← Back
Publicaciones

Identifying and Characterizing Lipid-Binding Cavities in Lipid Transfer Proteins With CG-MD Simulations

Authors

ALVAREZ LORENZO, DANIEL, Vanni, Stefano , Srinivasan, Sriraksha

External publication

No

Means

Bio-protocol

Scope

Article

Nature

Científica

JCR Quartile

SJR Quartile

Publication date

20/12/2025

ISI

001652073100008

Abstract

Understanding how lipids interact with lipid transfer proteins (LTPs) is essential for uncovering their molecular mechanisms. Yet, many available LTP structures, particularly those thought to function as membrane bridges, lack detailed information on where their native lipid ligands are located. Computational strategies, such as docking or AI-methods, offer a valuable alternative to overcome this gap, but their effectiveness is often restricted by the inherent flexibility of lipid molecules and the lack of large training sets with structures of proteins bound to lipids. To tackle this issue, we introduce a reproducible computational pipeline that uses unbiased coarse-grained molecular dynamics (CG-MD) simulations on a free and opensource software (GROMACS) with the Martini 3 force-field. Starting from a configuration of a lipid in bulk solvent, we run CG-MD simulations and observe spontaneous binding of the lipid to the protein. We show that this protocol reliably identifies lipid-binding pockets in LTPs and, unlike docking methods, suggests potential entry routes for lipid molecules with no a priori knowledge other than the protein's structure. We demonstrate the utility of this approach in investigating bridge LTPs whose internal lipid-binding positions remain unresolved. Altogether, our study provides a cost-effective, efficient, and accurate framework for mapping binding sites and entry pathways in diverse LTPs.

Keywords

Coarse-grain MD simulations; Martini 3 force-field; lipid transfer proteins (LTPs); BLTPs; GROMACS; Lipid binding

Universidad Loyola members