/tools

Ringtail is a Python package that facilitates the storage and analysis of virtual screening results from AutoDock-GPU and AutoDock Vina. It allows users to create SQLite databases from docking results, perform filtering, and export data, making it a valuable tool for molecular docking studies.

OMTRA is a multi-task generative model that facilitates structure-based drug design by generating novel molecules and performing protein-ligand docking. It supports various tasks including unconditional and conditioned generation of ligands, making it a valuable tool in computational chemistry and drug discovery.

FASMIFRA is a tool for generating molecules quickly from a training set of molecular fragments using a method that matches the distribution of the training set. It also includes functionality for fragmenting molecules and has been evaluated in the GuacaMol benchmark for molecular generation methods.

PyQInt is an educational Python implementation of the Hartree-Fock method, designed to provide transparency in electronic structure calculations. It supports various molecular integrals and geometry optimization, making it a useful tool for learning and prototyping in computational chemistry.

EasyDock is a Python module designed to automate the molecular docking process, from molecule preparation to result analysis. It supports various docking programs and offers features like distributed computing and detailed protein-ligand interaction analysis.

SIRIUS is a framework designed for metabolomics mass spectrometry, enabling the identification of molecular formulas for small molecules. It includes various modules for isotope pattern analysis, fragmentation tree computation, and compound class prediction.

AaronTools.py is a Python library designed to automate routine tasks in quantum chemistry computations. It offers features for generating molecular structures, calculating steric parameters, and setting up quantum computation processes, making it a valuable tool for computational chemists.

LifeBrush is a VR toolkit that allows users to create and simulate biomolecular environments using a generative brush for painting molecular structures. It employs an agent-based modeling framework to visualize and interact with molecular dynamics in a 3D space.

The SAMPL6 repository contains challenge inputs and results for predicting molecular properties, specifically focusing on pKa and logP values of small molecules. It serves as a benchmark for evaluating computational methods in predicting these properties, providing datasets and performance evaluations for participants.

MolSnapper is a software tool that utilizes a conditioned diffusion model to generate 3D drug-like molecules. It is built on the MolDiff framework and is aimed at aiding in structure-based drug design.

The nmrgnn repository contains a graph neural network model for predicting NMR chemical shifts from protein structures and organic molecules. It includes functionalities for evaluating structures and analyzing molecular trajectories, making it a valuable tool in computational chemistry.

LDM-3DG implements a pipeline for latent 3D graph diffusion, enabling the generation and evaluation of molecular structures. It includes functionalities for training models on molecular data and generating embeddings for small molecules, making it a valuable tool for molecular design and docking applications.

Novana is a cheminformatics tool that allows for the decomposition of molecules into their scaffolds and shapes, enhancing the analysis of molecular datasets. It can be used for clustering and creating training/validation sets for machine learning, making it a valuable resource in molecular property prediction and design.

ConfVAE-ICML21 is an end-to-end framework designed for generating molecular conformations using a variational autoencoder approach. It provides tools for training models on molecular datasets and generating conformations for various molecules, making it a valuable resource in computational chemistry and molecular design.

CGRtools is a Python library designed for the manipulation of molecules and reactions using the Condensed Graph of Reaction (CGR) approach. It supports various operations such as format conversion, molecule standardization, and subgraph searching.

eMolFrag is a Python-based tool designed for molecular fragmentation using the BRICS algorithm. It aids in the decomposition of small molecules for fragment-based drug design, making it useful for predicting molecular properties and generating new molecular structures.

'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.

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.

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.

Chembience is a Docker-based platform designed for the rapid development of cheminformatics-centric web applications and microservices. It leverages RDKit for molecular data processing and supports the creation of applications that can predict molecular properties and handle various molecule types.

KERMT is a pretrained graph neural network model that focuses on predicting molecular properties, particularly for small molecules. It enhances the GROVER model by automating hyperparameter tuning and supports distributed pretraining, making it a valuable resource for molecular property prediction tasks.

Scopy is an integrated Python library that facilitates the screening of undesirable compounds in drug discovery. It includes modules for data preparation, screening filters, and the calculation of molecular properties, making it a valuable tool for designing high-quality chemical libraries.

CGCF-ConfGen is a tool for generating molecular conformations using neural generative dynamics. It allows users to train models and generate multiple conformations for molecules, making it useful for molecular design and optimization tasks.

3D-MCTS is a framework for structure-based de novo drug design that utilizes a fragment-based molecular editing strategy. It efficiently generates molecules with improved binding affinity and synthesizability, making it a valuable tool in drug discovery.