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

LINKER: Learning Interactions Between Functional Groups and Residues With Chemical Knowledge-Enhanced Reasoning and Explainability

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

Assignment for Kaggle competition "Predicting Protein-Ligand Interactions"

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.

🚀 Install the Affinity Universal app on Linux effortlessly with Affinity CLI, while easily managing Wine environments and installation profiles.