/tools

ParaTemp is a Python package designed for the setup and analysis of parallel tempering and replica exchange molecular dynamics. It provides tools for analyzing molecular dynamics trajectories, particularly those generated by GROMACS, and is suitable for a variety of molecular systems.

Molecule-RNN is a recurrent neural network designed to generate drug-like molecules for drug discovery. It learns from a dataset and samples new molecules that resemble the training data, utilizing various tokenization methods for SMILES representation.

The Tox21 dataset repository contains data used in the Tox21 Data Challenge for evaluating the toxicity of compounds. It includes lists of compounds, their activity, and descriptors, facilitating in silico toxicity prediction and compound prioritization.

AIRFold is a protein structure prediction system built on AlphaFold2, providing scalable solutions for predicting protein structures through various advanced models. It integrates modules for co-evolutionary information extraction and offers a user-friendly interface for researchers in the life sciences.

Progen is a Python implementation of a language model for generating protein sequences, based on the ProGen paper. It utilizes various protein sequence datasets for training and evaluation, making it a valuable tool for protein design and generation.

The tqchem library is a Python tool designed for efficient manipulation and optimization of molecular structures. It allows users to perform high accuracy conformer optimization and convert molecular data formats, facilitating molecular design and analysis.

The `altmol` repository enhances Altair visualizations by integrating interactive 2D molecular structures using RDKit. It allows users to create interactive plots that visualize molecular properties, making it a useful tool for cheminformatics applications.

Lasso-Highlight is a Python tool that allows users to highlight specific substructures within molecules drawn using RDKit. It facilitates the visualization of molecular features by enabling the delineation of substructures, which can be useful in various molecular analysis tasks.

This repository implements a method for orbital-free density functional theory using continuous-time normalizing flows to optimize molecular densities. It allows for simulations of electronic densities for various molecules, contributing to the field of computational chemistry.

RosettaAbinitio is a Bash script designed to automate the process of running Rosetta Abinitio folding simulations on high-performance computing systems. It facilitates the submission of jobs for generating and clustering protein decoys, making it a useful tool for protein structure prediction.

This tool provides a pipeline for designing and optimizing single chain variable fragment (scFv) antibodies targeting specific peptides and histone modifications. It automates the process of identifying CDR regions and optimizing antibody frameworks using AI models.

Matcha is a molecular docking tool that utilizes multi-stage flow matching to enhance the accuracy and physical validity of docking predictions. It includes features for benchmarking and supports various datasets for evaluating docking performance.

HybridMD is a computational tool designed to solve the Poisson equation for closely-packed dielectric sphere composites. It integrates analytical methods with a mesh-free approach to enhance the efficiency of molecular dynamics simulations involving dielectric nanoparticles.

This repository contains data for QM9 molecules and reactions, along with Python scripts for processing and analyzing molecular data. It enables users to download molecular data, create databases of atomization energies, and process reaction information, making it a valuable resource for computational chemistry research.

TopoteinWorkshop is a topological deep learning extension to the ProteinWorkshop framework, designed for protein structure representation learning. It incorporates novel geometric topological neural network architectures and provides benchmarking capabilities for evaluating these models against existing ones.

VenomPred 2.0 is a platform that utilizes a machine learning consensus strategy to assess the toxicological profiles of small molecules. It is part of the MolBook Pro software and provides direct access for users to evaluate multiple compounds.

OptADMET is a webserver designed for ADMET optimization in drug discovery, providing a platform to analyze and optimize compounds based on 32 important ADMET properties. It utilizes a large database of experimental data and transformation rules to guide medicinal chemists in lead optimization.

CPIExtract is a software package that collects and harmonizes interaction data between small molecules and proteins from multiple databases. It provides pipelines for extracting interactions based on either compound or protein input, facilitating the analysis of compound-protein interactions.

msmJAX is a fast electrostatics code that utilizes the multilevel summation method with B-spline interpolation for evaluating electrostatic interactions in molecular dynamics simulations. It is built on Google JAX and aims to enhance the efficiency of molecular simulations.

Material Explorer 1.0 is a specialized assistant for material science research that helps users explore material properties, crystal structures, and computational simulations. It provides data from various sources to assist in material selection and application.

This repository provides scripts and data for conducting relative free energy calculations on terminally-blocked amino acids and the barnase-barstar complex. It utilizes the Perses framework for molecular simulations, enabling the analysis of molecular interactions and dynamics.

The LAMMPS Test Suite repository contains utilities for testing the LAMMPS molecular dynamics code. It allows users to run compilation, regression, and unit tests to ensure the accuracy and reliability of molecular simulations.

OCEAN is a web-based tool that predicts the target activity of chemical structures using data from the ChEMBL database. It allows users to input molecular structures and receive predictions on their biological activity, making it a valuable resource in drug discovery.