RDKit is a collection of cheminformatics and machine-learning software written in C++ and Python.
- BSD license - a business friendly license for open source
- Core data structures and algorithms in C++
- Python (2.x and 3.x) wrapper generated using Boost.Python
- Java and C# wrappers generated with SWIG
- 2D and 3D molecular operations
- Descriptor and Fingerprint generation for machine learning
- Molecular database cartridge for PostgreSQL supporting substructure and similarity searches as well as many descriptor calculators
- Cheminformatics nodes for KNIME
- Contrib folder with useful community-contributed software harnessing the power of the RDKit
Materials from user group meetings
Installation instructions are available in Docs/Book/Install.md.
Binary distributions, anaconda, homebrew
- Windows binaries are available with each release.
- RPMs for RedHat Enterprise Linux, Centos, and Fedora. Contributed by Gianluca Sforna.
- homebrew formula for building on the Mac. Contributed by Eddie Cao.
- recipes for building using the excellent conda package manager. Contributed by Riccardo Vianello.
Projects using RDKit
- ChEMBL Beaker - standalone web server wrapper for RDKit and OSRA
- myChEMBL (blog post, paper) - A virtual machine implementation of open data and cheminformatics tools
- sdf_viewer.py - an interactive SDF viewer
- sdf2ppt - Reads an SDFile and displays molecules as image grid in powerpoint/openoffice presentation.
- MolGears - A cheminformatics tool for bioactive molecules
- PYPL - Simple cartridge that lets you call Python scripts from Oracle PL/SQL.
- shape-it-rdkit - Gaussian molecular overlap code shape-it (from silicos it) ported to RDKit backend
- WONKA - Tool for analysis and interrogation of protein-ligand crystal structures
- OOMMPPAA - Tool for directed synthesis and data analysis based on protein-ligand crystal structures
- DeepChem - Machine learning library for small molecules
Code released under the BSD license.