Software
Geometric Graph Learning for Protein–Protein Interactions (GGL-PPI) integrates geometric graph representation and machine learning to forecast mutation-induced binding free energy changes.
Geometric Graph Learning for Protein–Protein Interactions (GGL-PPI) integrates geometric graph representation and machine learning to forecast mutation-induced binding free energy changes.
A multiscale geometric graph-learning scoring function that uses extended atom-type features to model protein–ligand interactions and predict binding affinities with high accuracy.
Algebraic surface–area–based scoring method that quantifies element-specific protein–ligand interactions for accurate binding affinity prediction and ranking.
Online server for algebraic graph theory based protein-ligand binding scoring, ranking, docking and screening.
Online server for differential geometry based geometric data analysis of molecular datasets.
Online server for geometric graph theory or rigidity index (RI) based scoring function for protein ligand binding affinity prediction.
Online server for the flexibility analysis of biomolecules based on flexibility and rigidity index.