Kalani Komal, Yadav Dharmendra K, Singh Aru, Khan Feroz, Godbole M M, Srivastava S K
Medicinal Chemistry Department, CSIR-CIMAP, Lucknow-226015 (U.P), India.
Curr Top Med Chem. 2014;14(8):1005-13. doi: 10.2174/1568026614666140324121606.
As a part of our anticancer drug discovery programme, QSAR models were developed for the prediction of anticancer activities of ursolic acid derivatives against the human hepatocellular carcinoma HepG2, breast carcinoma MDA-MB-231 and the human ductal breast epithelial T47D cancer cell lines followed by wet lab semi-synthesis of virtually active derivatives, their in-vitro biological evaluation and apoptosis. The development of QSAR models was carried out by forward stepwise multiple linear regression method using a leave-one-out approach. Virtually active derivatives were semi synthesized, spectroscopically characterized and then in-vitro tested against human cancer cell lines. Active derivatives were checked via DNA fragmentation assay. The results exhibited regression coefficients (r(2)) and the cross-validation regression coefficients (rCV(2)) for the human HepG2, MDA-MB-231 and T47D cancer cell lines as .95 and .90; .92 and .87; .89 and .83 respectively showing the prediction accuracy of the models against biological activities. Computational molecular modeling is a valid modern approach, widely used in the identification of potential drug leads. The most active virtual derivatives of UA were semi- synthesized and their in-vitro and ex-vivo evaluation showed similar results with the predicted one, validating our QSAR models. Out of several active derivatives, the three UA2, UA7 and UA10 were potentially active against the above human cancer cell lines. These findings may be of immense importance in the anticancer drug development of an inexpensive and widely available natural product, ursolic acid.
作为我们抗癌药物发现计划的一部分，开发了定量构效关系（QSAR）模型，用于预测熊果酸衍生物对人肝癌HepG2细胞、乳腺癌MDA - MB - 231细胞以及人乳腺导管上皮T47D癌细胞系的抗癌活性，随后通过湿实验室半合成虚拟活性衍生物，对其进行体外生物学评估和凋亡研究。QSAR模型的开发采用向前逐步多元线性回归方法和留一法。对虚拟活性衍生物进行半合成、光谱表征，然后针对人癌细胞系进行体外测试。通过DNA片段化分析检查活性衍生物。结果显示，针对人HepG2、MDA - MB - 231和T47D癌细胞系的回归系数（r(2)）和交叉验证回归系数（rCV(2)）分别为0.95和0.90；0.92和0.87；0.89和0.83，表明模型对生物活性的预测准确性。计算分子建模是一种有效的现代方法，广泛应用于潜在药物先导物的识别。熊果酸最具活性的虚拟衍生物被半合成，其体外和体内评估结果与预测结果相似，验证了我们的QSAR模型。在几种活性衍生物中，UA2、UA7和UA10对上述人癌细胞系具有潜在活性。这些发现对于一种廉价且广泛可得的天然产物熊果酸的抗癌药物开发可能具有极其重要的意义。
