/tools

FABFlex is a tool designed for fast and accurate blind flexible docking, enabling the prediction of molecular interactions between proteins and ligands. It provides functionalities for inference and model training, making it suitable for applications in drug discovery and molecular simulations.

RDKit Heatmaps is a Python package that allows users to draw custom heatmaps on molecular depictions, enhancing the visualization of molecular properties. It utilizes RDKit functionalities to map values to atoms and bonds, providing a visual representation that can aid in understanding molecular characteristics.

ACID is a web server designed for drug repurposing using a consensus inverse docking method. It evaluates the binding affinities of small molecules to various proteins, providing a valuable resource for molecular docking studies.

CSMILES is a tool that extends the SMILES notation to encode conformer structures in a compact form. It allows for the encoding and decoding of molecular structures, facilitating the analysis and manipulation of 3D conformers.

This repository implements a reinforcement learning framework combined with active learning to optimize the selection of small-molecule drug candidates for in-silico screening. It enhances the efficiency of training by focusing on informative samples, thereby reducing computational costs.

This tool implements parallel graph neural networks to analyze protein-ligand interactions, facilitating the prediction of binding affinities and other molecular properties. It includes data preparation scripts for both classification and regression models, making it suitable for molecular property prediction tasks.

The ADMET Prediction System utilizes deep learning to predict Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties from molecular structures. It employs Graph Neural Networks and provides mechanistic interpretations of the predictions, making it a valuable tool in preclinical drug development.

This repository contains code for predictive modeling of late-stage functionalization in chemistry using transfer learning techniques. It includes modules for training models, predicting regioselectivity of new molecules, and handling datasets relevant to molecular properties.

Zinc-Million is a tool that allows users to download millions of small molecules from the ZINC database in 3D SDF format. It is designed for large-scale virtual screening against specific protein targets, making it useful for drug discovery and molecular simulations.

HackaMol is an object-oriented Perl library that facilitates computational work on molecular structures at multiple scales. It provides methods for organizing and manipulating atoms and molecules, making it useful for tasks in molecular modeling and simulations.

KinaseDocker² is a computational tool that automates the docking and scoring of kinase inhibitors using a Deep Neural Network. It can be used as a PyMOL plugin or through the command line, leveraging GPU-accelerated docking methods.

pyqchem is a Python repository that contains routines for performing electronic structure calculations on atoms and small molecules. It allows users to execute various quantum chemistry methods, such as MP2, by modifying the script parameters.

ML4NMR is a machine learning-based tool designed to correct computed NMR chemical shifts from DFT calculations towards higher accuracy. It includes functionalities for data acquisition and model training, specifically targeting the prediction of NMR properties for small molecules.

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.

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.

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.

TorchMMFF94 provides a PyTorch implementation of the MMFF94 force field, enabling molecular energy minimization both in isolation and in the context of protein pockets. It offers a simple interface for testing and running examples related to molecular optimization.

The 'topo-tools-scripts' repository provides scripts for preparing input files for molecular dynamics simulations of gases in MOF-74 analogues. It focuses on generating LAMMPS input files for simulating the adsorption of methane and carbon dioxide in metal-organic frameworks using a DFT-derived force field.

ConveyorLC is a parallel virtual screening pipeline designed for docking and MM/GBSA calculations. It facilitates the preparation of receptors and ligands, as well as the execution of docking simulations, making it a valuable tool for drug discovery and molecular modeling.

This repository provides an introduction to small molecule drug design using structure-based techniques and interactive Jupyter notebooks. It covers ligand-based analysis, generative design with REINVENT4, and docking to analyze interactions with the Zika virus protease.

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.

This repository provides educational materials for the 2025 CCPBioSim Training Week, focusing on parameterizing small molecules and conducting molecular dynamics simulations for protein-ligand complexes. It includes Jupyter Notebooks that guide users through practical applications in molecular modeling.

molmetrics is a Python tool designed to assess 3D molecular structures by providing various metrics. It allows users to evaluate the validity and uniqueness of molecular structures and calculate bond length distributions, making it useful for molecular analysis and simulations.

DrugDataResource is a repository that offers a variety of datasets aimed at facilitating drug discovery and development. It includes datasets for drug-target interactions, ADMET properties, and other molecular characteristics, which are essential for computational chemistry and molecular biology research.