Worachartcheewan Apilak, Prachayasittikul Veda, Prachayasittikul Supaluk, Tantivit Visanu, Yeeyahya Chareef, Prachayasittikul Virapong
Department of Community Medical 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.
EXCLI J. 2020 Feb 26;19:209-226. doi: 10.17179/excli2019-1903. eCollection 2020.
Coumarins are well-known for their antioxidant effect and aromatic property, thus, they are one of ingredients commonly added in cosmetics and personal care products. Quantitative structure-activity relationships (QSAR) modeling is an method widely used to facilitate rational design and structural optimization of novel drugs. Herein, QSAR modeling was used to elucidate key properties governing antioxidant activity of a series of the reported coumarin-based antioxidant agents (-). Several types of descriptors (calculated from 4 softwares i.e., Gaussian 09, Dragon, PaDEL and Mold softwares) were used to generate three multiple linear regression (MLR) models with preferable predictive performance ( = 0.813-0.908; = 0.150-0.210; = 0.875-0.952; = 0.104-0.166). QSAR analysis indicated that number of secondary amines (nArNHR), polarizability (G2p), electronegativity (D467, D580, SpMin2_Bhe, and MATS8e), van der Waals volume (D491 and D461), and H-bond potential (SHBint4) are important properties governing antioxidant activity. The constructed models were also applied to guide rational design of an additional set of 69 structurally modified coumarins with improved antioxidant activity. Finally, a set of 9 promising newly design compounds were highlighted for further development. Structure-activity analysis also revealed key features required for potent activity which would be useful for guiding the future rational design. In overview, our findings demonstrated that QSAR modeling could possibly be a facilitating tool to enhance successful development of bioactive compounds for health and cosmetic applications.
香豆素因其抗氧化作用和芳香特性而闻名,因此,它们是化妆品和个人护理产品中常用的成分之一。定量构效关系(QSAR)建模是一种广泛用于促进新药合理设计和结构优化的方法。在此,QSAR建模用于阐明一系列已报道的基于香豆素的抗氧化剂(-)的抗氧化活性的关键性质。使用几种类型的描述符(由4种软件即高斯09、Dragon、PaDEL和Mold软件计算得出)生成了三个具有较好预测性能的多元线性回归(MLR)模型( = 0.813 - 0.908; = 0.150 - 0.210; = 0.875 - 0.952; = 0.104 - 0.166)。QSAR分析表明仲胺数量(nArNHR)、极化率(G2p)、电负性(D467、D580、SpMin2_Bhe和MATS8e)、范德华体积(D491和D461)以及氢键潜力(SHBint4)是控制抗氧化活性的重要性质。构建的模型还被应用于指导另外一组69种具有改进抗氧化活性的结构修饰香豆素的合理设计。最后,突出了一组9种有前景的新设计化合物以供进一步开发。构效分析还揭示了强效活性所需的关键特征,这将有助于指导未来的合理设计。总体而言,我们的研究结果表明QSAR建模可能是一种促进生物活性化合物在健康和化妆品应用中成功开发的工具。