Peng Tao

This paper introduces a transformer-based diffusion model that generates protein conformational ensembles efficiently, showing alignment with MD simulations and broader conformational coverage.

This study integrates molecular dynamics, mutational scanning, and network modeling to characterize KRAS-RAF1 binding hotspots, allostery, and conformational dynamics, revealing how oncogenic mutations alter binding affinity and signaling.

This study adapts AlphaFold2 to predict conformational ensembles of allosteric ABL kinase mutants, showing that sequence masking and subsampling improve prediction of structural state shifts caused by mutations.

This study uses AlphaFold2 and molecular dynamics to predict conformational ensembles and binding mechanisms of SARS-CoV-2 Omicron variants, showing agreement with experimental data.

This study uses molecular dynamics simulations and Markov state models to analyze mutation-induced allostery in AsLOV2, identifying key β-sheet interactions critical for signal transmission during photoactivation.

This study uses AlphaFold2 and molecular dynamics to analyze the structure, dynamics, and binding of SARS-CoV-2 Omicron BA.2.86 spike protein with ACE2 and antibodies, revealing key mutations that enhance immune evasion and ACE2 binding.

This study adapts AlphaFold2 to predict conformational ensembles and allosteric states of ABL kinase using sequence scanning and frustration profiling, revealing limitations in detecting low-populated inactive states.

This study uses AlphaFold2 and molecular simulations to analyze how mutations in SARS-CoV-2 Spike protein variants balance ACE2 binding and antibody resistance through epistatic interactions.

SSnet predicts protein-ligand interactions using secondary structure features, outperforming existing models and revealing key structural elements for ligand binding.