Reference baseline for high-performance cheminformatics fingerprint search benchmarking
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This version of chemfp includes command-lines tools to generate cheminformatics fingerprints and search those fingerprints by Tanimoto similarity, as well as a Python library which you can use to build new tools.
It is the no-cost/open source chemfp release track. It only supports Python 2.7. It is being maintained only to provide a good reference baseline for benchmarking other similarity search tools.
The commercial track, currently chemfp 3.4, includes faster performance, many new features, and support for Python 3.
Chemfp is designed for the dense, 100-10,000 bit fingerprints which occur in small-molecule/pharmaceutical chemisty. The Tanimoto search algorithms are implemented in C and assembly for performance, and support both threshold and k-nearest searches using the BitBound algorithm of Swamidass and Baldi.
Fingerprint generation can be done either by extracting existing fingerprint data from an SD file or by using an existing chemistry toolkit. chemfp supports the Python libraries from Open Babel, OpenEye, and RDKit toolkits. Be aware that those vendors no longer support Python 2.7.
The main web site is https://chemfp.com/ .
Extensive documentation is at https://chemfp.readthedocs.io/ .
To cite chemfp use: Dalke, Andrew. The chemfp project. J. Cheminformatics 11, 76 (2019). https://doi.org/10.1186/s13321-019-0398-8 https://jcheminf.biomedcentral.com/articles/10.1186/s13321-019-0398-8
FAQs
Reference baseline for high-performance cheminformatics fingerprint search benchmarking
We found that chemfp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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