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

Citation

Rebollo-Lopez, Maria Jose et al. (2016), Data from: Release of 50 new, drug-like compounds and their computational target predictions for open source anti-tubercular drug discovery, Dryad, Dataset, https://doi.org/10.5061/dryad.8r351

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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