Improved prediction of antibody and their complexes with clustered generative modelling ensembles.

ABSTRACT:

Motivation

Gaining structural insights into antibody-antigen complexes is crucial for understanding antigen recognition mechanisms and advancing therapeutic antibody design. However, accurate prediction of the structure of highly variable complementarity-determining region 3 on the antibody heavy chain (CDR-H3 loop) remains a significant challenge due to its increased length and conformational variability. While AlphaFold2-multimer (AF2) has made substantial progress in protein structure prediction, its application on antibodies and antibody-antigen complexes is limited by the weak evolutionary signals in the CDR region and the lack of structural diversity in its output.

Results

To address these limitations, we propose a workflow that combines AlphaFlow to generate ensembles

SUBMITTER: Xu X 

PROVIDER: S-EPMC12279294 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature