a Institute for Cardiovascular Rehabilitation, Faculty of Medicine , University of Nis , Niska Banja , Serbia.
b Center for Anesthesiology and Reanimatology , Clinical Center Niš , Niš , Serbia.
SAR QSAR Environ Res. 2018 Jul;29(7):503-515. doi: 10.1080/1062936X.2018.1485737.
Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure-activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.
血管紧张素转换酶（ACE）抑制剂已被公认为治疗高血压和多种心血管疾病的一线药物。在这种情况下，基于简化分子输入线系统（SMILES）符号和局部图不变量，为一系列非肽化合物作为 ACE 抑制剂开发了定量构效关系（QSAR）模型。使用三个随机拆分到训练集和测试集中。应用蒙特卡罗方法进行模型开发。分子对接研究用于最终评估所开发的 QSAR 模型和新型抑制剂的设计。所开发模型的统计质量良好。计算了负责研究活性增加/减少的分子片段。提出了作为潜在 ACE 抑制剂的新化合物的计算机辅助设计。使用不同的方法测试了所应用方法的预测潜力，并证明了模型的稳健性。分子对接研究的结果与 QSAR 研究的结果非常吻合。本研究可能有助于基于 ACE 抑制作用寻找新型心血管治疗药物。
