Worachartcheewan Apilak, Suvannang Naravut, Prachayasittikul Supaluk, Prachayasittikul Virapong, Nantasenamat Chanin
Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
EXCLI J. 2014 Dec 8;13:1259-74. eCollection 2014.
This study investigated the quantitative structure-activity relationship (QSAR) of imidazole derivatives of 4,7-disubstituted coumarins as inhibitors of aromatase, a potential therapeutic protein target for the treatment of breast cancer. Herein, a series of 3,7- and 4,7-disubstituted coumarin derivatives (1-34) with R1 and R2 substituents bearing aromatase inhibitory activity were modeled as a function of molecular and quantum chemical descriptors derived from low-energy conformer geometrically optimized at B3LYP/6-31G(d) level of theory. Insights on origins of aromatase inhibitory activity was afforded by the computed set of 7 descriptors comprising of F10[N-O], Inflammat-50, Psychotic-80, H-047, BELe1, B10[C-O] and MAXDP. Such significant descriptors were used for QSAR model construction and results indicated that model 4 afforded the best statistical performance. Good predictive performance were achieved as verified from the internal (comprising the training and the leave-one-out cross-validation (LOO-CV) sets) and external sets affording the following statistical parameters: R (2) Tr = 0.9576 and RMSETr = 0.0958 for the training set; Q (2) CV = 0.9239 and RMSECV = 0.1304 for the LOO-CV set as well as Q (2) Ext = 0.7268 and RMSEExt = 0.2927 for the external set. Significant descriptors showed correlation with functional substituents, particularly, R1 in governing high potency as aromatase inhibitor. Molecular docking calculations suggest that key residues interacting with the coumarins were predominantly lipophilic or non-polar while a few were polar and positively-charged. Findings illuminated herein serve as the impetus that can be used to rationally guide the design of new aromatase inhibitors.
本研究调查了4,7-二取代香豆素的咪唑衍生物作为芳香酶抑制剂的定量构效关系(QSAR),芳香酶是治疗乳腺癌的一个潜在治疗性蛋白质靶点。在此,一系列具有R1和R2取代基且具有芳香酶抑制活性的3,7-和4,7-二取代香豆素衍生物(1-34)被建模为分子和量子化学描述符的函数,这些描述符源自于在B3LYP/6-31G(d)理论水平上进行几何优化的低能量构象体。通过计算得到的一组7个描述符(包括F10[N-O]、Inflammat-50、Psychotic-80、H-047、BELe1、B10[C-O]和MAXDP),对芳香酶抑制活性的起源有了深入了解。这些重要的描述符被用于构建QSAR模型,结果表明模型4具有最佳的统计性能。从内部(包括训练集和留一法交叉验证(LOO-CV)集)和外部集验证获得了良好的预测性能,给出了以下统计参数:训练集的R(2)Tr = 0.9576和RMSETr = 0.0958;LOO-CV集的Q(2)CV = 0.9239和RMSECV = 0.1304;外部集的Q(2)Ext = 0.7268和RMSEExt = 0.2927。重要描述符显示出与功能取代基相关,特别是R1在决定作为芳香酶抑制剂的高效力方面。分子对接计算表明,与香豆素相互作用的关键残基主要是亲脂性或非极性的,而少数是极性和带正电荷的。本文阐述的研究结果可作为合理指导新型芳香酶抑制剂设计的推动力。