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Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformationa...

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Autores principales: Yu, Lei, Brüschweiler, Rafael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491582/
https://www.ncbi.nlm.nih.gov/pubmed/36084124
http://dx.doi.org/10.1371/journal.pcbi.1010036
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author Yu, Lei
Brüschweiler, Rafael
author_facet Yu, Lei
Brüschweiler, Rafael
author_sort Yu, Lei
collection PubMed
description Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including (15)N spin relaxation, without the need for reweighting. Further inspection revealed that 10–20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.
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spelling pubmed-94915822022-09-22 Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins Yu, Lei Brüschweiler, Rafael PLoS Comput Biol Research Article Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including (15)N spin relaxation, without the need for reweighting. Further inspection revealed that 10–20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function. Public Library of Science 2022-09-09 /pmc/articles/PMC9491582/ /pubmed/36084124 http://dx.doi.org/10.1371/journal.pcbi.1010036 Text en © 2022 Yu, Brüschweiler https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yu, Lei
Brüschweiler, Rafael
Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title_full Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title_fullStr Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title_full_unstemmed Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title_short Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
title_sort quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491582/
https://www.ncbi.nlm.nih.gov/pubmed/36084124
http://dx.doi.org/10.1371/journal.pcbi.1010036
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