/tools

AttentionDTA_BIBM is a repository that implements a model for predicting drug-target binding affinity using an attention mechanism. It includes code for data processing, model training, and testing, making it a useful tool for researchers in the field of molecular property prediction.

This repository contains OPLS-AA force field parameters designed for simulating deep eutectic solvents. It includes a tutorial for constructing a simulation box and performing molecular dynamics simulations using these parameters.

GRAPPA is a graph neural network model designed to predict the parameters of the Antoine equation based on molecular structure. It allows users to calculate vapor pressure and boiling temperatures using the SMILES representation of molecules.

C3PO is a tool designed to classify SMILES strings into CHEBI classes using learning classification programs. It leverages large language models to enhance the categorization of molecular structures.

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.

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.

ML Conformer Generator is a tool that utilizes Equivariant Diffusion Models and Graph Convolutional Networks to generate novel 3D molecular conformations that adhere to specific shape constraints. It supports workflows in molecular design by allowing the generation of molecules that are chemically valid and spatially similar to reference structures.

pytng is a Python library designed to facilitate access to data stored in TNG files, commonly used in molecular dynamics simulations. It allows users to easily read and manipulate trajectory data from molecular simulation programs like Gromacs.

This repository contains code for generating molecular conformers using SO(3) Averaged Flow-Matching and Reflow techniques. It provides a framework for efficient conformer generation, which is essential in molecular design and optimization.

pySiRC is a web application designed to predict reaction rate constants through machine learning models utilizing molecular fingerprints. It employs algorithms like XGBoost and Random Forest to facilitate predictions for specific oxidation reactions.

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.

The 'qchem' repository is a framework for molecular modeling that combines machine learning and quantum chemistry to explore molecular properties and datasets. It provides tools for implementing models and datasets in a modular and extendable manner, facilitating research in molecular simulations and property predictions.

Conformer-Search is a workflow designed for minimum energy conformer search of molecules using force field optimization methods like UFF and MMFF94. It allows users to import molecules from SMILES, generate conformers, optimize them, and select the minimum energy conformer for further analysis.

The 'rif' repository provides Python libraries for computational protein design, specifically utilizing Rotamer Interaction Fields. It aims to facilitate the design and optimization of protein structures, making it a valuable tool in molecular biology and computational chemistry.

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.

This repository provides code for evaluating numerical methods used in Langevin dynamics simulations. It systematically enumerates different integrators and measures their error in sampling distributions, contributing to the field of molecular dynamics.

This repository contains a deep learning project aimed at reconstructing and generating molecules from low-dimensional representations. It utilizes Variational Autoencoders (VAEs) and employs the ZINC250K dataset for training and evaluation, making it a relevant tool for molecular design.

The qm9star_query repository facilitates access to the QM9star database, which includes two million DFT-computed molecular structures. It also provides tools for querying the database and training neural network models using the dataset, making it useful for molecular property prediction and research.

ESMBind is a deep learning and physics-based workflow designed to predict metal-binding proteins and generate their 3D structures with bound metal ions. It integrates evolutionary scale modeling for residue-level predictions and physics-based modeling for detailed structural generation.

CATNIP is a tool designed to facilitate the prediction of enzyme compatibility with small molecules in biocatalysis. It utilizes machine learning models and a curated dataset to navigate between chemical and protein sequence spaces, aiming to streamline biocatalytic synthetic strategies.

GA4AMOEBA is a genetic algorithm program designed to optimize parameters of the AMOEBA polarizable force field. It is intended for use in molecular simulations, particularly in high-performance computing environments.

DefiNet is a tool designed for processing datasets related to high-density and low-density defects in materials. It includes functionalities for data preprocessing, model training, and predicting relaxed structures, making it relevant for molecular simulations and materials science.

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.