P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.

Source code for "DeepDTA: deep drug-target binding affinity prediction"

PLACER is graph neural network for local prediction of protein-ligand conformational ensembles.

PocketGen (Nature Machine Intelligence 24): Generating Full-Atom Ligand-Binding Protein Pockets

PSICHIC (pronounced Psychic) - PhySIcoCHemICal graph neural network for learning protein-ligand interaction fingerprints from sequence data

RxDock is a fork of rDock. Note: the latest code is under development. Please do git checkout patched-rdock after clone if you want patched rDock. [IMPORTANT NOTE: pull requests should be posted on GitLab, this is a read-only source code mirror]

Implementation of ICLR23 paper "Molecule Generation for Target Protein Binding with Structural Motifs"

Source code for "A universal framework for accurate and efficient geometric deep learning of molecular systems" (Nature Scientific Reports)

GPU-accelerated protein-ligand docking with automated pocket detection, exploring through multi-pocket conditioning. Official Implementation of PocketVina

Methods for the parallel and distributed analysis and mining of the Protein Data Bank using MMTF and Apache Spark.

Structural Bioinformatics Training Workshop & Hackathon 2018

All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.

Implementation of Nvidia's NeuralPlexer, for end-to-end differentiable design of functional small-molecules and ligand-binding proteins, in Pytorch

Contact map analysis for biomolecules; based on MDTraj

DeltaVina scoring function

Protein target prediction using random forests and reliability-density neighbourhood analysis

[EMNLP 2025]* FusionDTI utilises a Token-level Fusion module to effectively learn fine-grained information for Drug-Target Interaction Prediction.

Comparison of active site and full kinase sequences for drug-target affinity prediction and molecular generation. Full paper: https://pubs.acs.org/doi/10.1021/acs.jcim.1c00889

[ICML 2024] Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation