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

We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.

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]

GaudiMM: A modular optimization platform for molecular design

Implementation of the Confidence Bootstrapping procedure for protein-ligand docking.

Colab version of "DiffDock: : Diffusion Steps, Twists, and Turns for Molecular Docking"

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

A novel approach to pose selection in protein-ligand docking based on graph theory.

Flexible Artificial Intelligence Docking

LigTMap currently supports prediction for 17 protein target classes that include 6000+ protein targets.

A python script for PyMol to make protein-ligand interaction images.

A toolkit for predicting the binding mode of small molecules interacting with proteins based on interfacial rigidification, as assessed by graph theoretic constraint counting on the covalent and noncovalent bond network. Raschka et al. (2016) Proteins: Structure, Function, and Bioinformatics

Root-mean-square deviation of atomic positions

Protein Recognition Index (PRI), measuring the similarity between H-bonding features in a given complex (predicted or designed) and the characteristic H-bond trends from crystallographic complexes

Repository for the Taba tool

PIAWeb - a graphical web interface for PIA

Analysis on the number of non-hydrogen atomic contacts between a ligand and each of specified residues on the protein following molecular docking of multiple ligands to a protein structure.

The NRGsuite is a PyMOL plugin (GUI) for FlexAID

NRGsuite is a PyMOL plugin (GUI) for FlexAID

Automatic identification of important interactions and interaction-frequency-based scoring in protein-ligand complexes