Release of 50 new, drug-like compounds and their computational target predictions for open source anti-tubercular drug discovery

发布 50 种新型类药物化合物及其计算靶标预测,用于开源抗结核药物发现

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作者:María Jose Rebollo-Lopez, Joël Lelièvre, Daniel Alvarez-Gomez, Julia Castro-Pichel, Francisco Martínez-Jiménez, George Papadatos, Vinod Kumar, Gonzalo Colmenarejo, Grace Mugumbate, Mark Hurle, Vanessa Barroso, Rob J Young, María Martinez-Hoyos, Rubén González del Río, Robert H Bates, Eva Maria Lopez

Abstract

As a follow up to the antimycobacterial screening exercise and the release of GSK´s first Tres Cantos Antimycobacterial Set (TCAMS-TB), this paper presents the results of a second antitubercular screening effort of two hundred and fifty thousand compounds recently added to the GSK collection. The compounds were further prioritized based on not only antitubercular potency but also on physicochemical characteristics. The 50 most attractive compounds were then progressed for evaluation in three different predictive computational biology algorithms based on structural similarity or GSK historical biological assay data in order to determine their possible mechanisms of action. This effort has resulted in the identification of novel compounds and their hypothesized targets that will hopefully fuel future TB drug discovery and target validation programs alike.

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