/tools

DisCo-DiffDock is a tool designed for molecular docking experiments, enhancing continuous diffusion models with discrete latents. It provides code and methods for evaluating molecular interactions, specifically targeting protein complexes.

Uni-pKa is a machine learning-based tool designed for accurate pKa prediction of small molecules. It includes a microstate enumerator for building protonation ensembles and a model that integrates thermodynamic principles to enhance prediction accuracy.

DrugGEN is a generative system designed for the de novo creation of drug candidate molecules that are tailored to interact with specific protein targets. It utilizes graph transformer-based generative adversarial networks to generate and evaluate potential drug candidates.

mdapy is a Python library designed for the analysis of molecular dynamics simulation data. It offers a suite of tools for processing atomic trajectories and performing structural analysis, making it a valuable resource for researchers in computational chemistry and materials science.

Pyscreener is a Python library designed for conducting high-throughput virtual screening (HTVS) of ligands against molecular targets. It supports various docking software and allows users to efficiently evaluate ligand-receptor interactions through a streamlined interface.

LiteFold is a tool designed to make protein structure prediction more accessible by providing a lightweight server that runs state-of-the-art folding models. It allows researchers to submit prediction jobs and retrieve results easily, bridging the gap between complex computational tools and the scientific community.

DuIvyTools is a Python library that facilitates the analysis and visualization of molecular dynamics simulation results from GROMACS. It offers various commands for processing data files, making it a useful tool for researchers in computational chemistry.

MolEncoder is a Molecular AutoEncoder implemented in PyTorch that allows users to train models on molecular datasets, specifically designed for tasks such as molecular representation and generation. It includes functionalities for downloading datasets and training models, making it a useful tool in computational chemistry and molecular biology.

This repository provides educational materials for a course on Structural Bioinformatics, including practical exercises on molecular dynamics simulations, protein structure prediction, and molecular docking. It serves as a resource for understanding and applying computational methods in molecular biology and bioinformatics.

The Benchmarking-Single-Cell-Perturbation repository provides a library of models for analyzing genetic and chemical perturbation data in single-cell contexts. It includes tools for predicting cellular responses to perturbations and offers datasets and benchmarks for evaluating model performance in drug discovery applications.

Dayhoff is a resource that combines extensive protein sequence data with generative language models to predict mutation effects and generate novel protein sequences. It includes datasets and models that facilitate the design and analysis of proteins, making it a valuable tool in molecular biology.

Denovo-Pinal is a tool for designing proteins from natural language descriptions, enabling users to generate novel protein sequences based on specified instructions. It utilizes advanced models to facilitate the design process, making it a valuable resource in the field of molecular biology and protein engineering.

This repository provides tutorials and code for training neural network potentials to simulate protein thermodynamics. It aims to improve the efficiency and accuracy of traditional methods used in molecular simulations.

DiffAbXL is a benchmarking tool for generative models aimed at antibody design, specifically evaluating log-likelihood scores for ranking antibody sequences based on their predicted binding affinities. It provides datasets and methodologies for assessing the performance of various models in the context of antibody optimization.

PoET is a generative model designed for protein families that enables the prediction of variant effects and the generation of protein sequences. It utilizes deep learning techniques to analyze and score protein variants based on their fitness, making it a valuable tool in protein engineering and bioinformatics.

ScoreMD is a framework designed for training energy-based diffusion models that can perform both independent sampling and continuous molecular dynamics simulations. It provides tools for energy estimation and generative modeling in the context of molecular dynamics.

The 'protein-design-skills' repository provides a set of 21 Claude Code skills aimed at facilitating computational protein design. It includes a standard pipeline for designing protein binders and utilizes various skills for optimizing and generating protein structures.

This repository provides Jupyter notebooks for a workshop on Python for Cheminformatics-Driven Molecular Docking. It includes practical exercises on digital representations of molecules, exploring chemical data, and preparing structures for docking, making it a useful resource for those interested in molecular docking techniques.

GRO2LAM is a Python tool designed to convert Gromacs input files into Lammps input files, facilitating the transition between these two molecular dynamics simulation software. It supports various molecular structures and parameters, making it useful for researchers in computational chemistry.

SSAGES is an open-source software suite for advanced general ensemble simulations, providing an engine-agnostic framework for molecular dynamics. It supports multiple molecular dynamics engines and offers various advanced sampling methods and collective variables for enhanced molecular simulations.

NEP_CPU is a standalone C++ implementation of the neuroevolution potential (NEP) designed for molecular dynamics simulations. It interfaces with LAMMPS, allowing users to perform simulations using machine-learned potentials, making it a valuable tool for molecular modeling and simulations.

OpenFermion-Psi4 is a plugin that allows the Psi4 electronic structure package to interface with OpenFermion, facilitating quantum simulations of fermionic systems. It is designed to support quantum chemistry applications, particularly in the context of molecular simulations.

MLIP Arena is a benchmark platform designed to evaluate machine learning interatomic potentials (MLIPs) beyond conventional error metrics. It aims to improve the predictive accuracy and efficiency of molecular modeling by assessing the physical soundness of MLIPs in real-world scenarios.

DiffPack is a torsional diffusion model that predicts the conformation of protein side-chains based on their backbone structures. It utilizes a diffusion process to improve the accuracy of side-chain packing, making it a valuable tool for protein design.