MPBind: a multitask protein binding site predictor using protein language models and equivariant GNNs.

ABSTRACT:

Motivation

Proteins interact with a variety of molecules, including other proteins, DNAs, RNAs, ligands, ions, and lipids. These interactions play a crucial role in cellular communication, metabolic regulation, gene regulation, and structural integrity, making proteins fundamental to nearly all biological functions. Accurately predicting protein interaction (binding) sites is essential for understanding protein interaction and function.

Results

In this work, we introduce MPBind, a multitask protein binding site prediction method, which integrates protein language models (PLMs) that can extract structural and functional information from sequences and equivariant graph neural networks (EGNNs) that can effectively capture geometric features of 3D protein structures. Through mul

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12631785 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature