Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets
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Nathalie Lagarde1,2, Julien Rey1,2, Aram Gyulkhandanyan1,2, Pierre Tufféry1,2, Maria A. Miteva1,2 and Bruno O. Villoutreix1,2
1Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France
2INSERM, U973, Paris, France
Bruno O. Villoutreix, email: [email protected]
Keywords: virtual screening; docking; purchasable approved drugs; repositioning; cancer
Received: June 23, 2018 Accepted: July 31, 2018 Published: August 17, 2018
Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery. We developed three compounds libraries of purchasable compounds: Drugs-lib, FOOD-lib and NP-lib that contain approved drugs, food constituents and natural products, respectively, that are optimized for structure-based virtual screening studies. The three compounds libraries are implemented in the MTiOpenScreen web server that allows users to perform structure-based virtual screening computations on their selected protein targets. The server outputs a list of 1,500 molecules with predicted binding scores that can then be processed further by the users and purchased for experimental validation. To illustrate the potential of our service for drug repositioning endeavours, we selected five recently published drugs that have been repositioned in vitro and/or in vivo on cancer targets. For each drug, we used the MTiOpenScreen service to screen the Drugs-lib collection against the corresponding anti-cancer target and we show that our protocol is able to rank these drugs within the top ranked compounds. This web server should assist the discovery of promising molecules that could benefit patients, with faster development times, and reduced costs and risk.
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