We also constructed Cα -Cα contact-maps and secondary-structure analysis for clusters 1, 2 and 3 of all simulations (Fig. ). For CHARMM36m BEMD, the concurring Asn14-Ala24 and Ser16-Lys22 contacts, which have been proven to be highly associated with the β-strands observed along Asn14-to-Asn26, emerge primarily b). Thus, it is possible that the observed discrepancy can be due to the fact that both αcontent (α-content) and β-content (β-content) were used as collective variables in BEMD, while the bias potential of PTMetaD-WTE (a function of Cα -Cα and Cγ -Cγ contacts) can only implicitly explore along the two secondary-structure reaction coordinates. Nevertheless, the difference may be relatively trivial in presence of the dominating disordered nature of DHH1N -over 70 % of the total population is contained in the low β-content (β-content ≤ 4) region for both CHARMM36m BEMD and PTWTE. Furthermore, all simulations provide a similar insight into a possible nucleation pathway for the partially disordered regions of DHH1N (schematically represented by the green dashed lines in Fig. ). While the 2D-FES cannot reveal an accurate multi-dimensional pathway for the full conformational transition kinetics 109 , which could be a common challenge for representing protein free energies in lowdimensional space of popular CVs with physical meanings, our evidence indicates the dynamic disorder à a transition in the local domains of Asp18-to-Asn26 and Thr36to-Thr42 is likely to occur within a relatively compact DHH1N (Rg ~ 1.5 nm) with moderate sphericity (Fig. , Supplementary Note 5, Figs. and). Nevertheless, the high conformational heterogeneity of IDPs means that the exact locations and energies of the metastable states and barriers would require a more accurate free energy representation of reduced dimensionality. As a result of the designs and advantages of various protein force-fields and sampling methods, different portions of high-dimensional phase space may be preferably explored within simulation time, despite the high possibility that all results should converge in the long-time limit. Relying on the results from a single forcefield/sampling method simulation may restrain our understanding of the protein. For example, the temperature-dependence of certain protein properties can be easily recovered by analysing the sampling obtained from PTMetaD-WTE, which can provide key structure-property information to help understanding protein structures at different temperatures 110 ; on the other hand, BEMD simulations explore more collective variables and possibly higher portions of phase space within limited time, which can be preferred if certain metastable states can be better explored along certain CV directions.