Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

Fabian Mayr; Gabriele Möller; Ulrike Garscha; Jana Fischer; Patricia Rodríguez Castano; Silvia G. Inderbinen; Veronika Temml; Birgit Waltenberger; Stefan Schwaiger; Rolf W Hartmann; Christian Gege; Stefan Martens; Alex Odermatt; Amit V Pandey; Oliver Werz; Jerzy Adamski; Hermann Stuppner; Daniela Schuster

doi:10.20944/preprints202007.0495.v1

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preprints.org > chemistry and materials science > medicinal chemistry > doi: 10.20944/preprints202007.0495.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

Patricia Rodríguez Castano

Version 1 : Received: 20 July 2020 / Approved: 21 July 2020 / Online: 21 July 2020 (13:43:40 CEST)

A peer-reviewed article of this Preprint also exists.

Mayr, F., Möller, G., Garscha, U., Fischer, J., Rodríguez Castaño, P., Inderbinen, S. G., ... & Schuster, D. (2020). Finding new molecular targets of familiar natural products using in silico target prediction. International journal of molecular sciences, 21(19), 7102. Mayr, F., Möller, G., Garscha, U., Fischer, J., Rodríguez Castaño, P., Inderbinen, S. G., ... & Schuster, D. (2020). Finding new molecular targets of familiar natural products using in silico target prediction. International journal of molecular sciences, 21(19), 7102.

Abstract

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for large scale target prediction of natural products are still rare. We have developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs) – a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β- hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target prediction and guidance on using the respective tools.

Keywords

In silico target prediction; dihydrochalcones; SEA; SwissTargetPrediction; SuperPred; polyphamracology; virtual screening

Subject

Chemistry and Materials Science, Medicinal Chemistry

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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