Preprint Article Version 1 This version is not peer-reviewed

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

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

How to cite: Mayr, F.; Möller, G.; Garscha, U.; Fischer, J.; Rodríguez Castano, P.; Inderbinen, S.G.; Temml, V.; Waltenberger, B.; Schwaiger, S.; Hartmann, R.W.; Gege, C.; Martens, S.; Odermatt, A.; Pandey, A.V.; Werz, O.; Adamski, J.; Stuppner, H.; Schuster, D. Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction. Preprints 2020, 2020070495 (doi: 10.20944/preprints202007.0495.v1). Mayr, F.; Möller, G.; Garscha, U.; Fischer, J.; Rodríguez Castano, P.; Inderbinen, S.G.; Temml, V.; Waltenberger, B.; Schwaiger, S.; Hartmann, R.W.; Gege, C.; Martens, S.; Odermatt, A.; Pandey, A.V.; Werz, O.; Adamski, J.; Stuppner, H.; Schuster, D. Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction. Preprints 2020, 2020070495 (doi: 10.20944/preprints202007.0495.v1).

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.

Subject Areas

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

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