Open source toolkit for cheminformatics
Releases every 6 months
|||(1, 2, 3, 4) These implementations are functional but are not necessarily the best, fastest, or most complete.|
|||Contribution from Andrew Dalke|
|||Putta, S., Eksterowicz, J., Lemmen, C. & Stanton, R. “A Novel Subshape Molecular Descriptor” Journal of Chemical Information and Computer Sciences 43:1623–35 (2003).|
|||Tosco, P., Balle, T. & Shiri, F. Open3DALIGN: an open-source software aimed at unsupervised ligand alignment. J Comput Aided Mol Des 25:777–83 (2011).|
|||Landrum, G., Penzotti, J. & Putta, S. “Feature-map vectors: a new class of informative descriptors for computational drug discovery” Journal of Computer-Aided Molecular Design 20:751–62 (2006).|
|||Nguyen, K. T., Blum, L. C., van Deursen, R. & Reymond, J.-L. Classification of Organic Molecules by Molecular Quantum Numbers. ChemMedChem 4:1803–5 (2009).|
|||Riniker, S. & Landrum, G. A. Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods. Journal of Cheminformatics 5:43 (2013).|
The Contrib directory, part of the standard RDKit distribution, includes code that has been contributed by members of the community.
LEF: Local Environment Fingerprints
Contains python source code from the publications:
Contribution from Anna Vulpetti
Contains a set of pharmacophoric feature definitions as well as code for finding molecular frameworks.
Contribution from Markus Kossner
PBF: Plane of best fit
Contains C++ source code and sample data from the publication:
Contribution from Nicholas Firth
mmpa: Matched molecular pairs
Python source and sample data for an implementation of the matched-molecular pair algorithm described in the publication:
Hussain, J., & Rea, C. “Computationally efficient algorithm to identify matched molecular pairs (MMPs) in large data sets.” Journal of chemical information and modeling 50 339-348 (2010). http://dx.doi.org/10.1021/ci900450m
Includes a fragment indexing algorithm from the publication:
Wagener, M., & Lommerse, J. P. “The quest for bioisosteric replacements.” Journal of chemical information and modeling 46 677-685 (2006).
Contribution from Jameed Hussain.
SA_Score: Synthetic assessibility score
Python source for an implementation of the SA score algorithm described in the publication:
Ertl, P. and Schuffenhauer A. “Estimation of Synthetic Accessibility Score of Drug-like Molecules based on Molecular Complexity and Fragment Contributions” Journal of Cheminformatics 1:8 (2009)
Contribution from Peter Ertl
fraggle: A fragment-based molecular similarity algorithm
Python source for an implementation of the fraggle similarity algorithm developed at GSK and described in this RDKit UGM presentation: https://github.com/rdkit/UGM_2013/blob/master/Presentations/Hussain.Fraggle.pdf
Contribution from Jameed Hussain
This document is copyright (C) 2013-2014 by Greg Landrum
This work is licensed under the Creative Commons Attribution-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.
The intent of this license is similar to that of the RDKit itself. In simple words: “Do whatever you want with it, but please give us some credit.”