OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
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Updated
Nov 26, 2023 - Python
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
A Euclidean diffusion model for structure-based drug design.
Protwis is the backbone of the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).
Interaction Fingerprints for protein-ligand complexes and more
Molecular Processing Made Easy.
DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
Official code repository of CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Code and data for "NeVAE: A Deep Generative Model for Molecular Graphs", AAAI 2019
Pytorch implementation of BionoiNet, which is a deep learning-based software to classify ligand-binding sites.
This repository is the official code source of PPFlow: Target-Aware Peptide Design with Torsional Flow Matching (ICML2024)
DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins
An integrated negative design python library for desirable HTS/VS database design
Structure-based Drug Design; Reinforcement Learning and Genetic Algorithm
Computational Analysis of Novel Drug Opportunities
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 number descriptors.
This pipeline is executing a RE-EDS run for relative free energy calculations. It can be used for example for calculation of hydration free energies or ligand binding free energies.
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