/tools

ProTrek is a trimodal protein language model designed to enhance protein searches by integrating sequence, structure, and function information. It utilizes contrastive learning to improve retrieval tasks and provides embeddings for various protein-related applications.

The SPICE dataset is a collection of quantum mechanical data aimed at training potential functions for simulating drug-like small molecules interacting with proteins. It includes a wide range of chemical space and conformations, making it a valuable resource for molecular machine learning applications.

Chemfiles is a high-quality library that facilitates reading and writing of trajectory files from computational chemistry simulations. It provides a unified interface for various file formats, enabling users to conduct post-processing analysis and extract physical information from molecular simulations.

Deep-Drug-Coder is a generative neural network designed for de novo drug design, utilizing a conditional recurrent neural network to generate SMILES strings based on specified molecular properties. It aims to facilitate the generation of molecules that meet desired bioactivity criteria, making it a valuable tool in the field of drug discovery.

The Variational Dynamical Encoder (VDE) is a tool designed to reduce high-dimensional time-series data from chemical and biophysical systems into simpler representations using deep learning techniques. It captures complex dynamics, such as those in protein folding and Brownian motion, making it useful for analyzing molecular behaviors.

Pytraj is a Python front-end for cpptraj, enabling interactive analysis of molecular dynamics simulations. It supports a wide range of data analyses and file formats, making it a valuable tool for researchers in computational chemistry and molecular biology.

fftool is a Python tool that facilitates the creation of force field input files for molecular dynamics simulations. It supports systems composed of molecules, ions, or extended materials and integrates with various molecular dynamics packages like LAMMPS, OpenMM, and GROMACS.

The Basis Set Exchange repository is a library that contains a curated database of quantum chemistry basis sets. It allows users to obtain and manipulate basis set data, which is crucial for performing accurate quantum chemistry calculations.

Bgflow is a PyTorch framework designed for Boltzmann Generators and other sampling methods, enabling accurate computation of free-energy differences and discovery of new molecular configurations. It integrates various sampling techniques, including molecular dynamics, to facilitate advanced molecular simulations.

Auto3D is a tool that automatically generates low-energy 3D molecular conformers from SMILES or SDF input using neural network potentials. It includes features for tautomer enumeration, stereoisomer generation, and geometry optimization, making it useful for molecular design and optimization tasks.

Genie 2 is a protein structure diffusion model designed for unconditional protein generation and motif scaffolding. It includes training and inference code, allowing users to generate diverse protein structures and evaluate their designability and novelty.

The 'deeptime' repository provides a toolbox for dimension reduction of time series data using a time-lagged autoencoder, specifically designed for applications in molecular dynamics. It also includes a Variational Approach for Markov Processes networks, which can be useful for analyzing molecular simulations.

MolGen is a tool for domain-agnostic molecular generation that incorporates chemical feedback to optimize molecular properties. It supports de novo molecule generation and fine-tuning for specific properties like QED and logP, making it valuable for molecular design and optimization tasks.

GromacsWrapper provides a Python interface to GROMACS tools, facilitating the setup and execution of molecular dynamics simulations. It includes helper functions for common tasks in molecular simulations, making it easier for users to work with GROMACS.

The 'mdgrad' repository offers a PyTorch-based differentiable molecular dynamics simulator that allows for end-to-end simulations and optimization of molecular properties. It includes features such as automatic differentiation and compatibility with various force fields, making it suitable for advanced molecular simulations and research.

tblite is a light-weight framework designed for tight-binding quantum chemistry calculations. It allows users to perform single-point energy calculations and provides a high-level interface for manipulating parametrization data, making it useful for molecular property predictions.

Genie is a tool for de novo protein design that utilizes equivariant diffusion models to generate protein structures. It includes functionalities for training models, sampling generated domains, and evaluating the results against established benchmarks.

PiFold is a tool designed for effective and efficient protein inverse folding, generating protein sequences that fold into specified structures. It employs novel features and a graph neural network approach to enhance the accuracy and speed of protein design.

DrugCLIP is a tool designed for contrastive protein-molecule representation learning aimed at enhancing virtual screening processes in drug discovery. It includes datasets and methodologies for training models that predict interactions between proteins and small molecules.

Neural-Network-Models-for-Chemistry is a repository that provides a variety of neural network models aimed at advancing computational chemistry. It includes methods for quantum chemistry, force fields, and molecular simulations, facilitating the prediction of molecular properties and behaviors.

MolVS is a Python-based tool that focuses on the validation and standardization of chemical structures. It utilizes the RDKit framework to enhance data quality by standardizing representations, helping with de-duplication, and identifying relationships between molecules.

QCElemental is a Python library that offers data structures for quantum chemistry, including a periodic table and physical constants. It also includes functionalities for parsing molecules, making it useful for various molecular chemistry applications.

IgLM is a tool for generative language modeling aimed at antibody design. It allows users to generate unique antibody sequences and evaluate their likelihood based on specified parameters, facilitating the design and optimization of antibodies.

FlowMol is a flow matching model that facilitates the generation of 3D small molecules from scratch. It employs advanced machine learning techniques to create novel molecular structures, making it a valuable tool for drug discovery and molecular design.