/tools

SGGRL is a framework designed for multi-modal representation learning aimed at predicting molecular properties using sequence, graph, and geometry data. It provides functionalities for processing data and performing molecular property predictions, making it relevant for computational chemistry applications.

Origin-1 is a generative AI platform designed for the de novo design of antibodies targeting novel epitopes. It includes data on binding affinity and optimization results, making it a valuable resource for antibody development in molecular biology.

The 'openmm-tutorials' repository offers a collection of Jupyter notebooks designed to help researchers learn how to utilize OpenMM for molecular dynamics simulations. It covers topics such as creating molecular systems and integrators, making it a valuable resource for practitioners in the field.

Uni-FEP-Benchmarks is a benchmark dataset aimed at systematically evaluating the Uni-FEP method for binding free energy calculations. It compiles diverse protein-ligand systems and chemical transformations to facilitate the validation and optimization of the Uni-FEP methodology, contributing to advancements in drug discovery.

This repository contains source code and documentation for a computer-assisted synthesis planning tool used to analyze reaction datasets in organic chemistry. It facilitates the extraction of templates and the training of policies for synthetic route generation.

ARC (Automated Rate Calculator) is a tool designed to automate electronic structure calculations, providing high-quality thermodynamic and kinetic data for chemical kinetic modeling. It processes molecular representations to compute properties such as thermodynamic values and rate coefficients.

SlowQuant is a Python-based molecular quantum chemistry program designed for both classic and quantum computing applications. It specializes in unitary parameterized wave functions and linear response methods, providing tools for simulating molecular properties and behaviors.

The `load-atoms` package is designed for loading open access datasets related to atomistic materials science. It facilitates the downloading and manipulation of datasets, making it useful for researchers in computational chemistry and materials science.

PropMolFlow is a tool for property-guided molecular generation using SE(3) equivariant flow matching. It includes datasets for training, benchmarks for molecular properties, and supports the generation of molecules conditioned on specific properties.

QC-DMET is a Python implementation of density matrix embedding theory designed for ab initio quantum chemistry calculations. It facilitates the study of molecular properties and behaviors through quantum mechanical simulations.

This repository provides code for fine-tuning protein language models using a parameter-efficient approach. It includes configuration files and scripts for running experiments related to protein interactions and symmetry, making it a useful tool for researchers in molecular biology.

The torchmd-cg repository provides examples for fitting parameters and running coarse-grained molecular dynamics simulations using TorchMD and Schnet. It is designed to facilitate the study of molecular behavior and properties through simulation techniques.

Porter5 is a tool designed for fast and accurate prediction of protein secondary structure in both 3 and 8 classes. It utilizes advanced machine learning techniques to enhance the prediction quality, making it a valuable resource for researchers in molecular biology.

'shape-it' is a shape-based alignment tool that utilizes Open Babel and RDKit for molecular shape alignment. It is designed to assist in the analysis and comparison of molecular structures, which is essential in fields like drug discovery and molecular modeling.

CARBonAra is a deep learning framework that facilitates the design of protein sequences by utilizing atomic coordinates and context-aware generation methods. It allows for the integration of molecular environments, including non-protein entities, enhancing the control over protein engineering and design.

This repository implements a machine learning-guided framework for protein design through directed evolution. It utilizes large language models to predict fitness scores and generate novel protein sequences, streamlining the optimization process in protein engineering.

This repository hosts various programming projects related to quantum chemistry, including methods for vibrational analysis and energy calculations. It serves as a resource for summer program participants to engage with computational chemistry concepts and tools.

The openff-fragmenter is a Python package designed to fragment molecules for quantum mechanics torsion scans. It allows users to visualize and manipulate molecular fragments, making it a useful tool in molecular design and computational chemistry.

The S3F repository provides a multimodal representation learning framework for predicting protein fitness. It integrates various protein features and is evaluated using the ProteinGym benchmark, making it a valuable tool for protein design and property prediction.

CCpy is a Python package designed for performing electronic structure calculations using coupled-cluster theory. It supports various methods for calculating molecular properties and simulating molecular systems.

GREA is a source code repository for a method that enhances graph neural networks for predicting molecular properties, particularly in the context of polymers. It includes implementations for various molecular datasets and provides tools for conducting experiments on these datasets.

VeloxChem is a Python-based open source quantum chemistry software designed for computing molecular properties and conducting various spectroscopy simulations using response theory. It is optimized for high-performance computing environments.

Uni-Dock2 is a GPU-accelerated molecular docking software that enhances docking accuracy through advanced algorithms. It supports various docking tasks, including virtual screening and covalent docking, making it a valuable tool for researchers in drug discovery and molecular design.