The structure-antituberculosis activity relationships study in a series of 5-aryl-2-thio-1,3,4-oxadiazole derivatives.
The structure-antituberculosis activity relationships study in a series of 5-aryl-2-thio-1,3,4-oxadiazole derivatives.
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一系列5-芳基-2-硫代-1,3,4-恶二唑衍生物的结构-抗结核活性关系研究。
DOI：
10.1016/j.bmc.2011.09.038
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发表时间：
2011
影响因子：
3.5
通讯作者：
Reynolds,Robert
中科院分区：
文献类型：
--
作者：
Macaev,Fliur;Ribkovskaia,Zinaida;Pogrebnoi,Serghei;Boldescu,Veaceslav;Rusu,Ghenadie;Shvets,Nathaly;Dimoglo,Anatholy;Geronikaki,Athina;Reynolds,Robert
对82个5-芳基-2-硫代-1，3，4-恶二唑衍生物进行了抗结核分枝杆菌H37 Rv活性筛选。合成的化合物30-37似乎是最具活性的衍生物，在12.5μg/mL下表现出超过90%的分枝杆菌生长抑制。采用电子拓扑方法结合神经网络（ETM-NN）对化合物进行构效关系研究。作为训练关联神经网络（ASNN）的结果，开发了用于抗分枝杆菌活性预测的系统，所述关联神经网络具有从Kohonen的自组织映射（SOM）的元素上发现的化合物和每个药效片段的投影计算的权重。通过对所研究的所有化合物的详细分析，已经制定了具有抗结核活性的化合物的必要要求。分析表明，对分子的任何要求的违反意味着其活性的显著降低甚至完全丧失。化合物的分子对接研究允许阐明这些新型抗分枝杆菌抑制剂的结合模式。
A series of 82 5-aryl-2-thio-1,3,4-oxadiazole derivatives were screened for their anti-mycobacterial activities against Mycobacterium tuberculosis H37Rv. The synthesized compounds 30–37 appeared to be the most active derivatives exhibiting more than 90% inhibition of mycobacterial growth at 12.5μg/mL. Structure–activity relationships study was performed for the given series by using the electronic-topological method combined with neural networks (ETM–NN). A system for the anti-mycobacterial activity prediction was developed as the result of training associative neural network (ASNN) with weights calculated from projections of a compound and each pharmacophoric fragment found on the elements of the Kohonen’s self-organizing maps (SOMs). From the detailed analysis of all compounds under study, the necessary requirements for a compound to possess antituberculosis activity have been formulated. The analysis has shown that any requirement’s violation for a molecule implies a considerable decrease or even complete loss of its activity. Molecular docking studies of the compounds allowed shedding light on the binding mode of these novel anti-mycobacterial inhibitors.