structure - based drug design and often ligand scaffold hopping is performed in the absence of a protein structure . scaffold sah was divided into three substructure parts as group-1 ( 2-amino-4-mercaptobutanoic acid ) , group-2 ( 9h - purine ) , and group-3 ( tetrahydrofuran-3,4-diol ) shown in figure 1 . crystal structure of methyltransferase with its inhibitors s - adenosyl - l - homocysteine in dark yellow color docking is drug designing program on the basis of receptor and ligand . it is applied to predict the structure and binding free energy of receptor and ligand complex . based on the extent of flexibility docking can be classified into four classes : both the receptor and ligand are flexible , receptor is flexible and ligand is rigid , ligand is flexible and receptor is rigid , and both the receptor and ligand are rigid . libdock module of discovery studio 3.5 was used for docking of the analogs of sah and target protein . the binding site was created by selecting sah using discovery studio 3.5 having binding site dimensions x ( 15.12 ) , y ( 13.23 ) , and z directions ( 17.28 ) for docking . the conformations of compounds were generated with maximum 225 numbers of conformations to be generated , and conformations of separate isomers were also created within the threshold of 20.0 kcal / mol relative energy . the charmm force field was applied to minimize the compounds with 1000 steps of steepest descent ( sd ) algorithm . the having a root mean square deviation ( rmsd ) < 1.0  were considered as duplicates as the higher specified rmsd value will reduce the number of ligand poses returned and an rms gradient 0.001 . libdock is a high - throughput algorithm developed by diller and merz , which consist of the polar and apolar features as  hotspots . the molecules which passed the applied filters were docked with the crystal structure of mtase ( pdb i d - 2p41 ) in complex with guanine - n7 and adenosine-2o methylation ( 7-megpppg2ome ) and sah . charmm force field was applied for docking and scoring , and other docking parameters were kept default . ligand - receptor minimization in situ during dockingwas performed on the complexes to remove any ligand van der waals clashes prior scoring and calculating binding energy . the 5000 steps of sd with free movement of atoms within the binding site sphere were used during the minimization . the binding energy of protein - ligand complexes was calculated from the free energies of the complex , and free energies of individual protein and the ligand using charmm force field and implicit salvation method . ligands were prepared for use in docking and other applications by using discovery studio 3.5 , particularly for those which require a three - dimensional ( 3d ) coordinates and biological ionization and tautomerization states . when studying receptor - ligand interactions and other areas , it is important to correctly prepare the ligands . different protonation states , isomers and tautomers typically have different 3d geometries and binding characteristics . admet properties of the drug should be optimum at least to get drug absorbed and distributed to the site of action . the ratio of lipophilicity and water solubility should be according to the lipinski rule of five . as a highly soluble drug can not cross the membranes and a highly lipophilic drug gets the problem to get dissolved . hence , adme and toxicity prediction of compounds was done using admet and toxicity prediction modules of discovery studio 3.5 . adme descriptors allow eliminating the compounds with unfavorable admet characteristics early on to avoid expensive reformulation cost later and , for structural refinements that are designed to improve adme properties , prior to resource expenditure on synthesis . analogs were also subjected for analysis of topkat_fda_male / female mouse_noncarcinogenicity versus carcinogenicity probability where carcinogen versus noncarcinogen , probability below 0.3 indicates a noncarcinogen , and probability above 0.7 signifies a carcinogen . cytochrome p450 2d6 ( cyp2d6 ) plays an essential role in the metabolism of a wide range of xenobiotics in the liver and its inhibition by a drug constitutes a majority cases of drug - drug interaction . topkat module of discovery studio 3.5 validates toxicity estimation through quantitative structural toxicity relationship and similarity searching of the model 's database . on the basis of query compound structure , predictive models perform an accurate and valid estimation of the query structure because the model is accurately predictive in that region of space . replacement of the fragments of the compound sah was done using the lead optimization module of discovery studio 3.5 . structure - based drug design and often ligand scaffold hopping is performed in the absence of a protein structure . scaffold sah was divided into three substructure parts as group-1 ( 2-amino-4-mercaptobutanoic acid ) , group-2 ( 9h - purine ) , and group-3 ( tetrahydrofuran-3,4-diol ) shown in figure 1 . crystal structure of methyltransferase with its inhibitors s - adenosyl - l - homocysteine in dark yellow color it is applied to predict the structure and binding free energy of receptor and ligand complex . based on the extent of flexibility docking can be classified into four classes : both the receptor and ligand are flexible , receptor is flexible and ligand is rigid , ligand is flexible and receptor is rigid , and both the receptor and ligand are rigid . libdock module of discovery studio 3.5 was used for docking of the analogs of sah and target protein . the binding site was created by selecting sah using discovery studio 3.5 having binding site dimensions x ( 15.12 ) , y ( 13.23 ) , and z directions ( 17.28 ) for docking . the conformations of compounds were generated with maximum 225 numbers of conformations to be generated , and conformations of separate isomers were also created within the threshold of 20.0 kcal / mol relative energy . the charmm force field was applied to minimize the compounds with 1000 steps of steepest descent ( sd ) algorithm . the having a root mean square deviation ( rmsd ) < 1.0  were considered as duplicates as the higher specified rmsd value will reduce the number of ligand poses returned and an rms gradient 0.001 . libdock is a high - throughput algorithm developed by diller and merz , which consist of the polar and apolar features as  hotspots . the molecules which passed the applied filters were docked with the crystal structure of mtase ( pdb i d - 2p41 ) in complex with guanine - n7 and adenosine-2o methylation ( 7-megpppg2ome ) and sah . charmm force field was applied for docking and scoring , and other docking parameters were kept default . ligand - receptor minimization in situ during dockingwas performed on the complexes to remove any ligand van der waals clashes prior scoring and calculating binding energy . the 5000 steps of sd with free movement of atoms within the binding site sphere were used during the minimization . the binding energy of protein - ligand complexes was calculated from the free energies of the complex , and free energies of individual protein and the ligand using charmm force field and implicit salvation method . ligands were prepared for use in docking and other applications by using discovery studio 3.5 , particularly for those which require a three - dimensional ( 3d ) coordinates and biological ionization and tautomerization states . when studying receptor - ligand interactions and other areas , it is important to correctly prepare the ligands . different protonation states , isomers and tautomers typically have different 3d geometries and binding characteristics . admet properties of the drug should be optimum at least to get drug absorbed and distributed to the site of action . the ratio of lipophilicity and water solubility should be according to the lipinski rule of five . as a highly soluble drug can not cross the membranes and a highly lipophilic drug gets the problem to get dissolved . hence , adme and toxicity prediction of compounds was done using admet and toxicity prediction modules of discovery studio 3.5 . adme descriptors allow eliminating the compounds with unfavorable admet characteristics early on to avoid expensive reformulation cost later and , for structural refinements that are designed to improve adme properties , prior to resource expenditure on synthesis . analogs were also subjected for analysis of topkat_fda_male / female mouse_noncarcinogenicity versus carcinogenicity probability where carcinogen versus noncarcinogen , probability below 0.3 indicates a noncarcinogen , and probability above 0.7 signifies a carcinogen . cytochrome p450 2d6 ( cyp2d6 ) plays an essential role in the metabolism of a wide range of xenobiotics in the liver and its inhibition by a drug constitutes a majority cases of drug - drug interaction . topkat module of discovery studio 3.5 validates toxicity estimation through quantitative structural toxicity relationship and similarity searching of the model 's database . on the basis of query compound structure , predictive models perform an accurate and valid estimation of the query structure because the model is accurately predictive in that region of space . pdb structure of mtase protein ( pdbid -2p41.a ) was retrieved from protein drug bank ( http://www.rcsb.org/pdb/home/home.do ) . mtase contains 7-megpppg2ome and sah where sah is shown in the binding pocket in dark yellow color in figure 1 . the bioisosteric replacement of group-1 ( 2-amino-4-mercaptobutanoic acid ) , group-2 ( 9h - purine ) , and group-3 ( tetrahydrofuran-3,4-diol ) [ figure 2 ] generated 93 , 89 , and 132 new bioisosteric analogs of sah , respectively . structure of s - adenosyl - l - homocysteine showing groups modified all the designed analogs of sah were subjected for in - silico adme analysis using discover studio 3.5 . only 41 analogs could pass the admet filter ( lipinski rule of five ) and toxicity filters ( carcinogenicity , mutagenicity , cyp2d6 prediction , and toxicity ) . a drug should have to get dissolved , i.e. , the drug should be soluble because solubility plays a significant role in drug action . hence , solubility range should between the 8.0 ( extremely low solubility ) and 0.0 ( optimal solubility ) . levels defined for solubility signified that the compounds with solubility levels 3 and 4 have good and optimal solubility , respectively , therefore these analogs have solubility as per ro5 as tabulated in table 1 . inhibitor analogs with good admet properties absorption of the drug should also be good so that a large amount of drug can reach at the site of action . absorption of a compound depends mainly on alogp and polar surface area ( psa ) of that compound . alogp98 denoted lipophilicity ( alogp ) value of the compound where the value of it should be between the 2.0 and 5.0 for good intestinal absorption of a drug . drug to permeate cells and to be absorbed orally it should have psa not more than 140 a. likewise , absorption level 0 and 1 defined that the compounds had good and moderate absorption level , respectively , according to ro5 as given in table 1 . all the 41 analogs were subjected for toxicity ( mutagenicity and carcinogenicity ) analysis using discovery studio 3.5 . the mutagenic or carcinogenic analogs of sah were eliminated where only 26 compounds were found nonmutagenic and noncarcinogenic [ table 2 ] . carcinogen versus noncarcinogen , probability below 0.3 indicates that only 26 analogs were found a noncarcinogen , in male , as well as in female , according to the data made available by the fda . the negative effect of selected compounds on cyp2d6 was analyzed and found that none of selected 26 compounds may inhibit the cyp2d6 . hence , there may be no chances of drug - drug interaction as shown in table 2 . the bioisosteric analogs of group-2 ( 9h - purine ) substructure only showed better druglikeness profiles . inhibitor analogs of sah which could pass toxicity screening before docking all the selected druglike 26 analogs of sah and target protein , mtase were prepared using discover studio 3.2 . the binding site was defined by selecting the lead compound sah in light red color circle around the sah compound as shown in figure 1 . prepared compounds were docked with target protein using libdock module of discover studio 3.2 and hundreds of pose conformations were generated for each compound . lead compound sah found to have libdock score 124.5 and binding energy ( 142.4 kcl / mol ) which formed hydrogen bonds with two residues lys.181 and ser.150 as shown in figure 3 . the methyl donor substrate sam had libdock score 125.3 and binding energy ( 145.3 kcl / mol ) and formed a hydrogen bond with two residues gly.148 and arg.84 different than the sah within the same binding pocket as shown in figure 3 . interaction of ( a ) s - adenosyl - l - homocysteine ( libdock score - 124.5 ) and ( b ) s - adenosyl - l - methionine ( libdock score - 125.3 ) with the methyltransferase target protein . s - adenosyl - l - methionine and s - adenosyl - l - homocysteine in yellow color , interacting amino acids in element color , and hydrogen bonds in green color are shown hence , analogs with more libdock score than sah and sam toward target protein ( more than 126 ) and good binding energy was selected as better compound analogs . only 17 analogs [ table 3 ] were found to have better interaction affinity ( libdock score ) than endogenous ligands sah and sam and lower binding energy and were also interacted with the amino acid residues participated in interacting with sah and sam given in table 4 . structures of final 17 designed bioisosteric analogs of sah ligand interaction score and interacting residues of better scoring analogs of sah the compound analog 1 with ( 137.8 ) highest libdock score formed h - bond with amino acids residues lys.181 and arg.57 shown in figure 4 . the compound analog 15 scored ( 135.9 ) formed the hydrogen bond with ser.150 residue as shown in figure 5 and analog 17 scored ( 136.1 ) also found to interact with the amino acid residues lys.181 and arg.84 as shown in figure 6 . these most scoring three compound analogs ( analog 1 , analog 15 , and analog 17 ) and all other selected analogs scored better dock score at lower binding energy and formed the hydrogen bonds with the residues interacting with sah within the same binding pocket . computational analysis suggested that the designed compounds interacted in a