/tools

Fragmenstein is a tool that merges and links compounds by stitching them together based on atomic overlap, allowing for the generation of new molecular conformers. It also places follow-up molecules in relation to parent compounds, facilitating molecular design and optimization in drug discovery.

ATOMICA is a geometric AI model that learns universal representations of intermolecular interactions at an atomic scale. It is pretrained on a large dataset of molecular interaction interfaces and can be used for various downstream tasks, including binding site prediction and embedding biomolecular complexes.

autodE is a Python module designed for the automated calculation of reaction profiles from SMILES strings of reactants and products. It provides functionalities such as transition state location and conformer searching, facilitating the study of molecular reactions.

ScaffoldGraph is an open-source cheminformatics library that utilizes RDKit and NetworkX to generate and analyze scaffold networks and trees. It allows users to explore scaffold-space by generating sub-scaffolds from input molecules, making it a valuable tool for molecular design and analysis.

MolT5 is a tool that facilitates the translation between molecular representations (like SMILES) and natural language descriptions. It includes pretrained models for tasks such as molecule captioning and generation, along with datasets for training and evaluation.

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.

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.

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.

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.

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.

ChemTS is a software tool that utilizes Monte Carlo Tree Search combined with neural networks to design novel molecules with desired properties such as HOMO-LUMO gap and logP. It also allows for the design of molecules that are active against target proteins, facilitating advancements in drug discovery.

Graph-ViT-MLPMixer is an implementation of a model that generalizes ViT and MLP-Mixer architectures to graph data, enabling tasks such as graph classification and regression on molecular datasets. It supports various datasets, including those related to peptides and small molecules, making it relevant for molecular property prediction.

rdeditor is a simple RDKit molecule editor GUI that allows users to interactively edit molecular structures. It provides tools for adding and modifying atoms and bonds, making it useful for molecular design and visualization.

DrugEx is an open-source software library designed for the de novo design of small molecules using deep learning generative models within a multi-objective reinforcement learning framework. It provides various generator architectures and scoring tools to facilitate the generation and optimization of drug-like compounds.

FPSim2 is a Python/C++ package that enables fast compound similarity searches using optimized algorithms. It is particularly useful in cheminformatics applications, allowing researchers to efficiently find similar molecules based on their chemical properties.

AIMNet2 is a calculator that integrates a neural network potential for performing fast and reliable molecular simulations. It supports a wide range of molecular types and provides interfaces for popular simulation packages, making it versatile for various computational chemistry applications.

ChatDrug is a tool for conversational drug editing that utilizes retrieval and domain feedback to assist in the design and modification of small molecules, peptides, and proteins. It includes datasets for training and evaluation, making it a comprehensive resource for drug discovery.

PMDM is a software tool that enables the generation of 3D bioactive molecules and lead optimization by utilizing a dual diffusion model. It supports molecular docking and provides benchmarks for evaluating generated molecules, making it a valuable resource for drug discovery and molecular design.

G-SchNet is a generative model that creates 3D molecular structures in an autoregressive manner. It is designed to work with datasets like QM9, allowing for the generation and analysis of small molecules based on their atomic positions and types.

SIRIUS is a software framework that facilitates the de-novo identification of metabolites using tandem mass spectrometry. It automates the analysis of mass spectra to deduce molecular formulas and structures, integrating various tools for enhanced metabolite identification.

The RDKit Python Wheels repository provides precompiled binaries for the RDKit cheminformatics toolkit, which is used for various molecular modeling tasks including property prediction, molecular simulations, and manipulation of chemical structures. It facilitates the installation of RDKit, enabling users to perform computational chemistry and molecular biology tasks efficiently.

Molchanica is a comprehensive tool for editing, visualizing, and simulating molecules and proteins. It includes features for molecular dynamics, docking, and predicting pharmacokinetic properties, making it suitable for drug discovery and molecular design.

DockStream is a docking wrapper that automates docking execution and post hoc analysis, providing access to various ligand embedders and docking backends. It is integrated with the REINVENT platform, allowing for the incorporation of docking into the molecular design process.

Uni-GBSA is an automatic workflow designed to perform MM/GB(PB)SA calculations for evaluating ligand binding free energies in virtual screening. It includes functionalities for topology preparation, structure optimization, and batch processing of multiple ligands against a protein target.