#6 · Structural bio & protein design
Free energy and coarse-grained physics methods for biomolecular binding and interfaces
The common thread is the use of explicit physical energy functions or molecular dynamics sampling to evaluate binding and structural properties. Four relative binding free energy engines are benchmarked head-to-head on shared Amber force fields, while absolute binding FEP is used to classify integrin ligands by the conformation they stabilize, and FEP with coupling and conformational corrections predicts Fc-FcRn binding energy changes for antibody variants. Coarse-grained energetics enter the workflow in two places: MARTINI2 is implemented in HADDOCK3 for faster protein-protein sampling and scoring, and Martini Mapper automates Martini 3 models from SMILES across 1075 molecules. MD-derived analyses appear in PP-MAPS, which aggregates pharmacophore interactions from protein-peptide trajectories, and AlphaUnfold, which applies short high-pressure NAMD3 runs to AlphaFold3 models to flag fragile regions. FMOPhore pairs fragment molecular orbital calculations with pharmacophore models to classify hotspot residues. Novelty lies mainly in head-to-head benchmarking and in carrying coarse-grained and MD-derived energetics into docking and interface analysis.
Published papers
SARS-CoV-2 intra-host recombination promotes epistatic spike interactions and temperature-dependent adaptation.
Prolonged infections in immunocompromized individuals are associated with accumulation of unexpected combinations of mutations, as exemplified by the Omicron va
SARS-CoV-2 Spike Protein's Structural Dynamics Affect the Activity of the Bebtelovimab Antibody.
Molecular modeling and dynamics of SARS-CoV-2 spike mutants with ACE2 and bebtelovimab, predicting how mutations alter antibody binding affinity and activity.
Utilizing virus genomic surveillance to predict vaccine effectiveness.
Bayesian model links spike amino acid distance to time-varying SARS-CoV-2 vaccine effectiveness for sequence-based protection prediction.
Preprints
Epistatic evolution drives HLA-dependent CD8+ T Cell escape risk in diverse populations
Understanding how viral evolution shapes HLA-dependent T cell escape is crucial to identify individuals at risk of reduced cellular immunity to emerging variant
Interpreting the WaveSeekerNet model to reveal the evolution and biology of influenza A virus
WaveSeekerNet, a calibrated ML model over all 8 influenza A segments, predicts host source (macro F1 0.9728) and links G/C vs A/T codon usage to avian vs…
An Integrated Computational Approach to Predict and Characterize Emerging Mutations in the Japanese Encephalitis Virus Envelope Protein
Japanese encephalitis virus (JEV) causes significant encephalitis across the Asia-Pacific region.
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