Suhui Wang

TopoFlow generates protein conformational ensembles using evolutionary and structural information, improving benchmark metrics and aligning with experimental data.

ProSiteHunter improves protein binding site prediction by integrating sequence-based features and a fine-tuned language model, achieving better performance than existing methods.

SAMAffinity predicts mutation-induced changes in protein-protein binding affinity using a sequence-aware deep learning model, outperforming existing methods on multiple datasets.

DeepAAAssembly improves antibody-antigen complex modeling by integrating dynamic interactions, outperforming AlphaFold3 on a benchmark set.

MultiSAAI predicts antibody-antigen interactions using a multi-scale deep learning framework, achieving high AUROC scores on benchmark datasets.

DeepAssembly2 improves protein complex structure prediction using domain-domain interactions and integrates new features and models to enhance accuracy.

This paper introduces FoldPAthreader, a method predicting protein folding pathways using a novel force field derived from evolutionary data, achieving 70% accuracy on 30 targets.