Prachayasittikul Veda, Pingaew Ratchanok, Anuwongcharoen Nuttapat, Worachartcheewan Apilak, Nantasenamat Chanin, Prachayasittikul Supaluk, Ruchirawat Somsak, Prachayasittikul Virapong
Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand ; Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
Department of Chemistry, Faculty of Science, Srinakharinwirot University, Bangkok, 10110 Thailand.
Springerplus. 2015 Oct 5;4:571. doi: 10.1186/s40064-015-1352-5. eCollection 2015.
Considerable attention has been given on the search for novel anticancer drugs with respect to the disease sequelae on human health and well-being. Triazole is considered to be an attractive scaffold possessing diverse biological activities. Structural modification on the privileged structures is noted as an effective strategy towards successful design and development of novel drugs. The quantitative structure-activity relationships (QSAR) is well-known as a powerful computational tool to facilitate the discovery of potential compounds. In this study, a series of thirty-two 1,2,3-triazole derivatives (1-32) together with their experimentally measured cytotoxic activities against four cancer cell lines i.e., HuCCA-1, HepG2, A549 and MOLT-3 were used for QSAR analysis. Four QSAR models were successfully constructed with acceptable predictive performance affording R CV ranging from 0.5958 to 0.8957 and RMSECV ranging from 0.2070 to 0.4526. An additional set of 64 structurally modified triazole compounds (1A-1R, 2A-2R, 7A-7R and 8A-8R) were constructed in silico and their predicted cytotoxic activities were obtained using the constructed QSAR models. The study suggested crucial moieties and certain properties essential for potent anticancer activity and highlighted a series of promising compounds (21, 28, 32, 1P, 8G, 8N and 8Q) for further development as novel triazole-based anticancer agents.
鉴于癌症后遗症对人类健康和福祉的影响，人们对新型抗癌药物的研发给予了相当多的关注。三唑被认为是一种具有多种生物活性的有吸引力的骨架结构。对这些优势结构进行结构修饰是成功设计和开发新型药物的有效策略。定量构效关系（QSAR）是一种强大的计算工具，有助于发现潜在的化合物。在本研究中，一系列32种1,2,3 - 三唑衍生物（1 - 32）及其针对四种癌细胞系（即HuCCA - 1、HepG2、A549和MOLT - 3）的实验测量细胞毒性活性被用于QSAR分析。成功构建了四个QSAR模型，其预测性能良好，交叉验证相关系数（R CV）范围为0.5958至0.8957，交叉验证均方根误差（RMSECV）范围为0.2070至0.4526。另外在计算机上构建了一组64种结构修饰的三唑化合物（1A - 1R、2A - 2R、7A - 7R和8A - 8R），并使用构建的QSAR模型获得了它们的预测细胞毒性活性。该研究表明了对强效抗癌活性至关重要的关键部分和某些性质，并突出了一系列有前景的化合物（21、28、32、1P、8G、8N和8Q），可作为新型三唑类抗癌药物进一步开发。
