Department of Pharmaceutical Sciences, College of Pharmacy, Western University of Health Sciences, Pomona, California, United States of America.
PLoS Comput Biol. 2020 Nov 25;16(11):e1007719. doi: 10.1371/journal.pcbi.1007719. eCollection 2020 Nov.
Angiotensin II type 1 receptor (AT1R) blockers (ARBs) are among the most prescribed drugs. However, ARB effectiveness varies widely, which may be due to non-synonymous single nucleotide polymorphisms (nsSNPs) within the AT1R gene. The AT1R coding sequence contains over 100 nsSNPs; therefore, this study embarked on determining which nsSNPs may abrogate the binding of selective ARBs. The crystal structure of olmesartan-bound human AT1R (PDB:4ZUD) served as a template to create an inactive apo-AT1R via molecular dynamics simulation (n = 3). All simulations resulted in a water accessible ligand-binding pocket that lacked sodium ions. The model remained inactive displaying little movement in the receptor core; however, helix 8 showed considerable flexibility. A single frame representing the average stable AT1R was used as a template to dock Olmesartan via AutoDock 4.2, MOE, and AutoDock Vina to obtain predicted binding poses and mean Boltzmann weighted average affinity. The docking results did not match the known pose and affinity of Olmesartan. Thus, an optimization protocol was initiated using AutoDock 4.2 that provided more accurate poses and affinity for Olmesartan (n = 6). Atomic models of 103 of the known human AT1R polymorphisms were constructed using the molecular dynamics equilibrated apo-AT1R. Each of the eight ARBs was then docked, using ARB-optimized parameters, to each polymorphic AT1R (n = 6). Although each nsSNP has a negligible effect on the global AT1R structure, most nsSNPs drastically alter a sub-set of ARBs affinity to the AT1R. Alterations within N298 -L314 strongly effected predicted ARB affinity, which aligns with early mutagenesis studies. The current study demonstrates the potential of utilizing in silico approaches towards personalized ARB therapy. The results presented here will guide further biochemical studies and refinement of the model to increase the accuracy of the prediction of ARB resistance in order to increase overall ARB effectiveness.
血管紧张素 II 型 1 型受体（AT1R）阻滞剂（ARB）是最常被开处方的药物之一。然而，ARB 的有效性差异很大，这可能是由于 AT1R 基因内的非同义单核苷酸多态性（nsSNP）。AT1R 编码序列包含 100 多个 nsSNP；因此，本研究着手确定哪些 nsSNP 可能会阻断选择性 ARB 的结合。奥米沙坦结合的人 AT1R（PDB：4ZUD）的晶体结构被用作模板，通过分子动力学模拟创建一个无配体的apo-AT1R（n = 3）。所有模拟都导致配体结合口袋可被水进入，其中缺乏钠离子。该模型仍然是无活性的，受体核心几乎没有运动；然而，螺旋 8 显示出相当大的灵活性。选择一个代表平均稳定 AT1R 的单帧作为模板，通过 AutoDock 4.2、MOE 和 AutoDock Vina 对接奥米沙坦，以获得预测的结合构象和平均玻尔兹曼加权平均亲和力。对接结果与奥米沙坦的已知构象和亲和力不匹配。因此，使用 AutoDock 4.2 启动了一个优化方案，该方案为奥米沙坦提供了更准确的构象和亲和力（n = 6）。使用分子动力学平衡的 apo-AT1R 构建了 103 种已知的人类 AT1R 多态性的原子模型。然后，使用 ARB 优化的参数，将 8 种 ARB 中的每一种分别对接每种多态性的 AT1R（n = 6）。尽管每个 nsSNP 对全局 AT1R 结构的影响可以忽略不计，但大多数 nsSNP 会极大地改变一组 ARB 对 AT1R 的亲和力。N298-L314 内的改变强烈影响预测的 ARB 亲和力，这与早期的诱变研究一致。本研究表明，利用计算机模拟方法进行个性化 ARB 治疗的潜力。这里呈现的结果将指导进一步的生化研究和模型的改进，以提高 ARB 耐药性预测的准确性，从而提高 ARB 的整体效果。
