/tools

AlphaFold is an open-source implementation of a deep learning model that predicts protein structures from amino acid sequences. It utilizes advanced algorithms to provide accurate predictions, significantly aiding in molecular biology research and applications.

AlphaFold 3 is an inference pipeline that allows users to predict the three-dimensional structures of proteins based on their amino acid sequences. It leverages advanced machine learning techniques to provide accurate predictions, which are essential for understanding biomolecular interactions and functions.

RDKit is a comprehensive cheminformatics library that provides tools for molecular property prediction, descriptor generation, and various molecular operations. It supports both small molecules and proteins, making it a versatile tool for researchers in computational chemistry and molecular biology.

MMseqs2 is an ultra-fast and sensitive software suite for searching and clustering large sets of protein and nucleotide sequences. It significantly improves the speed and sensitivity of sequence searches compared to traditional methods like BLAST, making it a valuable tool for molecular biology research.

Chai-1 is a multi-modal foundation model for predicting the structures of various biomolecules, including proteins, small molecules, DNA, and RNA. It utilizes advanced techniques to achieve state-of-the-art performance in molecular structure prediction across multiple benchmarks.

This repository is an unofficial PyTorch implementation of AlphaFold2, a model that predicts protein structures from amino acid sequences. It utilizes advanced deep learning techniques to generate accurate structural predictions, contributing significantly to the field of molecular biology.

AlphaFold 3 - Pytorch is an implementation of the AlphaFold 3 model from Google DeepMind, designed to predict protein structures using deep learning techniques. It provides functionalities for training and evaluating models on molecular data, particularly focusing on protein structures.

ProtTrans is a repository that offers pre-trained language models specifically designed for proteins, enabling tasks such as feature extraction, prediction, and protein sequence generation. It supports the bioinformatics community by providing tools for analyzing protein sequences and structures.

Open Babel is a versatile chemical toolbox designed for handling chemical data across multiple formats. It allows users to search, convert, analyze, and store molecular data, supporting a wide range of applications in chemistry and molecular modeling.

MolecularNodes is an add-on for Blender that facilitates the import and visualization of structural biology data. It allows users to create animations from molecular structures and import molecular dynamics trajectories, enhancing the representation of proteins and other molecules.

3Dmol.js is a WebGL accelerated JavaScript library designed for online molecular visualization. It supports various molecular file formats and allows users to create interactive and visually appealing representations of molecular structures in web applications.

SimpleFold is a protein folding model that utilizes a generative flow-matching approach to predict protein structures from sequences. It is designed to be efficient and scalable, achieving competitive performance on standard folding benchmarks.

The 'tf-gnn-samples' repository provides TensorFlow implementations of various Graph Neural Network architectures. It includes tasks related to molecular property prediction, such as protein-protein interactions and quantum chemistry, making it a useful resource for researchers in computational chemistry and molecular biology.

AutoDock Vina is a fast and widely used open-source docking program that facilitates the docking of ligands to macromolecules. It supports multiple ligands and batch mode for virtual screening, making it a valuable tool in computational drug discovery.

BoltzGen is a tool for designing and generating protein structures based on specified design criteria. It utilizes advanced algorithms to produce ranked sets of protein designs, facilitating the exploration of novel molecular architectures.

Open-AF3 is an open-source implementation of AlphaFold 3, a model that predicts the structures of biomolecules such as proteins. It utilizes advanced machine learning techniques to generate accurate structural predictions based on input sequences, making it a valuable tool for researchers in molecular biology.

RoseTTAFold All-Atom is a neural network designed for predicting the structures of various biomolecular assemblies, including proteins, nucleic acids, and small molecules. It provides functionalities for predicting protein-nucleic acid complexes and covalently modified proteins, making it a valuable tool in molecular biology and computational chemistry.

Dynamic PDB is a large-scale dataset that integrates dynamic behaviors and physical properties in protein structures, enhancing existing protein databases. It includes data from all-atom molecular dynamics simulations, capturing conformational changes and various physical attributes of proteins.

BioPandas provides tools for handling molecular structures, particularly from PDB and MOL2 files, using pandas DataFrames. It facilitates the analysis and manipulation of protein structures, making it useful for tasks in drug discovery and computational biology.

AIRS is an open-source collection of software tools and datasets focused on artificial intelligence applications in quantum, atomistic, and continuum systems. It includes resources for predicting molecular properties, designing molecules, and conducting simulations, making it highly relevant to the fields of computational chemistry and molecular biology.

Ketcher is an open-source web-based chemical structure editor designed for chemists and laboratory scientists. It provides features for drawing, editing, and visualizing molecular structures in various formats, supporting both small molecules and macromolecules.

PLIP (Protein-Ligand Interaction Profiler) is a tool designed to analyze and visualize non-covalent interactions between proteins and ligands in PDB files. It facilitates the understanding of molecular interactions, which is crucial for applications in drug discovery and molecular biology.

PDBFixer is an application that addresses common issues in Protein Data Bank files, such as adding missing atoms and building loops, to facilitate their use in molecular simulations. It streamlines the preparation of protein structures for further computational analysis.

Avogadro libraries are designed for advanced molecular editing and visualization, supporting computational chemistry and molecular modeling. They offer a flexible plugin architecture and are suitable for a wide range of applications in bioinformatics and materials science.