similar manner of sah within the binding pocket of sah . the compounds attained similar binding orientation occupying the common amino acids within the binding site figure 7 . interaction of analog 1 most scoring analogs of s - adenosyl - l - homocysteine interacting residues information within the binding pocket of target protein ( element color - ligand ; dotted blue color line - hydrogen bond ) interaction of analog 15 most scoring analogs of s - adenosyl - l - homocysteine within the binding pocket of target protein and interacting amino acid residues ( element color - ligand ; dotted blue color line - hydrogen bond ) analog 17 of most scoring analogs of s - adenosyl - l - homocysteine with interacting residues within the binding pocket of target protein ( element color - ligand ; dotted blue color line - hydrogen bond ) superimposition of all 17 s - adenosyl - l - homocysteine ( yellow color ) designed analogs ( green color ) within the binding site ( pale red color ) of target protein out of analogs designed by bioisosteric replacement of three substructures of sah , group-2 ( 9h - purine ) substructure bioisosteric analogs of sah only showed better interaction affinity than lead sah toward dengue mtase , as well as druglikeness . the bioisosteric replacement of group-1 ( 2-amino-4-mercaptobutanoic acid ) , group-2 ( 9h - purine ) , and group-3 ( tetrahydrofuran-3,4-diol ) [ figure 2 ] generated 93 , 89 , and 132 new bioisosteric analogs of sah , respectively . all the designed analogs of sah were subjected for in - silico adme analysis using discover studio 3.5 . only 41 analogs could pass the admet filter ( lipinski rule of five ) and toxicity filters ( carcinogenicity , mutagenicity , cyp2d6 prediction , and toxicity ) . a drug should have to get dissolved , i.e. , the drug should be soluble because solubility plays a significant role in drug action . hence , solubility range should between the 8.0 ( extremely low solubility ) and 0.0 ( optimal solubility ) . levels defined for solubility signified that the compounds with solubility levels 3 and 4 have good and optimal solubility , respectively , therefore these analogs have solubility as per ro5 as tabulated in table 1 . inhibitor analogs with good admet properties absorption of the drug should also be good so that a large amount of drug can reach at the site of action . absorption of a compound depends mainly on alogp and polar surface area ( psa ) of that compound . alogp98 denoted lipophilicity ( alogp ) value of the compound where the value of it should be between the 2.0 and 5.0 for good intestinal absorption of a drug . drug to permeate cells and to be absorbed orally it should have psa not more than 140 a. likewise , absorption level 0 and 1 defined that the compounds had good and moderate absorption level , respectively , according to ro5 as given in table 1 . all the 41 analogs were subjected for toxicity ( mutagenicity and carcinogenicity ) analysis using discovery studio 3.5 . the mutagenic or carcinogenic analogs of sah were eliminated where only 26 compounds were found nonmutagenic and noncarcinogenic [ table 2 ] . carcinogen versus noncarcinogen , probability below 0.3 indicates that only 26 analogs were found a noncarcinogen , in male , as well as in female , according to the data made available by the fda . the negative effect of selected compounds on cyp2d6 was analyzed and found that none of selected 26 compounds may inhibit the cyp2d6 . hence , there may be no chances of drug - drug interaction as shown in table 2 . the bioisosteric analogs of group-2 ( 9h - purine ) substructure only showed better druglikeness profiles . before docking all the selected druglike 26 analogs of sah and target protein , mtase were prepared using discover studio 3.2 . the binding site was defined by selecting the lead compound sah in light red color circle around the sah compound as shown in figure 1 . prepared compounds were docked with target protein using libdock module of discover studio 3.2 and hundreds of pose conformations were generated for each compound . lead compound sah found to have libdock score 124.5 and binding energy ( 142.4 kcl / mol ) which formed hydrogen bonds with two residues lys.181 and ser.150 as shown in figure 3 . the methyl donor substrate sam had libdock score 125.3 and binding energy ( 145.3 kcl / mol ) and formed a hydrogen bond with two residues gly.148 and arg.84 different than the sah within the same binding pocket as shown in figure 3 . interaction of ( a ) s - adenosyl - l - homocysteine ( libdock score - 124.5 ) and ( b ) s - adenosyl - l - methionine ( libdock score - 125.3 ) with the methyltransferase target protein . s - adenosyl - l - methionine and s - adenosyl - l - homocysteine in yellow color , interacting amino acids in element color , and hydrogen bonds in green color are shown