kHz. The signal was displayed in real time (AxoScope 8.1, Axon Instruments, USA) and stored digitally. |
60c757e4ee301c183ec7b660 | 13 | The amperometric traces were processed by a macro of Igor Pro 6 (Version 6.3.7.2; Page 16 of 24 WaveMetrics, Lake Oswego, OR) designed for analysis of quantal release by the group of David Sulzer at Columbia University. Peaks were detected if they exceeded a threshold of 3 times the RMS noise. Statistical analysis for amperometric measurements data were performed in GraphPad Prism 7 (GraphPad Software, Inc., San Diego, CA). The average of all parameters are calculated as the mean of medians of all recorded traces. |
60c757e4ee301c183ec7b660 | 14 | The finite elemental model for liposomal release was based on the model of a disk electrode detecting exocytosis in our previous work 1 , with a new module for calculating the adsorption-desorption dynamics was added (scheme in Figure ). Schematically, a circle (the radius, Rlip=188 nm) and a pore on the membrane with variable size (Rp) was used to simulate the electroporated liposome membrane where a total quantity of cargo (Q=48.4 fC, the average experimental charge for spikes from DA/5-HT groups) was initially set inside the vesicles, but separated into adsorbed spcies (Qs, s indicates the membrane inner surface) and free species (Qf, f indicates freely moving species). The values for Qs and Qf were calculated a priori based on the Langmuir adsorption model. At time=0 s, the initial surface concentration (Cs,0) and initial concentration of intraliposomal freely moving molecules (Cf,0) was assumed to be at equilibrium, so the initial adsorption rate (rads,0) was equal to the desorption rate (rdes,0). |
60c757e4ee301c183ec7b660 | 15 | Where kads is the adsorption rate constant, kdes is the desorption rate constant, Γs is the surface concentration of adsorbed molecules in saturated state on the membrane. Hence, the initial surface concentration (Cs,0) can be calculated by Meanwhile, the total spike charge Q=Qs+Qf, and ; where F is the Faraday constant. Then Cf,0 was solved by equation 1, |
60c757e4ee301c183ec7b660 | 16 | Finally, a current reflecting the release dynamics was solved by use of Faraday's law and surface integration of the flux density of molecules across the pore, where J(t) is the flux density of molecules across the liposome pore, ze is the charge transfer number of the electrochemical reaction which is 2, and F is the Faraday constant. |
60c757e4ee301c183ec7b660 | 17 | The inverse estimation was based on a Monte Carlo least-squares optimization method. The model parameters include kdes, kads, Γs, Rp. The experimental spike signal was set as the target, and the least sum of the squared difference between the target and the corresponding value calculated by the above finite elemental model was used to search |
64ba769eb605c6803b1d017b | 0 | In the field of DNA nanotechnology, synthetic DNA strands are used to build molecular systems that can exhibit programmable functions of increasing complexity. The unique predictability of DNA-DNA interactions allows rationally designed synthetic DNA strands to be used as building blocks for the construction of 2D and 3D nanostructures with defined geometries. Synthetic DNA strands can also be site-specifically modified with a wide range of functional components, including optical labels, recognition elements, and proteins, giving otherwise inert DNA-based structures different functionalities. In addition, DNA switches and devices can also be designed to respond to external stimuli such as temperature or pH. The programmability and responsiveness of synthetic DNA described above has been exploited over the past two decades to create DNA-based structures that can perform mechanical work in response to specific inputs. Recently, basic machine elements made of DNA such as hinges, joints, arms, and levers have been demonstrated that can be controlled by DNA-DNA interactions or by environmental stimuli such as pH, ionic strength, temperature, or external fields. Recently, for example, Dietz and Simmel described a rotating ratchet motor made entirely of synthetic DNA. The rotor achieves rotational speeds and torques similar to those of other natural molecular machines, such as ATP synthase, and can move in a specific direction by applying a simple external AC field. DNA-based devices and machines can also be developed for molecular transport mechanisms. |
64ba769eb605c6803b1d017b | 1 | For example, following the example of kinesin and dynein, which move along microtubules, synthetic DNA walkers have been developed that move along specific 2D and 3D DNA tracks thanks to the programmability of DNA-DNA interactions. Despite the above advances in generating motion in DNA-based structures, to our knowledge, no autonomous DNA-based motor has yet been described that can self-propel in fluids and perform net translation (swimming). |
