Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
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Updated
Mar 27, 2025 - Mathematica
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
GPU-accelerated protein-ligand docking with automated pocket detection, exploring through multi-pocket conditioning. Official Implementation of PocketVina
[ICML 2024] Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
Binding affinity prediction for drug discovery
ENS-Score is machine learning-based scoring function, which applies a probabilistic approach to estimate protein-ligand binding affinity.
R shiny app to analyse microscale thermophoresis (MST) data
Deep-ProLiPrint: A cutting-edge deep learning framework that generates compact, information-rich fingerprints from protein-ligand complexes, augmenting machine learning-driven drug discovery and molecular design.
A graphical user interface (GUI) and web application to facilitate the usage of ENS-Score.
Ranking of all the ligands in molecular docking by their AutoDock Vina scores, an approximation to their free energy of binding to the protein.
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