MSA clustering enhances AF-Multimer's ability to predict conformational landscapes of protein-protein interactions.

ABSTRACT:

Motivation

Understanding the conformational landscape of protein-ligand interactions is critical for elucidating the binding mechanisms that govern these interactions. Traditional methods like molecular dynamics (MD) simulations are computationally intensive, leading to a demand for more efficient approaches. This study explores how multiple sequence alignment (MSA) clustering enhance AF-Multimer's ability to predict conformational landscapes, particularly for proteins with multiple conformational states.

Results

We verified this approach by predicting the conformational landscapes of chemokine receptor 4 (CXCR4) and glucagon receptor (GCGR) in the presence of their agonists and antagonists. In our experiments, AF-Multimer predicted the structures of CXCR4 and GCGR predomina

SUBMITTER: Rustamov KR 

PROVIDER: S-EPMC11671036 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature