mmpdb: An Open-Source Matched Molecular Pair Platform for Large Multiproperty Data Sets

Andrew Dalke, Jérôme Hert, Christian Krämer

Journal of Chemical Information and Modeling · 2018 · 126 citations · 15 references

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Abstract

Matched molecular pair analysis (MMPA) enables the automated and systematic compilation of medicinal chemistry rules from compound/property data sets. Here we present mmpdb, an open-source matched molecular pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large data sets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. It is freely available from https://github.com/rdkit/mmpdb .

References

15