Stars
Workflow for ranking dominant structural variants from molecular inputs.
Official implementation for LigUnity: Hierarchical affinity landscape navigation through learning a shared pocket-ligand space.
Official repo of "CarsiDock: a deep learning paradigm for accurate protein–ligand docking and screening based on large-scale pre-training" proposed by CarbonSilicon AI.
GPU-accelerated molecular docking software: Uni-Dock 2
Highly Precise Prediction of Micro- and Supra-pKa Based on 3D Descriptors Integrating Non-Covalent Interactions
Compilation of literature examples of generative drug design that demonstrate experimental validation
A Multi-Task Generative model for Structure-Based Drug Design
Refined and extended version of ChemTS
The graph-convolutional neural network for pka prediction
Utilities for working with high-performance computing (HPC) environments. The scripts help inspect PBS job efficiency and monitor CPU and memory usage on a running system or process tree.
Official repository for the Boltz biomolecular interaction models
Access to Biological Web Services from Python.
Fast and Accurate Prediction of Tautomer Ratios in Aqueous Solution via Siamese Neural Network
Automated Adaptive Absolute alchemical Free Energy calculator
DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules…
SurfDock is a Surface-Informed Diffusion Generative Model for Reliable and Accurate Protein-ligand Complex Prediction
Molecular multi-instance machine learning
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
hutchisonlab / QupKake
Forked from Shualdon/QupKakeMachine Learning model for molecular micro-pKa prediction
Module containing scripts to perform multiple comparison simultaneously and getting the exact same value as the average pairwise comparisons of molecules represented by binary fingerprints or real …
Adds or removes hydrogen atoms to achieve the appropriate molecular protonation state for a user-specified pH range
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.