Release of 50 new, drug-like compounds and their computational target predictions for open source anti-tubercular drug discovery
0301 basic medicine
Science
Q
R
Antitubercular Agents
Computational Biology
Hep G2 Cells
Mycobacterium tuberculosis
3. Good health
03 medical and health sciences
Cell Line, Tumor
Drug Design
Drug Discovery
Medicine
Humans
Biología y Biomedicina
Algorithms
Research Article
DOI:
10.1371/journal.pone.0142293
Publication Date:
2015-12-08T14:18:20Z
AUTHORS (24)
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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CITATIONS (37)
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