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

Andrew DalkeJérôme HertChristian Kramer
Published in: Journal of chemical information and modeling (2018)
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 .
Keyphrases
  • high throughput
  • electronic health record
  • machine learning
  • big data
  • deep learning
  • single molecule
  • data analysis