Unbiased MD simulations identify lipid binding sites in lipid transfer proteins

Author:

Srinivasan Sriraksha1ORCID,Álvarez Daniel12ORCID,John Peter Arun T.1ORCID,Vanni Stefano13ORCID

Affiliation:

1. University of Fribourg 1 Department of Biology, , Fribourg, Switzerland

2. Universidad de Oviedo 2 Departamento de Química Física y Analítica, , Oviedo, España

3. Swiss National Center for Competence in Research Bio-inspired Materials, University of Fribourg 3 , Fribourg, Switzerland

Abstract

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.

Funder

Swiss National Science Foundation

Swiss National Supercomputing Centre

European Research Council

European Union’s Horizon 2020

Ministerio de Universidades

Novartis Forschungsstiftung

Publisher

Rockefeller University Press

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