/tools
browse indexed tools
openmmforcefields
openmm/openmmforcefields
The openmmforcefields repository offers CHARMM and AMBER force fields for use with OpenMM, enabling the parameterization of biomolecular systems and small molecules. It supports various force fields and provides tools for generating parameters for small molecules, making it a valuable resource for molecular simulations.
exmol
ur-whitelab/exmol
The `exmol` package is designed to explain black-box predictions of molecular properties using model agnostic methods. It includes functionalities for generating counterfactuals and descriptor attributions, helping users understand the influence of molecular structures on predicted properties.
ChemDataExtractor
mcs07/ChemDataExtractor
ChemDataExtractor is a toolkit designed to automatically extract chemical information from scientific documents. It utilizes natural language processing techniques to identify and parse chemical entities and data from various document formats.
packmol
m3g/packmol
Packmol is a tool that generates initial configurations for molecular dynamics simulations by packing molecules in defined regions of space. It ensures that short-range repulsive interactions do not disrupt the simulations, making it suitable for various types of molecular systems.
examples
Allen-Tildesley/examples
This repository contains Fortran and Python examples for molecular dynamics and Monte Carlo simulations, designed to accompany the book 'Computer Simulation of Liquids'. It serves as a practical resource for understanding and implementing these simulation techniques in computational chemistry.
PyEMMA
markovmodel/PyEMMA
PyEMMA is an open-source Python package that provides algorithms for the estimation, validation, and analysis of Markov models in the context of molecular dynamics simulations. It supports clustering, featurization, and various Markov modeling techniques, making it useful for researchers in computational chemistry.
REINVENT
MarcusOlivecrona/REINVENT
REINVENT is a tool for molecular de novo design that employs recurrent neural networks and reinforcement learning techniques. It allows users to explore chemical space and generate novel molecular structures based on learned representations.
pypdb
williamgilpin/pypdb
PyPDB is a Python toolkit designed for performing searches and fetching data from the RCSB Protein Data Bank (PDB). It allows users to access information about protein structures, sequences, and related data programmatically, facilitating research in molecular biology.
Meeko
forlilab/Meeko
Meeko is an interface for AutoDock that prepares input files for molecular docking and processes the output. It parameterizes both small organic molecules and biological macromolecules, facilitating drug discovery and molecular modeling.
protein_generator
RosettaCommons/protein_generator
ProteinGenerator is a tool that generates sequence-structure pairs using a diffusion model based on RoseTTAFold. It allows users to explore and create new protein sequences conditioned on structural motifs, facilitating advancements in protein design.
rgn
aqlaboratory/rgn
The 'rgn' repository provides a TensorFlow implementation of recurrent geometric networks for end-to-end differentiable learning of protein structures. It allows users to train models and predict protein structures from sequences, making it a valuable tool in the field of molecular biology and computational chemistry.
se3-transformer-pytorch
lucidrains/se3-transformer-pytorch
The SE3-Transformer-PyTorch repository provides an implementation of SE3-Transformers for equivariant self-attention, specifically aimed at applications in protein structure prediction and drug discovery. It allows for the modeling of molecular interactions and features, making it a valuable tool in computational chemistry and molecular biology.
scikit-fingerprints
scikit-fingerprints/scikit-fingerprints
Scikit-fingerprints is a Python library designed for efficient computation of molecular fingerprints, which are crucial in drug discovery and chemical analysis. It provides a scikit-learn compatible interface, allowing users to integrate molecular fingerprints into machine learning workflows and access popular benchmark datasets.
CBGBench
EDAPINENUT/CBGBench
CBGBench is a benchmark tool for generative target-aware molecule design, integrating multiple state-of-the-art methods for generating molecules. It supports tasks such as linker design, fragment growing, and scaffold hopping, making it a valuable resource for researchers in drug discovery.
equiformer_v2
atomicarchitects/equiformer_v2
EquiformerV2 is a PyTorch implementation of an improved equivariant transformer designed for scaling to higher-degree representations in molecular systems. It is utilized for training on datasets related to energy and force predictions, making it a valuable tool in drug discovery and molecular dynamics simulations.
viamd
scanberg/viamd
VIAMD is an interactive analysis tool designed for molecular dynamics simulations. It allows users to perform operations on trajectory frames and visualize the results, making it a valuable resource for researchers in computational chemistry.
freud
glotzerlab/freud
freud is a Python library that provides powerful tools for analyzing particle trajectories from molecular dynamics and Monte Carlo simulations. It includes features for computing various analysis metrics such as radial distribution functions and potentials of mean force, facilitating research in materials science and computational chemistry.
MolCLR
yuyangw/MolCLR
MolCLR is an implementation of a contrastive learning framework for molecular representation learning using graph neural networks. It enhances the performance of models on various molecular property prediction tasks and provides datasets for pre-training and fine-tuning.
GearNet
DeepGraphLearning/GearNet
GearNet is a geometry-aware relational graph neural network designed for protein structure representation learning. It employs various self-supervised learning methods to enhance the encoding of protein spatial information, making it suitable for downstream tasks in molecular biology.
gReLU
Genentech/gReLU
gReLU is a Python library designed for training, interpreting, and applying deep learning models to DNA sequences. It provides functionalities for genome annotation and processing, making it a useful tool in the field of molecular biology.
openmmtools
choderalab/openmmtools
OpenMMTools is a Python library that enhances the OpenMM molecular simulation engine by providing tools for various molecular dynamics tasks, including free energy calculations and Markov chain Monte Carlo methods. It is designed to facilitate the development of comprehensive molecular simulation packages.
moltemplate
jewettaij/moltemplate
Moltemplate is a cross-platform text-based molecule builder that prepares simulations for LAMMPS, supporting both coarse-grained and all-atom models. It facilitates the creation of molecular models using various force fields and integrates with other molecular modeling tools.
torch-molecule
liugangcode/torch-molecule
torch-molecule is a deep learning package designed for molecular discovery, featuring an sklearn-style interface for property prediction, inverse design, and representation learning. It supports various molecular tasks and includes datasets for training models on molecular properties.
provis
salesforce/provis
This repository provides an implementation for visualizing and analyzing attention in protein language models, specifically designed to interpret how these models interact with protein structures. It includes tools for generating visualizations and conducting attention analysis on various protein datasets.