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Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus

Proceedings of the National Academy of Sciences - PNAS, 2014-03, Vol.111 (11), p.4067-4072 [Peer Reviewed Journal]

copyright © 1993—2008 National Academy of Sciences of the United States of America ;Copyright National Academy of Sciences Mar 18, 2014 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1320001111 ;PMID: 24591595

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  • Title:
    Identifying the macromolecular targets of de novo-designed chemical entities through self-organizing map consensus
  • Author: Reker, Daniel ; Rodrigues, Tiago ; Schneider, Petra ; Schneider, Gisbert
  • Subjects: Artificial Intelligence ; Biological Sciences ; Chemical compounds ; Chemical Engineering - methods ; Chemicals ; Drug design ; Drug discovery ; Drug Discovery - methods ; Drug Repositioning - methods ; Ligands ; Macromolecular Substances - chemistry ; Modeling ; Molecules ; P values ; Pharmacology ; Physical Sciences ; Polypharmacology ; Receptors ; Side effects ; Software ; Spiders
  • Is Part Of: Proceedings of the National Academy of Sciences - PNAS, 2014-03, Vol.111 (11), p.4067-4072
  • Description: De novo molecular design and in silico prediction of polypharmacological profiles are emerging research topics that will profoundly affect the future of drug discovery and chemical biology. The goal is to identify the macromolecular targets of new chemical agents. Although several computational tools for predicting such targets are publicly available, none of these methods was explicitly designed to predict target engagement by de novo-designed molecules. Here we present the development and practical application of a unique technique, self-organizing map—based prediction of drug equivalence relationships (SPiDER), that merges the concepts of self-organizing maps, consensus scoring, and statistical analysis to successfully identify targets for both known drugs and computer-generated molecular scaffolds. We discovered a potential off-target liability of fenofibraterelated compounds, and in a comprehensive prospective application, we identified a multitarget-modulating profile of de novo designed molecules. These results demonstrate that SPiDER may be used to identify innovative compounds in chemical biology and in the early stages of drug discovery, and help investigate the potential side effects of drugs and their repurposing options.
  • Publisher: United States: National Academy of Sciences
  • Language: English
  • Identifier: ISSN: 0027-8424
    EISSN: 1091-6490
    DOI: 10.1073/pnas.1320001111
    PMID: 24591595
  • Source: GFMER Free Medical Journals
    MEDLINE
    PubMed Central
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