/tools

P4ward is an automated pipeline for modeling Protacs ternary complexes, allowing researchers to generate and analyze complex structures. It utilizes open-source tools for structural biology and provides interactive visualizations and summary tables of the modeling results.

DockCoV2 is a molecular docking pipeline that facilitates the prediction of binding affinities between FDA-approved drugs and SARS-CoV-2 proteins. It provides a comprehensive drug database and allows users to download docking data for further analysis.

AutoGrid is a software tool designed to precalculate grids used by docking programs like AutoDock. It helps predict the binding of small molecules to proteins, facilitating structure-based drug design and virtual screening.

FABFlex is a tool designed for fast and accurate blind flexible docking of molecules, particularly proteins and ligands. It includes functionalities for inference and training of models to predict molecular interactions and structures.

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.

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.

AllMetal3D is a tool designed to predict metal and water binding sites in proteins using 3D convolutional neural networks (3DCNNs). It provides functionalities for both local and server-based usage, facilitating research in protein structure and interactions.

TAGMol is a framework for target-aware gradient-guided molecule generation, aimed at optimizing molecular properties for drug design. It includes functionalities for training models and evaluating generated molecules based on various criteria such as binding affinity and drug-likeness.

ECIFGraph is a tool designed to predict protein-ligand binding affinities by utilizing a water network-augmented two-state model. It integrates deep learning techniques to enhance the accuracy of scoring functions in molecular docking and virtual screening applications.

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.

DockTGrid is a Python package designed to generate customized voxel representations of protein-ligand complexes, facilitating deep learning applications. It supports GPU acceleration and is compatible with various file formats, making it a useful tool for molecular docking and virtual screening tasks.

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.

Drugforge is a toolkit designed for open antiviral drug discovery, offering a range of functionalities including molecular docking, simulations, and machine learning models for predicting compound activity. It aims to support the medicinal chemistry community with a robust pipeline of computational tools.