List of Molecular and Material design using Generative AI and Deep Learning
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Updated
Nov 27, 2024
List of Molecular and Material design using Generative AI and Deep Learning
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Molecular Processing Made Easy.
Interaction Fingerprints for protein-ligand complexes and more
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.
DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
Official code repository of CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
Interface for AutoDock, molecule parameterization
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
A python package for exploring end-to-end chemistry workflows on quantum computers and simulators.
Python for chemoinformatics
DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins
benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.
We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)
Awesome De novo drugs design papers
Pose checks for 3D Structure-based Drug Design methods
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