Pratiwi Reny, Prachayasittikul Veda, Prachayasittikul Supaluk, Nantasenamat Chanin
Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
Department of Medical Laboratory Technology, Faculty of Health Sciences, Setia Budi University, Surakarta 57127, Indonesia.
EXCLI J. 2019 Apr 5;18:207-222. doi: 10.17179/excli2019-1274. eCollection 2019.
Sirtuin 1 (SIRT1) enzyme regulates major cell activities, and its activation offers lucrative therapeutic potentials for aging diseases including Alzheimer's disease (AD). Regarding the global aging society, continual attention has been given to various chemical scaffolds as a source for the discovery of novel SIRT1 activators since the discovery of the pioneer activator, resveratrol. Understanding structure-activity relationship (SAR) is essential for screening, designing as well as improving the properties of drugs. In this study, an approach based on quantitative structure-activity relationship (QSAR) modeling, was employed for understanding the SAR of currently available SIRT1 fused-aromatic activators (i.e., imidazothiazole, oxazolopyridine, and azabenzimidazole analogs). Three QSAR models constructed using multiple linear regression (MLR) provided good predictive performance ( = 0.729 - 0.863 and RMSE = 0.165 - 0.325). An additional novel set of 181 structurally modified compounds were rationally designed according to key descriptors deduced from the QSAR findings and their SIRT1 activities were predicted using the constructed models. In overview, the study provides insightful SAR findings of currently available SIRT1 activators that would be useful for guiding the rational design, screening, and development of further potent SIRT1 activators for managing age-related clinical conditions. A series of promising compounds as well as important scaffolds and molecular properties for potent SIRT1 activator were highlighted. This study demonstrated the efficacious role of QSAR-driven structural modification for the rational design of novel leads.
沉默调节蛋白1（SIRT1）酶调节主要的细胞活动，其激活为包括阿尔茨海默病（AD）在内的衰老相关疾病提供了诱人的治疗潜力。鉴于全球老龄化社会，自首个激活剂白藜芦醇被发现以来，人们持续关注各种化学骨架作为新型SIRT1激活剂的来源。理解构效关系（SAR）对于药物的筛选、设计以及性质改善至关重要。在本研究中，采用了一种基于定量构效关系（QSAR）建模的方法来理解目前可用的SIRT1稠合芳香族激活剂（即咪唑并噻唑、恶唑并吡啶和氮杂苯并咪唑类似物）的SAR。使用多元线性回归（MLR）构建的三个QSAR模型具有良好的预测性能（R² = 0.729 - 0.863，RMSE = 0.165 - 0.325）。根据QSAR研究结果推导的关键描述符合理设计了另外一组181种结构修饰化合物，并使用构建的模型预测了它们的SIRT1活性。总体而言，该研究提供了目前可用的SIRT1激活剂的有洞察力的SAR研究结果，这将有助于指导合理设计、筛选和开发用于管理与年龄相关临床病症的更有效的SIRT1激活剂。强调了一系列有前景的化合物以及强效SIRT1激活剂的重要骨架和分子性质。本研究证明了QSAR驱动的结构修饰在新型先导化合物合理设计中的有效作用。
