Differentiable, Hardware Accelerated, Molecular Dynamics
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Updated
Jul 26, 2026 - Jupyter Notebook
Differentiable, Hardware Accelerated, Molecular Dynamics
End-To-End Molecular Dynamics (MD) Engine using PyTorch
Some useful RDKit functions
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
Reaction fingerprints, atlases and classification. Code complementing our Nature Machine Intelligence publication on "Mapping the space of chemical reactions using attention-based neural networks" (http://rdcu.be/cenmd).
Molecular Processing Made Easy.
Source code for molecular graphics program UCSF ChimeraX
Knowledge-Guided Diffusion Model for 3D Ligand-Pharmacophore Mapping
A Pharmacophore MultiToolkit designed to simplify and streamline the detection, generation, analysis, comparison, and application of pharmacophore models in drug-design strategies.
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
Molsystem provides a general class for handling molecular and periodic systems
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
A comprehensive macromolecular library
The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io
Prediction of binding residues for metal ions, nucleic acids, and small molecules.
IF-SitePred is a method for predicting ligand-binding sites on protein structures. It first generates an embedding for each residue of the protein using the ESM-IF1 (inverse folding) model, then performs point cloud clustering to identify binding site centers.
NequIP is a code for building E(3)-equivariant interatomic potentials
A package to identify matched molecular pairs and use them to predict property changes.
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