hence , analogs with more libdock score than sah and sam toward target protein ( more than 126 ) and good binding energy was selected as better compound analogs . only 17 analogs [ table 3 ] were found to have better interaction affinity ( libdock score ) than endogenous ligands sah and sam and lower binding energy and were also interacted with the amino acid residues participated in interacting with sah and sam given in table 4 . structures of final 17 designed bioisosteric analogs of sah ligand interaction score and interacting residues of better scoring analogs of sah the compound analog 1 with ( 137.8 ) highest libdock score formed h - bond with amino acids residues lys.181 and arg.57 shown in figure 4 . the compound analog 15 scored ( 135.9 ) formed the hydrogen bond with ser.150 residue as shown in figure 5 and analog 17 scored ( 136.1 ) also found to interact with the amino acid residues lys.181 and arg.84 as shown in figure 6 . these most scoring three compound analogs ( analog 1 , analog 15 , and analog 17 ) and all other selected analogs scored better dock score at lower binding energy and formed the hydrogen bonds with the residues interacting with sah within the same binding pocket . computational analysis suggested that the designed compounds interacted in a similar manner of sah within the binding pocket of sah . the compounds attained similar binding orientation occupying the common amino acids within the binding site figure 7 . interaction of analog 1 most scoring analogs of s - adenosyl - l - homocysteine interacting residues information within the binding pocket of target protein ( element color - ligand ; dotted blue color line - hydrogen bond ) interaction of analog 15 most scoring analogs of s - adenosyl - l - homocysteine within the binding pocket of target protein and interacting amino acid residues ( element color - ligand ; dotted blue color line - hydrogen bond ) analog 17 of most scoring analogs of s - adenosyl - l - homocysteine with interacting residues within the binding pocket of target protein ( element color - ligand ; dotted blue color line - hydrogen bond ) superimposition of all 17 s - adenosyl - l - homocysteine ( yellow color ) designed analogs ( green color ) within the binding site ( pale red color ) of target protein out of analogs designed by bioisosteric replacement of three substructures of sah , group-2 ( 9h - purine ) substructure bioisosteric analogs of sah only showed better interaction affinity than lead sah toward dengue mtase , as well as druglikeness . the drug discovery for dengue fever is the serious concern around the world in recent decades because there is no permanent good drug against dengue . mtase plays a crucial role in methylation and catalyzing the capping of viral rna , which is an important step for viral replication . out of the modified analogs of sah , 17 analogs were found to have a better affinity for mtase protein and admet property . seventeen compounds found nonmutagenic , as well as noncarcinogenic and had a good druglike profile . the dock score of all selected 17 inhibitor analogs of mtase found better than sah and even sam also . three analogs ( analog 1 , analog 15 , and analog 17 ) were found best scoring among all . compounds interacted in the pattern of sah and sam - forming hydrogen bond with lys.181 , ser.150 , and arg.84 amino acid residues found to interact with sam and sah . so the computational study suggested that the designed analogs may act as inhibitors of mtase protein and may lead to the better drug against dengue virus .
aim : aim of this work was to design and identify some s - adenosyl - l - homocysteine ( sah ) analogs as inhibitors of s - adenosyl - l - methionine - dependent methyltransferase ( mtase ) protein using computational approaches.introduction:according to the current scenario the dengue has been a global burden . 
 the people are being killed by dengue virus in an abundant number . despite of lot of research being going on dengue worldwide , there is no single drug which can kill its virus . 
 this creates an urge for new drug target identification and designing . 
 mtase has been reported as an effective target against dengue virus as it catalyzes an essential step in methylation and capping of viral rna for viral replication.materials and methods : the crystal structure of mtase in complex with sah was used for designing new analogs of sah . 
 sah analogs designed were analyzed on the basis of docking , admet , and toxicity analysis done using discovery studio 3.5.results:seventeen analogs found noncarcinogenic , nonmutagenic , as well as good admet properties and good drug - like profile.conclusion:these sah analogs , inhibitors of mtase may act as drugs against dengue virus . 
 further synthesis and biological testing against dengue virus is under observation .