/tools

Prolint2 is an optimized tool that calculates distance-based lipid-protein interactions from molecular dynamics trajectories of membrane protein systems. It provides functionalities for analyzing and visualizing these interactions, making it useful for researchers in computational chemistry and molecular biology.

This repository contains resources and tutorials related to Cheminformatics, aimed at helping users understand and apply various molecular modeling techniques. It includes Jupyter notebooks and utilities that facilitate molecular property prediction and design.

TCRcube is a machine learning model designed for predicting the interactions between peptide-MHC complexes and T-cell receptors (TCRs). It utilizes pre-computed representations from ESM2 and AlphaFold2 to facilitate inference and training on molecular datasets, making it a valuable tool in the field of molecular biology.

TrDesign_partialhall is a tool that supports the design of protein structures with partial hallucination capabilities. It allows users to modify and generate protein sequences based on provided PDB files, facilitating the optimization and design of molecular structures.

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.

The kissim_app repository provides tools for comparing structural pockets of kinases using the kissim fingerprint. It facilitates the analysis of kinase structures, which is essential for understanding protein interactions and potential drug targets.

QRCI is a tool that calculates the Quantitative Ring Complexity Index, which profiles the topology and diversity of ring systems in molecules. It is useful for molecular design and optimization by providing insights into the complexity and characteristics of chemical structures.

DeepMD-PyTorch is a deprecated repository that provided a PyTorch implementation of the DeePMD framework, which is designed for molecular dynamics simulations and predicting molecular properties. It has been migrated to DeePMD-kit, which continues to support these functionalities.

TED-Gen is a framework designed for generating and analyzing atomic structures at van der Waals interfaces using a generative model. It utilizes experimental and simulated data to create high-quality training datasets and offers tools for training models to analyze stacking patterns in materials.

AF2Dock is a tool for predicting the interactions between proteins and ligands, utilizing advanced machine learning techniques. It supports training and inference for molecular docking tasks, making it relevant for applications in drug discovery and protein design.

PeSTo-Carbs is a tool designed to predict protein-carbohydrate and protein-cyclodextrin binding interfaces using geometric deep learning techniques. It provides models that can be applied to PDB files to generate predictions, making it useful for researchers in molecular biology and drug discovery.