The current work is focused on in silico modeling of COX-1 inhibitors with enhanced safety gastric profile. A 5-point pharmacophore model, atom-based 3D quantitative structure-activity relationship (3D-QSAR) and electronic properties were computed for a series of COX-1 inhibitors. The best pharmacophore model AAHRR.10 consisting of two hydrogen bond acceptors, one hydrophobic site, and two rings was developed to derive a predictive, statistically significant 3D-QSAR model at three partial least square factors (R2 = 0.991, SD = 0.059, F = 278.5, Q2 = 0.682, RMSE = 0.325, Pearson’s R = 0.903, Spearman’s rho = 0.872). The AAHRR.10 hypothesis was validated by enrichment studies employing a custom-made validation dataset adopting selective COX-1 inhibitors extracted from ChEMBL and decoys generated via DUD methodology. The global reactivity descriptors, such as HOMO and LUMO energies, the HOMO-LUMO gaps, global hardness, softness, Fukui indices, and electrostatic potential, were carried out using density functional theory (DFT) to confirm the key structural features required to achieve COX-1 selectivity. Well-validated AAHRR.10 hypothesis was further used as 3D query in virtual screening of the DrugBank database to detect novel potential COX-1 inhibitors. Docking algorithm was applied to enhance the pharmacophore prediction and to recommend drugs for repositioning, which can interact selectively with COX-1.

中文翻译：

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通过药效团建模、虚拟筛选和基于 DFT 的方法分析二芳基噻唑和二芳基咪唑选择性 COX-1 抑制剂

目前的工作集中在具有增强安全性胃特征的 COX-1 抑制剂的计算机模拟。计算了一系列 COX-1 抑制剂的 5 点药效团模型、基于原子的 3D 定量构效关系 (3D-QSAR) 和电子特性。开发了由两个氢键受体、一个疏水位点和两个环组成的最佳药效团模型 AAHRR.10，以在三个偏最小二乘因子 (R2 = 0.991, SD = 0.059, F = 278.5，Q2 = 0.682，RMSE = 0.325，Pearson 的 R = 0.903，Spearman 的 rho = 0.872）。AAHRR.10 假设通过使用定制验证数据集的富集研究得到验证，该数据集采用从 ChEMBL 中提取的选择性 COX-1 抑制剂和通过 DUD 方法生成的诱饵。全局反应性描述符，例如 HOMO 和 LUMO 能量、HOMO-LUMO 间隙、整体硬度、柔软度、福井指数和静电势，使用密度泛函理论 (DFT) 进行，以确认实现 COX-1 选择性所需的关键结构特征。经过充分验证的 AAHRR.10 假设进一步用作 DrugBank 数据库虚拟筛选中的 3D 查询，以检测新的潜在 COX-1 抑制剂。对接算法用于增强药效团预测并推荐重新定位的药物，这些药物可以选择性地与COX-1相互作用。10 假设进一步用作 DrugBank 数据库虚拟筛选中的 3D 查询，以检测新的潜在 COX-1 抑制剂。对接算法用于增强药效团预测并推荐重新定位的药物，这些药物可以选择性地与COX-1相互作用。10 假设进一步用作 DrugBank 数据库虚拟筛选中的 3D 查询，以检测新的潜在 COX-1 抑制剂。对接算法用于增强药效团预测并推荐重新定位的药物，这些药物可以选择性地与COX-1相互作用。