Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Abseil Common Libraries (C++)

Awesome papers related to generative molecular modeling and design.

Artificial Intelligence Research for Science (AIRS)

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

A deep learning package for many-body potential energy representation and molecular dynamics

Accurate prediction of protein pKa with representation learning

An Industrial Grade Federated Learning Framework

Auto3D generates low-energy conformers from SMILES/SDF

Vina-GPU 2.1, an improved docking toolkit for faster speed and higher accuracy on the virtual screening

AIMNet-NSE model

Accurate Neural Network Potential on PyTorch

Interaction Fingerprints for protein-ligand complexes and more

EquiDock: geometric deep learning for fast rigid 3D protein-protein docking

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

Repository for MolFormer

[ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

G-SchNet - a generative model for 3d molecular structures

Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)

The code allows for the generation of a molecular representation for amines used in carbon capture, generation from molecular fragment combinations and analysis of the chemical space.

Molecular optimization by capturing chemist’s intuition using the Seq2Seq with attention and the Transformer

Pocket to Concavity is a tool for refinement of Protein-Ligand binding site shape from alpha-spheres

Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput large-batch generation.

A Python Package for Protein Dynamics Analysis

source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

This is BlueMatter, the molecular dynamics application which was used to exercise the BlueGene/L and BlueGene/P range of supercomputers. This code is written to the hardware interfaces on BlueGene/…