Pawan Neupane

This paper improves AlphaFold3 by using customized MSAs and templates, achieving higher accuracy in structure prediction for monomers, multimers, and protein-ligand complexes.

The paper improves AlphaFold2 and AlphaFold3 predictions using MSA engineering, extensive model sampling, and ensemble QA methods, achieving high accuracy in CASP16.

The paper improves protein complex structure prediction by integrating AlphaFold2 and 3 with enhanced methods in MULTICOM4, achieving high TM-scores and DockQ scores in CASP16.

The paper predicts protein complex stoichiometry by combining AlphaFold3 and template information, achieving high accuracy in CASP16.

GATE estimates protein complex model accuracy using graph transformers on pairwise similarity graphs, achieving high correlation and low ranking loss on CASP15 and CASP16 datasets.