Petras J. Kundrotas

The paper introduces a docking-based simulation method that combines rigid-body approximations with flexible protein structures to model macromolecular interactions in crowded cellular environments over long timescales.

The paper evaluates AlphaFold-Multimer's performance on multi-chain protein complexes and introduces a new interface quality score.

The paper uses AlphaFold2 to predict structures for 65,484 human protein interactions, identifying high confidence models and disease-related mutations.

The paper predicts structures of large protein complexes using AlphaFold and Monte Carlo tree search, achieving accurate assemblies for some symmetric complexes.

The paper introduces a new dataset of 456 non-redundant alpha helical membrane protein-protein complexes for benchmarking docking methods.

The paper introduces two protein-protein docking scoring benchmarks designed to improve the evaluation of scoring functions in docking applications.

This paper introduces PconsDock, a fold-and-dock method that predicts tertiary and quaternary structures of protein pairs without prior structural information, achieving comparable performance to traditional methods.

This paper improves protein docking by using predicted interface residues to score docking models, finding that BIPSPI outperforms existing methods.