64ba769eb605c6803b1d017b | 2 | In recent years, several synthetic micro-and nanoscale systems have been described that can move in fluids thanks to the application of an external energy source such as magnetic, 22 light, or ultrasonic fields. Other important examples of micro/nanomotors include those driven by chemical reactions between the surface of the motor and a chemical propellant present in solution. A classic example in this regard is the use of catalytic surfaces such as platinum to decompose H2O2 in a solution and generate bubbles that propel the micromotor forward. More recently, enzymes have also been used as powerful catalysts to enable self-propulsion of microand nanomotors with biocompatible and bioavailable fuels. In this case, micro-and nanoparticles are functionalized with enzymes that catalytically convert a specific substrate into products, creating a chemical gradient around the particles that generates a driving force. These systems offer promising features for biomedical applications, such as the use of biocompatible and bioavailable fuels, chemotactic movement toward or away from chemical gradients, and the absence of external energy sources. Recently, enzyme-driven motors have also been equipped with pH-responsive DNA nanoswitches to create a device that is able to swim and simultaneously sense the pH of its surrounding environment. Despite the above advantages, such enzymedriven micro/nanomotors also suffer from some limitations. For example, the potential toxicity of their components (metals, silica, and polymers) may limit their application in clinical settings. In addition, it is not always easy to control the geometry and shape of the particles (especially at the nanoscale) in these materials, which could be critical for improving propulsion efficiency. Finally, it is also difficult to achieve efficient surface functionalization with enzymes and to control their distribution and concentration. To overcome the above limitations, we propose here to combine DNA structures with enzyme catalysis to build self-propelled DNA-based nanoswimmers (hereafter referred to as "DNA-enzyme nanoswimmers") that would enable easier surface enzyme modification, controlled degradability, biocompatibility, and shape flexibility. As a model system we used a tubular DNA structure and decorated it with a motor enzyme so that the DNA structure is able to move (swim) independently and unhindered in the presence of the enzymatic substrate (Figure ). |
64ba769eb605c6803b1d017b | 3 | The DNA structural scaffold used in this work is a well-characterized hollow tubular micrometer-scale structure formed by the interaction of specifically designed DNA tiles at room temperature. Such DNA tiles are formed by hybridization of five different DNA strands that have 4 sticky ends responsible for self-assembly. To directly visualize the assembled tubular structures, we conjugated a Cy3 fluorophore to the 5' end of one of the tile-forming strands. We then engineered another tile-forming strand to have an addressable 30-nucleotides (nt) singlestranded anchor domain that can be used for enzyme functionalization of the structure (Figure ). The assembled structures can be conveniently imaged by fluorescence microscopy and have an average length and count of 4.9 ± 0.3 µm and 5.2 ± 0.2 x 10 3 count/mm 2 , respectively (Figure , right). |
64ba769eb605c6803b1d017b | 4 | For the functionalization with the enzyme, we first selected urease, because this is often used for the development of enzyme-driven micro-and nanoswimmers thanks to the propulsion generated by the conversion of urea (CO(NH2)2) into ammonium (NH4 + ) and bicarbonate (CO3 2-). More specifically, this movement is thought to be the result of a gradient of ionic products (ionic self-diffusiophoresis) around the swimmer triggered by the enzymatic reaction. To better visualize the enzyme, we first labeled urease with a Cy5 fluorophore using a Cy5-NHS ester that is reactive toward amine groups in the protein (see Supporting Information for more details). The Cy5labeled urease was then functionalized with an N3-containing reagent that adds an azide handle to urease by reacting with the amine groups. The resulting azide-Cy5 urease was then conjugated to a dibenzocyclooctyne (DBCO)-modified ssDNA strand using strain-promoted azide-alkyne cycloaddition (SPAAC). The DNA-enzyme conjugate was then purified by anion-exchange chromatography (Figure To find the best conditions for enzyme functionalization, we assembled DNA structures with different percentage distribution of the anchor strand by using different proportions of tiles with and without anchor strand during self-assembly. The efficiency of the self-assembly process was not affected by the presence of the anchor strand, as the size and number of nanostructures formed did not show significant differences in the absence and presence of different proportions of anchor strands (Figures ). To all assembled structures, we then added the DNA strand conjugated with urease at a fixed excess concentration (i.e., 200 nM) and quantified the mean fluorescence intensity of Cy5 urease on the surface of the DNA structures (Cy3). The binding of the enzyme to the structure increases with the percentage of tiles with the anchor strand until it levels off at 50%. By further increasing the relative proportion of anchor strands in the structure, less enzyme decoration is observed, likely due to enzyme aggregation effects (Figures ). For future experiments, we then selected DNA structures containing 30% of the tiles with the anchor strand (Figure ). Under these conditions, we find a homogeneous distribution of urease across the DNA structures. For example, the values for the average length (Cy3-DNA structure: 5.0 ± 0.3; Cy5-urease: 4.4 ± 0.1 µm) and count (Cy3-DNA structure: 3.3 ± 0.6; Cy5-urease: 3.6 ± 0.4 x 10 3 count/mm 2 ) obtained by measuring either the Cy3 (DNA tiles) or Cy5 (enzyme) signals are comparable (Figure ). The homogenous enzyme distribution is also confirmed by analysing the pixel intensity of DNA tiles and urease along the entire length of a single DNA structure (Figure ). From these analyses we derived a homogeneity factor (defined here as the average ratio of urease (Cy5) signal to DNA structure signal (Cy3) along the length of the DNA structure) of 0.7 ± 0.1. Finally, to better quantify the distribution of urease on the DNA structure, we calculated a co-localization factor that we used to estimate the overlap of the urease signal (Cy5) with the DNA structure signal (Cy3). A value of this factor around 1 would indicate a high co-localization of the enzyme with the DNA structure, whereas no overlap would result in a value around 0. In our case, a co-localization factor of 0.9 ± 0.1 suggests that the enzyme is highly co-localised with the DNA tiles (Figure ). |
64ba769eb605c6803b1d017b | 5 | Next, we investigated the movement capabilities of urease-functionalized DNA structures. To induce active movement, we exposed the structures to different concentrations of urea (from 10 to 300 mM) (Figure ). We recorded videos of 30 seconds duration at a rate of 20 frames per second (see Supporting Videos 1 and 2). To track the trajectories of the DNA-enzyme nanoswimmers, we developed the Nano-Micromotor Tracking Tool (NMTT) v 1.0.0, a Python-based script that uses computer vision techniques to track the position of one or more particles in time (see details in Supporting Methods), which allowed us to calculate the mean square displacement (MSD), diffusion coefficient, and speed of the motors (see Supporting Information). Snapshots of nanoswimmer motion trajectories 30 seconds after the addition of urea show significantly longer trajectories for nanoswimmers exposed to 100 mM and 300 mM urea compared to those obtained in the absence of urea. |
64ba769eb605c6803b1d017b | 6 | Representative trajectories of different motion experiments under these conditions (0, 100, and 300 mM urea) are also shown in Figure . From these trajectories, the MSD and associated motion parameters can be extracted using the Python-based Nano-Micromotor Analysis Tool (NMAT) v 1.0.0 40 (Figure , left). We observed a clear correlation between the amount of fuel and the MSD of DNA enzyme nanoswimmers, in a concentration-dependent manner. With increasing urea concentration, the MSD shows a deviation from linear diffusion to a non-linear MSD characteristic of self-propelled motion. This is particularly visible in the case of 300 mM urea. Given their anisotropic shape and the homogeneous distribution of enzymes, one would not expect these nanotubes to exhibit ballistic motion, but only some degree of anomalous superdiffusion defined by an MSD scaling parameter 1< α < 2, as appears to be the case (Figure ). In the absence of a clear theory of active Brownian motion that would allow us to clearly characterize this case, we decided to investigate both the effective diffusion coefficient (Figure ) and the effective speed (Figure ) under an active Brownian motion regime with a ballistic component. We observed a concentration-dependent increase for both parameters, with a concentration of 300 mM leading to a significant increase in both the effective diffusion coefficient and speed. To exclude any effect of the fuel concentration on the diffusivity of the swimmers, we exposed the DNA structures without urease on their surface to concentrations of 0, 100 and 300 mM urea. Non-functionalized DNA nanostructures exposed to 0 and 100 mM urea showed a linear MSD, indicating purely diffusive motion, without significant differences (measured effective diffusion coefficient 0.7 ± 0.3 µm 2 /s and 0.6 ± 0.2 µm 2 /s, respectively) (Figure ). In the case of DNA nanostructures, without urease, exposed to 300 mM urea, we could not track their trajectories because the DNA nanostructures disassembled during video recording (see Supporting Video 3). We attribute this effect to the fact that urea at high concentrations is a DNA denaturing agent, causing the destabilization of the double DNA helix structure. Interestingly, we did not observe this effect in ureasefunctionalized nanoswimmers. We explain this difference by the fact that urease continuously converts urea, which leads to a decrease in the local urea concentration and thus preserves the stability of the DNA nanostructure. |
64ba769eb605c6803b1d017b | 7 | Next, we explored the potential versatility of our DNA enzyme nanoswimmers by using another enzyme as a source of self-propulsion (Figure ). For this purpose, we chose catalase, the most commonly used enzymatic drive for self-propelled micro-and nanomotors. Catalase is capable of converting hydrogen peroxide (H2O2) into water and oxygen (O2), which can lead to self-propulsion by i) the generation of bubbles or ii) a diffusiophoretic motion mechanism. We conjugated catalase to ssDNA strands using a reaction similar to that used to prepare urease-DNA conjugates (see the experimental section in the supporting information and Figure ). We then functionalized the DNA nanostructures using 30% of the tiles with anchor strand (as in the case of DNA urease nanoswimmers) (Figure ). We detected the presence of catalase (Cy3) on the surface of the DNA nanostructures (Cy5) using fluorescence microscopy images (Figure ). Comparable values for average length (Cy5 DNA structure: 2.8 ± 0.3; Cy3 catalase: 2.3 ± 0.2 µm) and count (Cy5 DNA structure: 4.4 ± 0.2; Cy3 catalase: 4.4 ± 0.4 |
64ba769eb605c6803b1d017b | 8 | x 10 4 counts/mm 2 ) were obtained, demonstrating a homogeneous distribution of catalase in the DNA structure (Figure ). Such a homogeneous distribution was also confirmed by analysis of the signals from the enzyme and DNA tiles along the DNA structure (homogeneity factor: 0.8 ± 0.1) (Figure ). Finally, we also found a high degree of co-localization of catalase with the DNA structure in this case (co-localization factor = 0.9 ± 0.1) (Figure ). Next, we examined the motility of the catalase-DNA swimmers when exposed to 1.5% H2O2 (see Supporting Videos 4 and 5). The nanoswimmers showed longer trajectories (Figure ), higher MSD (Figure ), higher effective diffusion coefficient (Figure ), and speed (Figure ). Similar to the case of urease nanoswimmers, we found a value of the MSD exponent of 1< α < 2 (see Supporting Figure ) for the nanoswimmers in presence of fuel. For this reason, we decided to analyse both effective diffusion coefficient and effective speed. The average effective diffusion coefficient for catalase DNA swimmers without fuel was 0.6 ± 0.3 µm 2 /s (mean ± SD), whereas the effective diffusion coefficient increased to 0.9 ± 0.6 µm 2 /s in the presence of propellant. As for the effective speed, a mean value of 0.5 ± 0.2 µm/s was observed for the nanoswimmers exposed under control conditions, which increased to 0.9 ± 0.4 µm/s. Both the increase in effective diffusion coefficient and effective speed were statistically significant (P < 0.05). |
64ba769eb605c6803b1d017b | 9 | Taken together, our results show that synthetic DNA has great potential as a building block for creating artificial nanoscale molecular motors that can self-propel in fluids. In addition, thanks to the use of enzymes, biologically available and biocompatible fuels can be used as a source of self-propulsion. We believe that the results reported here will pave the way to more sophisticated designs of DNA-based enzyme-powered motors, where synthetic DNA can lead to the discovery of new structural designs and allow programmable control of the decoration of enzymes and other biomolecules on their surfaces. The above properties, together with the sequence specificity of the DNA-DNA interactions, may enable the construction of enzyme-driven DNA motors that can respond to different substrates in the same solution and perform different motion dynamics in a fuel-dependent manner, paving the way for new approaches to understanding nanoscale motion and enabling better control over the design and functionality of nano/micro-swimmers. |
65acde689138d231616726ba | 0 | The study of diffusivity is critical in the domains of industrial engineering, environmental control, pollution control, biology, and isotope behavioral studies and their separation. Knowledge of the diffusion coefficient is taken into consideration during the development of scientific equipment and during the investigation of mass transfer. Coefficients of diffusion can either be computed empirically or via experimental means. The mass diffusivity is theoretically determined using analytical methods. The major problem that is encountered indetermination using empirical relations is that they fail at regimes of high concentration. So, there is a need for the development of reliable experimental techniques. |
65acde689138d231616726ba | 1 | Various experimental techniques are employed to determine diffusion coefficients. However,the results obtained using either approach are not precise. If we aspire to obtain a higher degree of precision is necessary, an experimental procedure is to be employed. The Wiener's process, light beam deflection techniques, decaying pulse technique, quasi-steady-state diffusion via a porous diaphragm, and interferometry are all the major experimental approaches that one can employ for assessing the mass diffusivity of a given species experimentally. |
65acde689138d231616726ba | 2 | Optical interferometry is one of the several techniques available for diffusivity determination. The theoretical basis of using an interferometry approach for diffusivity determination is based on the fact that the concentration distribution alters the optical path length of light travelling through a material during a diffusion process, resulting in the formation of fringes. These fringes are collected either manually or electronically using specific instruments. By interfering with a reference beam, the information stored in the interference pattern may be utilized to rebuild the concentration distribution and hence the diffusion coefficient. |
65acde689138d231616726ba | 3 | The analysis of their shape, size, variation with factors such as the time and the concentration gradient is essential for forming the basis of diffusivity determination. These fringes are the data collected from the experiments. Then, the collected data is resolved in both space and time. Fringes represent the concentration field in the space-time domain from which diffusivity canbe experimentally measured. For the calculation of the diffusion coefficients in clear liquid mixes, optical techniques such as classical interferometry, holographic interferometry, and electronic speckle pattern interferometry are generally utilized. Various types of interferometers are used for the experiment . In this term paper, we have restricted the discussion to optical interferometry-based techniques for diffusivity measurements. Here, both classical and modern interferometry-based techniques have been discussed. The following techniques like Phase Shifting Interferometry, Common Path Shearing Interferometry, Holographic Interferometry, Electronic Speckle Pattern Interferometry, Multiple Beam Interferometry and Michaelson Interferometry have been selected owing to the fact that they are used widely for various laboratory and industrial applications from a plethora of optical techniques available. Each technique has been briefly introduced in the form of its scientific basis and followed up by the experimental procedure and analysis. Care has been taken to discuss various aspects such as advantages and disadvantages of each technique mentioned above. The term paper aims at giving the reader a brief overview of the workings of the optical interferometry-based techniques for diffusion coefficient determination mentioned above. They have been discussed below in the next section. |
65acde689138d231616726ba | 4 | Bruning et al. developed the first phase-shifting interferometer (PSI) in the 1970s. The PSI technique is used to determine the diffusion field in the area of interest in real-time as it hashigh spatial and time resolution. We know in a dilute solution; the refractive index varies linearly with the concentration of the solute . The interferometer measures this refractive index change, which is then used to obtain the concentration profile and subsequently the diffusion coefficient. The PSI scans the interference fringes, leading to the development of a detailed pattern of the observation region. A local profile is generated between two neighboring fringes on an atomic level. |
65acde689138d231616726ba | 5 | A Mach-Zehnder interferometer was used, and the given setup was assembled. With the use of a polarizing beam splitter, a laser diode beam was divided into reference and measurement beams. The beams were combined by another beam splitter after travelling through a compensator and a test cell. As these beams were polarized into perpendicular planes, they did not show interference. A quarter-wave plate was put in front of the charge-coupled device (CCD) camera to convert the two linearly polarized beams to right-or left-circularly polarized beams prior to entering the phase splitting 3-CCD camera. The three polarizers were set at the angle of -π/4, 0 and π/4.This led to the generation of three interferograms with phase-shifting of λ/4 with respect to each other. |
