Unbiased MD simulations identify lipid binding sites in lipid transfer proteins.


Journal

The Journal of cell biology
ISSN: 1540-8140
Titre abrégé: J Cell Biol
Pays: United States
ID NLM: 0375356

Informations de publication

Date de publication:
04 Nov 2024
Historique:
received: 13 12 2023
revised: 29 05 2024
accepted: 16 07 2024
medline: 6 8 2024
pubmed: 6 8 2024
entrez: 6 8 2024
Statut: ppublish

Résumé

The characterization of lipid binding to lipid transfer proteins (LTPs) is fundamental to understand their molecular mechanism. However, several structures of LTPs, and notably those proposed to act as bridges between membranes, do not provide the precise location of their endogenous lipid ligands. To address this limitation, computational approaches are a powerful alternative methodology, but they are often limited by the high flexibility of lipid substrates. Here, we develop a protocol based on unbiased coarse-grain molecular dynamics simulations in which lipids placed away from the protein can spontaneously bind to LTPs. This approach accurately determines binding pockets in LTPs and provides a working hypothesis for the lipid entry pathway. We apply this approach to characterize lipid binding to bridge LTPs of the Vps13-Atg2 family, for which the lipid localization inside the protein is currently unknown. Overall, our work paves the way to determine binding pockets and entry pathways for several LTPs in an inexpensive, fast, and accurate manner.

Identifiants

pubmed: 39105757
pii: 276888
doi: 10.1083/jcb.202312055
pii:
doi:

Substances chimiques

Carrier Proteins 0
lipid transfer protein 0
Saccharomyces cerevisiae Proteins 0
Lipids 0
Autophagy-Related Proteins 0
Vesicular Transport Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Swiss National Science Foundation
ID : PP00P3_194807
Pays : Switzerland
Organisme : Swiss National Supercomputing Centre
ID : s1030
Organisme : European Research Council
Pays : International
Organisme : European Union's Horizon 2020
ID : 803952
Organisme : Ministerio de Universidades
ID : MU-21-UP2021-030-53773022
Organisme : Novartis Forschungsstiftung

Informations de copyright

© 2024 Srinivasan et al.

Auteurs

Sriraksha Srinivasan (S)

Department of Biology, University of Fribourg, Fribourg, Switzerland.

Daniel Álvarez (D)

Department of Biology, University of Fribourg, Fribourg, Switzerland.
Departamento de Química Física y Analítica, Universidad de Oviedo, Oviedo, España.

Arun T John Peter (AT)

Department of Biology, University of Fribourg, Fribourg, Switzerland.

Stefano Vanni (S)

Department of Biology, University of Fribourg, Fribourg, Switzerland.
Swiss National Center for Competence in Research Bio-inspired Materials, University of Fribourg , Fribourg, Switzerland.

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Classifications MeSH