Modeling conformational states of proteins with AlphaFold.

Protein Conformation Proteins / chemistry
AlphaFold Conformational changes Conformational ensemble Protein structures

Journal

Current opinion in structural biology
ISSN: 1879-033X
Titre abrégé: Curr Opin Struct Biol
Pays: England
ID NLM: 9107784

Informations de publication

Date de publication:
08 2023
Historique:
received: 21 03 2023
revised: 16 05 2023
accepted: 01 06 2023
medline: 9 8 2023
pubmed: 2 7 2023
entrez: 1 7 2023
Statut: ppublish

Résumé

Many proteins exert their function by switching among different structures. Knowing the conformational ensembles affiliated with these states is critical to elucidate key mechanistic aspects that govern protein function. While experimental determination efforts are still bottlenecked by cost, time, and technical challenges, the machine-learning technology AlphaFold showed near experimental accuracy in predicting the three-dimensional structure of monomeric proteins. However, an AlphaFold ensemble of models usually represents a single conformational state with minimal structural heterogeneity. Consequently, several pipelines have been proposed to either expand the structural breadth of an ensemble or bias the prediction toward a desired conformational state. Here, we analyze how those pipelines work, what they can and cannot predict, and future directions.

Identifiants

DOI: 10.1016/j.sbi.2023.102645 PMID: 37392556
pubmed: 37392556
pii: S0959-440X(23)00119-7
doi: 10.1016/j.sbi.2023.102645
pii:
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

102645

Subventions

Organisme : NIDA NIH HHS
ID : R01 DA046138
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL122010
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM080403
Pays : United States

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

D Sala (D)

Institute of Drug Discovery, Faculty of Medicine, University of Leipzig, 04103 Leipzig, Germany. Electronic address: https://twitter.com/sala_davide.

F Engelberger (F)

Institute of Drug Discovery, Faculty of Medicine, University of Leipzig, 04103 Leipzig, Germany. Electronic address: https://twitter.com/fengel97.

H S Mchaourab (HS)

Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA. Electronic address: https://twitter.com/Mchaourablab.

J Meiler (J)

Institute of Drug Discovery, Faculty of Medicine, University of Leipzig, 04103 Leipzig, Germany; Center for Structural Biology, Vanderbilt University, Nashville, TN 37240, USA; Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Dresden/Leipzig, Germany. Electronic address: jens@meilerlab.org.

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Classifications MeSH

questionsmedicales.fr › Phénomènes chimiques › Phénomènes biochimiques › Conformation moléculaire › Conformation des protéines › Modeling conformational states of proteins...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Modeling conformational states of proteins...