Python Molecular-docking Resources

Molecular Docking integrated in Jupyter Notebooks Description | Citation | Installation | Examples | Limitations | License Table of content Descriptio

GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome

Molecular Nodes 🧬 🔬 💻 Buy Me a Coffee to Keep Development Going! Join a Community of Blender SciVis People! What is Molecular Nodes? Molecular Node

TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular

Direct Molecular Conformation Generation This repository contains the code for Direct Molecular Conformation Generation (DMCG). Dataset Download rdkit

Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022) Please cite "Independent SE(3)-Equivar

chem: collection of mostly python code for molecular visualization, QM/MM, FEP,

A simple yet versatile toolkit to setup quantum mechanical/molecular mechanical (QM/MM) calculations from molecular dynamics trajectories.

Boltzmann visualization - Visualize the Boltzmann distribution for simple quantum models of molecular motion

TUPÃ: Electric field analyses for molecular simulations What is TUPÃ? TUPÃ (pronounced as tu-pan) is a python algorithm that employs MDAnalysis engine

Riemannian Geometry for Molecular Surface Approximation (RGMolSA) Introduction Ligand-based virtual screening aims to reduce the cost and duration of

pymbar Python implementation of the multistate Bennett acceptance ratio (MBAR) method for estimating expectations and free energy differences from equ

unit-converter-albert-ext Extension for converting units of length, mass, speed, temperature, time, current, luminosity, printing measurements, molecu

pyscreener A pythonic interface to high-throughput virtual screening software Overview This repository contains the source of pyscreener, both a libra

HyFactor Graph-based architectures are becoming increasingly popular as a tool for structure generation. Here, we introduce a novel open-source archit

MDAnalysis Repository README [*] MDAnalysis is a Python library for the analysis of computer simulations of many-body systems at the molecular scale,

GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles This repository contains a method to generate 3D conformer ensembles direct

LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and

Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi

Ultra-Fast Force Fields (UF3) S. R. Xie, M. Rupp, and R. G. Hennig, "Ultra-fast interpretable machine-learning potentials", preprint arXiv:2110.00624

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Code for the Multiplex Molecular Graph Neural Network (M

Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi

ReacNetGenerator An automatic reaction network generator for reactive molecular dynamics simulation. ReacNetGenerator: an automatic reaction network g

MoT - Molecular Transformer Large-scale Pretraining for Molecular Property Prediction Samsung AI Challenge for Scientific Discovery This repository is

Description Small wrapper around 3dmol.js and html2canvas for creating self-contained HTML files that display a 3D molecular representation. Double cl

Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

High Performance Molecular Dynamics Logging into CINECA's computer systems To logon to the M100 system use the following command from an SSH client ss

freud Overview The freud Python library provides a simple, flexible, powerful set of tools for analyzing trajectories obtained from molecular dynamics

This package is a python library with tools for the Molecular Simulation - Software Gromos. It allows you to easily set up, manage and analyze simulations in python.

README: GromacsWrapper A primitive Python wrapper around the Gromacs tools. The library is tested with GROMACS 4.6.5, 2018.x, 2019.x, 2020.x, and 2021

Molecular Orbital Transitions (MOT) Animate molecular orbital transitions using Psi4 and Blender Author: Maximilian Paradiz Dominguez, University of A

Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery

Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations This directory contains the model architectures and experimental

Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

3D-Transformer: Molecular Representation with Transformer in 3D Space

Automatic Differentiation Multipole Moment Molecular Forcefield Performance notes On a single gpu, using waterbox_31ang.pdb example from MPIDplugin wh

MolEncoder Molecular AutoEncoder in PyTorch Install $ git clone https://github.com/cxhernandez/molencoder.git && cd molencoder $ python setup.py insta

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

Part of the 9th place solution for the Bristol-Myers Squibb – Molecular Translation challenge translating images containing chemical structures into I

[PDF] | [Slides] The official implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021 Long talk) Installation Inst

MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p

The MDAkit for membrane curvature analysis is part of the Google Summer of Code program and it is linked to a Code of Conduct.

BMS-Molecular-Translation Introduction This is a pipeline for Bristol-Myers Squibb – Molecular Translation by Vadim Timakin and Maksim Zhdanov. We got

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.