Faculty of Medicine, University of Nis, Clinical Center Nis, Clinic for Anesthesiology and Intensive Care, Nis, Serbia.
Faculty of Medicine, University of Nis, Clinical Center Nis, Clinic for Cardiovascular Disease, Nis, Serbia.
Comput Biol Med. 2021 May;132:104346. doi: 10.1016/j.compbiomed.2021.104346. Epub 2021 Mar 19.
The voltage-gated sodium channel Nav1.7 can be considered as a promising target for the treatment of pain. This research presents conformational-independent and 3D field-based QSAR modeling for a series of aryl sulfonamide acting as Nav1.7 inhibitors. As descriptors used for building conformation-independent QSAR models, SMILES notation and local invariants of the molecular graph were used with the Monte Carlo optimization method as a model developer. Different statistical methods, including the index of ideality of correlation, were used to test the quality of the developed models, robustness and predictability and obtained results were good. Obtained results indicate that there is a very good correlation between 3D QSAR and conformation-independent models. Molecular fragments that account for the increase/decrease of a studied activity were defined and used for the computer-aided design of new compounds as potential analgesics. The final evaluation of the developed QSAR models and designed inhibitors were carried out using molecular docking studies, bringing to light an excellent correlation with the QSAR modeling results.
电压门控钠离子通道 Nav1.7 可以被认为是治疗疼痛的一个有前途的靶点。本研究提出了一种构象无关的和基于 3D 场的 QSAR 建模方法，用于研究一系列作为 Nav1.7 抑制剂的芳基磺酰胺。为了构建构象无关的 QSAR 模型，使用了 SMILES 符号和分子图的局部不变量作为描述符，并采用蒙特卡罗优化方法作为模型开发者。采用了不同的统计方法，包括相关理想指数，来测试所开发模型的质量、稳健性和可预测性，得到的结果是良好的。结果表明，3D QSAR 和构象无关模型之间存在很好的相关性。定义了导致研究活性增加/减少的分子片段，并用于设计新的化合物作为潜在的镇痛药的计算机辅助设计。通过分子对接研究对所开发的 QSAR 模型和设计抑制剂进行了最终评估，结果表明与 QSAR 建模结果具有极好的相关性。
