/tools

The SMILES Transformer is a tool that extracts molecular fingerprints from SMILES representations of chemical molecules. It utilizes a transformer architecture to learn latent representations useful for various downstream tasks in drug discovery.

ChemDataExtractor is a toolkit designed to automatically extract chemical information from scientific documents. It utilizes natural language processing techniques to identify and parse chemical entities and data from various document formats.

Scikit-fingerprints is a Python library designed for efficient computation of molecular fingerprints, which are crucial in drug discovery and chemical analysis. It provides a scikit-learn compatible interface, allowing users to integrate molecular fingerprints into machine learning workflows and access popular benchmark datasets.

The RDKit Tutorials repository offers a collection of tutorials designed to help users learn how to effectively utilize the RDKit toolkit for various molecular tasks. It covers practical applications in cheminformatics, including molecular property predictions and manipulations.

xyz2mol is a Python tool that converts Cartesian coordinates from xyz files into RDKit molecular objects, allowing for the generation of molecular graphs. It supports the handling of resonance forms and can output various molecular formats, making it useful for computational chemistry applications.

Mol2vec is an unsupervised machine learning tool that generates vector representations of molecular substructures, facilitating the analysis and prediction of molecular properties. It allows users to prepare molecular data, train models, and featurize new samples using learned embeddings.

The 'stk' library is designed for the construction and manipulation of complex molecules, facilitating automatic molecular design and the creation of molecular databases. It serves as a framework for researchers in computational chemistry and materials science to explore molecular structures and properties.

Kekule.js is an open-source JavaScript toolkit designed for cheminformatics, enabling users to read, write, display, and edit chemical objects. It provides functionalities for performing various cheminformatics tasks, including molecule comparison and structure searching.

MolScribe is an image-to-graph model that converts molecular images into their corresponding chemical structures. It employs deep learning techniques to facilitate molecular structure recognition, making it a valuable tool for researchers in computational chemistry and related fields.

molplotly is an add-on for Plotly that allows users to display 2D images of molecules in interactive figures. It utilizes RDKit for molecular visualization and is useful for data exploration in cheminformatics.

mzmine is an open-source software designed for processing mass spectrometry data, providing a comprehensive set of modules for analyzing various types of mass spectrometry data, including liquid and gas chromatography. It aims to facilitate the analysis of molecular properties through mass spectrometry techniques.

This repository serves as a comprehensive resource for machine learning in drug discovery, offering curated datasets, benchmarks, and educational materials. It focuses on enhancing the understanding and application of cheminformatics in predicting molecular properties and interactions.

mols2grid is an interactive molecule viewer designed for visualizing 2D structures of molecules. It utilizes RDKit for cheminformatics tasks and provides a user-friendly interface for exploring molecular data.

Atomsk is a command-line tool that allows users to manipulate and convert atomic data files, facilitating the construction of crystals and polycrystals, as well as the introduction of defects in atomic systems. It supports various file formats and is useful in the context of materials science and atomic simulations.

The 'py4chemoinformatics' repository provides resources and tools for chemoinformatics, including methods for predicting molecular properties, generating chemical structures, and utilizing machine learning techniques in molecular design and analysis. It serves as a comprehensive guide for researchers in the field.

The ChEMBL Structure Pipeline provides protocols for standardizing and salt stripping molecules, facilitating the preparation of chemical structures for further analysis. It includes functionalities for checking the quality of molecular structures and retrieving parent compounds, making it a valuable tool in molecular data processing.

nvMolKit is a GPU-accelerated library that facilitates key computational chemistry tasks, including molecular similarity assessments and conformer generation. It is optimized for performance on NVIDIA GPUs, making it suitable for various molecular modeling applications.

PaDELPy is a Python wrapper for the PaDEL-Descriptor software, enabling users to calculate molecular descriptors and fingerprints from SMILES strings, MDL MolFiles, and SDF files. It facilitates property prediction and cheminformatics tasks by providing a straightforward interface for descriptor calculation.

RDKit.js is a cheminformatics and molecule rendering toolbelt for JavaScript, enabling users to visualize and manipulate molecular structures. It leverages the RDKit library's functionalities, making it suitable for applications in drug discovery and molecular analysis.

MolecularGraph.jl is a graph-based toolkit designed for cheminformatics and molecular modeling. It offers functionalities for analyzing molecular properties, performing substructure queries, and visualizing molecular graphs, making it a valuable resource for computational chemistry applications.

DrugEx is a deep learning toolkit designed for scaffold-constrained drug design using graph transformer-based reinforcement learning. It allows users to generate novel drug molecules by optimizing multiple objectives, making it a valuable tool in the field of drug discovery.

The 'useful_rdkit_utils' repository provides a collection of useful functions built on the RDKit library, aimed at facilitating various cheminformatics tasks. It includes Jupyter notebooks that demonstrate how to utilize these functions for molecular analysis and manipulation.

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.

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.