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

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]

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

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

Structural Bioinformatics Training Workshop & Hackathon 2018

Code for our Nature Scientific Reports paper "A universal framework for accurate and efficient geometric deep learning of molecular systems"

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

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

DeltaVina scoring function

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

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

This repository contains the code for the work on protein-ligand interaction with GNNs and XAI

Methods for mapping genomic data onto 3D protein structure.

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