Matrix-based Molecular Descriptors for Prospective Virtual Compound Screening

Francesca Grisoni, Daniel Reker, Petra Schneider, Lukas Friedrich, Viviana Consonni, Roberto Todeschini, Andreas Koeberle, Oliver Werz, Gisbert Schneider

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)

Abstract

Molecular descriptors capture diverse structural information of molecules and are a prerequisite for ligand-based similarity searching. In this study, we introduce topological matrix-based descriptors to virtual screening for hit discovery. We evaluated the usefulness of matrix-based descriptors in a retrospective setting and compared them with topological pharmacophore descriptors. Special attention was given to the influence of data pre-processing and the applied similarity metric on the virtual screening performance. Overall, the MB descriptors showed a competitive and complementary performance to other descriptors. A prospective screen of a commercial compound library led to the discovery of a novel natural-product-derived cyclooxygenase-2 inhibitor predicted to interact differently with the target protein compared to the query compound ibuprofen. The results of our study motivate the use of matrix-based descriptors for molecular similarity-based virtual screening and scaffold hopping.

Original languageEnglish
Article number1600091
JournalMolecular Informatics
Volume36
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

Keywords

  • cheminformatics
  • cyclooxygenase
  • drug discovery
  • molecular similarity
  • natural product

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