Local conformations in ordered and Intrinsically disordered proteins

Protein structures are highly dynamic macromolecules. This dynamics is often analysed with a limited number of proteins. In our study, molecular dynamics (MDs) simulations were performed on a large set of 169 representative protein domains. To investigate protein flexibility, classical approaches such as RMSf or solvent accessibility were used, but also innovative approaches such as local entropy. At first, classical secondary structures were explored. Concerning the helical structures, only 76.4% of the residues associated to α-helices retain the conformation; this tendency drops to 40.5% for 310-helices and near zero for π-helices. However, this last impressive non-stability is entirely dependent on the assignment approach. Indeed, with the most recent DSSP version, these results are totally scrambled, the π–helices showed behaviours equivalent to 310-helix (Narwani et al, Arch Biol Sci, 2018). The rigidity of β-sheet was confirmed, but we also show its capacity to transform into turns. Finally, while the dynamics between turns (with hydrogen bond) and bends (without hydrogen bond) have some strong similarities, they also showed differences as turns convert easily to helical structures while bends prefer the extended conformations. Analyses were similarly performed using a structural alphabet, namely the Protein Blocks (PBs, de Brevern et al, Proteins, 2000). For half of the PBs, to be buried or exposed does not change at all its dynamics. The majority of PBs remain as their original conformation, or at least with a high frequency. Few PBs have a higher tendency to be more flexible. The intriguing fact is that the change from a PB to another one does not correspond to a simple geometrical evolution. It is more frequent to go to an unexpected PB than an expected one (Narwani et al, J Biomol Struct Dyn, 2019). To go further, a dataset of disorder protein ensembles was analysed with the PB. Using a PB derived entropy index, we quantify, for the first time, continuum from rigidity to flexibility and finally disorder. We also highlight non-disordered regions in the ensemble of disordered proteins (Melarkode Vattekatte et al, J Struct Biol, 2020, Melarkode Vattekatte et al, Data in Brief, 2020). These studies show the complex nature of protein dynamics and the value of their analysis at a local level. In addition, they show the possibility of performing these analyses on both ordered and disordered proteins. These results have been compared to different types of prediction. References: de Brevern Alexandre G., Etchebest Catherine, Hazout Serge, Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Proteins, 41(3):271-87, 2000. https://doi.org/10.1002/1097-0134(20001115)41:3<271::AID-PROT10>3.0.CO;2-Z. Melarkode Vattekatte Akhila, Narwani Tarun J., Floch Aline, Maljković Mirjana, Bisoo Soubika, Shinada Nicolas K., Kranjc Agata, Gelly Jean-Christophe, Srinivasan Narayanaswamy, Mitić Nenad, de Brevern Alexandre G., A structural entropy index to analyse local conformations in intrinsically disordered proteins. J Struct Biol, 2020:107464, 2020.https://doi.org/10.1016/j.jsb.2020.107464. Melarkode Vattekatte Akhila, Narwani Tarun J., Floch Aline, Maljković Mirjana, Bisoo Soubika, Shinada Nicolas K., Kranjc Agata, Gelly Jean-Christophe, Srinivasan Narayanaswamy, Mitić Nenad, de Brevern Alexandre G., Data set of Intrinsically Disordered Proteins analysed at a local protein conformation level. Data in Brief, 29:105383,2020.https://doi.org/10.1016/j.dib.2020.105383. Narwani Tarun J., Craveur Pierrick, Shinada Nicolas K., Santuz Hubert, Rebehmed Joseph, Etchebest Catherine, de Brevern Alexandre G., Dynamics and deformability of α-, 310- and π- helices. Archives of Biological Sciences, 70(1):21-31, 2018. https://doi.org/10.2298/ABS170215022N. Narwani Tarun J., Craveur Pierrick, Shinada Nicolas K., Floch Aline, Santuz Hubert, Melarkode Vattekatte Akhila, Srinivasan Narayanaswamy, Rebehmed Joseph, Gelly Jean-Christophe, Etchebest Catherine, de Brevern Alexandre G., Discrete analyses of protein dynamics. J Biomol Struct Dyn, 12:1-15, 2019. https://doi.org/10.1080/07391102.2019.1650112.