65acde689138d231616726ba | 6 | The interferograms were constructed using the transient diffusion field data. They were then converted into phase-shifting data using a signal processor. Greyscale images of 0 to 255, which correspond to -π/2 to π/2, were recorded. From the fringe profile obtained, the value of the instantaneous diffusion coefficient was evaluated by relating it to Ficks's laws . |
65acde689138d231616726ba | 7 | This technique allows us to obtain high accuracy compared to conventional interferometers . The most significant strength of this method over a regular interferometer is the high phase resolution that is obtained. A small amount of solution is needed for the determination of the diffusion coefficient. Finally, one experiment is of the order of a coupleof minutes, and it is fast compared to conventional means . |
65acde689138d231616726ba | 8 | In this method, a Wollaston prism is used with the combination of a polarizer and an analyzer. The sensitivity of the interferometer, the divergence angle of the prism and the focal length of the lengths used are changed for adjustment. This process is used for obtaining the refractive index distribution in the mixing zone of the liquids. As time proceeds, the liquids begin to diffuse into each other, and the readings are obtained. |
65acde689138d231616726ba | 9 | CSPI has an easy alignment of the focused light. Another major advantage over point diffraction interferometer is that it is able to calculate diffusion coefficients for solutions with large refractive index variations. The fringes are related to the evolution of the concentration gradient. The concentration gradient is integrated to obtain the final concentration profile . |
65acde689138d231616726ba | 10 | In the holographic interferometry setup, we are able to record the fringe, which is in line andare of the same phase difference between the waves coming out of the diffusion cell at two different times. The interferogram fringes have a distinctive form with two extremes. A given fringe's deflection is proportional to the time difference between concentrations. We essentially measure the time difference of the extremes of a given concentration profile. Sandwich holography setup allows for two exposures on two separate holographic plates, which are then combined in a plate holder, and an image is reconstructed from a sandwichholograph. It exhibits the same fringe pattern as a normal double exposure hologram, but because the images are on two distinct plates, the fringe pattern may be manipulated by rotating and tilting the sandwich pair. This enables better accuracy compared to the other holographic methods. |
65acde689138d231616726ba | 11 | The source of light for this experiment was a Helium-Neon laser. Real-time holographic recordings were generated in the experiment. The plates were replicated in exactly the same position after the time of observation in order to obtain the diffusion coefficient. The mirrors were used to slightly deflect the laser beam. If one has to obtain the diffusion coefficient, thenit is necessary to measure the distance between the two extremums of the profiles obtained. |
65acde689138d231616726ba | 12 | Another major advantage of this process is that it does not involve careful mapping or any specific calibration. Irregularities show up in the interferograms, and some of them might be discarded if they are full of errors. . However, due to its long experimentation times, environmental and gravitational field effectsmay have a major impact on the results giving rise to errors . Also, incorporation of large errors might take place due to the difficulty in locating the peaks in the concentration of the diffusion profile . The error obtained in this is of the order of 1% . |
65acde689138d231616726ba | 13 | The primary advantage of sandwich holography is the ability to minimize undesired fringes created by the object's rigid body motion. The disadvantage of this technique is the need for repositioning of the plates with high accuracy for proper reconstruction . Hence, phase-shifting interferometry is preferred over single and double exposure modes. |
65acde689138d231616726ba | 14 | The major change is that here the recording takes place by using a camera, and a recording medium is not used, as in the case of holographic interferometry. The photosensor used is not able to reconstruct the hologram optically; hence the reconstruction process is electronic and is viewed using a digital monitor. |
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