Release of 50 new, drug-like compounds and their computational target predictions for open source anti-tubercular drug discovery
Release of 50 new, drug-like compounds and their computational target predictions for open source anti-tubercular drug discovery
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DOI：
10.1371/journal.pone.0142293
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发表时间：
2015-12-07
期刊：
影响因子：
3.7
通讯作者：
Barros-Aguire, David
中科院分区：
文献类型：
--
作者：
Jose Rebollo-Lopez, Maria;Lelievre, Joel;Barros-Aguire, David
作为抗分枝杆菌筛选工作和GSK的第一个Tres Cantos抗分枝杆菌集（TCAMS-TB）的发布的后续行动，本文介绍了最近添加到GSK收集的25万种化合物的第二次抗结核筛选工作的结果。这些化合物不仅根据抗结核效力，而且根据理化特性进一步优先考虑。然后，基于结构相似性或GSK历史生物测定数据，在三种不同的预测计算生物学算法中对50种最有吸引力的化合物进行评价，以确定其可能的作用机制。这一努力导致了新化合物及其假设靶点的鉴定，这将有望推动未来的结核病药物发现和靶点验证计划。
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.