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ChemMedChem. 2018 Mar 20;13(6):540-554. doi: 10.1002/cmdc.201700561. Epub 2018 Jan 29.

Mapping of the Available Chemical Space versus the Chemical Universe of Lead-Like Compounds.

Author information

1
Laboratory of Chemoinformatics, Faculty of Chemistry, University of Strasbourg, 4 Blaise Pascal str., 67081, Strasbourg, France.
2
Laboratory of Chemoinformatics and Molecular Modeling, Department of Organic Chemistry, A.M. Butlerov Institute of Chemistry, Kazan Federal University, 18 Kremlyovskaya str., 420008, Kazan, Russia.
3
Department of Chemistry and Biochemistry, University of Berne, 3 Freiestrasse, 3012, Berne, Switzerland.

Abstract

This is, to our knowledge, the most comprehensive analysis to date based on generative topographic mapping (GTM) of fragment-like chemical space (40 million molecules with no more than 17 heavy atoms, both from the theoretically enumerated GDB-17 and real-world PubChem/ChEMBL databases). The challenge was to prove that a robust map of fragment-like chemical space can actually be built, in spite of a limited (≪105 ) maximal number of compounds ("frame set") usable for fitting the GTM manifold. An evolutionary map building strategy has been updated with a "coverage check" step, which discards manifolds failing to accommodate compounds outside the frame set. The evolved map has a good propensity to separate actives from inactives for more than 20 external structure-activity sets. It was proven to properly accommodate the entire collection of 40 m compounds. Next, it served as a library comparison tool to highlight biases of real-world molecules (PubChem and ChEMBL) versus the universe of all possible species represented by FDB-17, a fragment-like subset of GDB-17 containing 10 million molecules. Specific patterns, proper to some libraries and absent from others (diversity holes), were highlighted.

KEYWORDS:

computer chemistry; generative topographic mapping; library comparison; molecular diversity; structure analysis

PMID:
29154440
DOI:
10.1002/cmdc.201700561

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