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

Journal of Chemical Information and Modeling
Andrew DalkeChristian Kramer

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 .

Citations

Dec 10, 2020·Journal of Cheminformatics·Thomas BlaschkeHongming Chen
Jan 9, 2021·Briefings in Bioinformatics·Li FuDong-Sheng Cao
Jan 13, 2021·Journal of Cheminformatics·Pavel Polishchuk
Feb 2, 2021·Journal of Chemical Information and Modeling·Mahendra AwaleChristian Kramer
May 7, 2020·Journal of Chemical Information and Modeling·Franziska KrugerNikolaus Stiefl
Mar 22, 2021·Journal of Cheminformatics·Jiazhen HeOla Engkvist
Jul 13, 2021·Journal of Chemical Information and Modeling·Xiaolin PanChangge Ji
Sep 12, 2019·Journal of Chemical Information and Modeling·Christian Kramer
Nov 28, 2020·Journal of Chemical Information and Modeling·Hans MatterGerhard Hessler
May 6, 2020·Journal of Chemical Information and Modeling·Mahendra AwaleChristian Kramer
Feb 27, 2020·Journal of Medicinal Chemistry·Steven L RohallMika Lindvall
Jan 16, 2020·ACS Medicinal Chemistry Letters·Matthew L Landry, James J Crawford
Sep 26, 2020·Journal of Chemical Information and Modeling·James A LumleyHongzhou Zhang
Aug 28, 2021·International Journal of Molecular Sciences·Shi-Ping PengYi Zhao
Dec 8, 2021·Bioinformatics·Yang FanTao Qin

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