Gabriele Pozzati

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.

AlphaFold2, fed concatenated chains with optimized organism-paired alignments and pDockQ-ranked seeds, gives acceptable models for 63% of heterodimers; the same predicted DockQ score flags interacting pairs.

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.