Ruibin-Liu
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DFMDock (Denoising Force Matching Dock), a diffusion model that unifies sampling and ranking within a single framework.
A tutorials suite for BioSimSpace.
Robust Molecular Structure Recognition with Image-to-Graph Generation
Transmits AM radio on computers without radio transmitting hardware.
Notebooks demonstrating how to do simple tasks related to free energy calculations.
A python script for PyMol to make protein-ligand interaction images.
toolkit for prediction pKa values of small molecules via graph convolutional networks
QSARtuna: QSAR model building with the optuna framework
De Novo Drug Design with RNNs and Transformers
💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)
Implementation of Lilly Medchem Rules - J Med Chem 2012
The Open Source Code for LLM4SD (Large Language Models for Scientific Synthesis, Inference and Explanation)
BARTSmiles, generative masked language model for molecular representations
PSICHIC (pronounced Psychic) - PhySIcoCHemICal graph neural network for learning protein-ligand interaction fingerprints from sequence data
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Baselines models for GuacaMol benchmarks
Implementation of the method proposed in the paper "Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space" by Robin Winter, Floriane Montanari, Andreas Steffen, Hans Briem, …
Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows
Deep generative models of 3D grids for structure-based drug discovery
Python 3 fork for the preparation scripts contained in AutoDockTools
Implementation of ICML23 paper "Learning Subpocket Prototypes for Generalizable Structure-based Drug Design"
Implementation of Nvidia's NeuralPlexer, for end-to-end differentiable design of functional small-molecules and ligand-binding proteins, in Pytorch
Implementation of ICLR23 paper "Molecule Generation for Target Protein Binding with Structural Motifs"
P2Rank: Protein-ligand binding site prediction tool based on machine learning. Stand-alone command line program / Java library for predicting ligand binding pockets from protein structure.