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使用基于计算的方法筛选针对内皮素-1 的药物候选物以治疗高血压:分子对接和动力学模拟。

Screening of drug candidates against Endothelin-1 to treat hypertension using computational based approaches: Molecular docking and dynamics simulation.

机构信息

Department of Bioinformatics & Biotechnology, Government College University Faisalabad-Pakistan, Faisalabad, Pakistan.

University of Sargodha Faculty of Medical and Health Sciences Department of Biotechnology, Virtual University of Pakistan, Lahore, Pakistan.

出版信息

PLoS One. 2022 Aug 18;17(8):e0269739. doi: 10.1371/journal.pone.0269739. eCollection 2022.

Abstract

Hypertension (HTN) is a major risk factor for cardiovascular and renal diseases, cerebrovascular accidents (CVA) and a prime underlying cause of worldwide morbidity and mortality. Hypertension is a complex condition and a strong interplay of multiple genetic, epigenetic and environmental factors is involved in its etiology. Previous studies showed an association of overexpression of genes with hypertension. Satisfactory control of Blood Pressure (BP) levels is not achieved in a major portion of hypertensive patients who take antihypertensive drugs. Since existing antihypertensive drugs have many severe or irreversible side effects and give rise to further complications like frequent micturition and headaches, dizziness, dry irritating cough, hypoglycemia, GI hemorrhage, impaired left ventricular function, hyperkalemia, Anemia, angioedema and azotemia. There is a need to identify new antihypertensive agents that can inhibit the expression of these overexpressed genes contributing to hypertension. The study was designed to identify drug-able targets against overexpressed genes involved in hypertension to intervene the disease. The structure of the protein encoded by an overexpressed gene Endothelin-1 was retrieved from Protein Database (PDB). A library of five thousand phytochemicals was docked against Endothelin-1. The top four hits against Endothelin-1 protein were selected based on S score and Root Mean Square Deviation (RMSD). S score is a molecular docking score which is used to determine the preferred orientation, binding mode, site of the ligand and binding affinity. RMSD refines value for drug target identification. Absorption, distribution, metabolism, excretion, and toxicity profiling (ADMET) was done. The study provides novel insights into HTN etiology and improves our understanding of BP pathophysiology. These findings help to understand the impact of gene expression on BP regulation. This study might be helpful to develop an antihypertensive drug with a better therapeutic profile and least side effects.

摘要

高血压(HTN)是心血管和肾脏疾病、脑血管意外(CVA)的主要危险因素,也是全球发病率和死亡率的主要潜在原因。高血压是一种复杂的疾病,涉及多种遗传、表观遗传和环境因素的强烈相互作用。先前的研究表明,基因的过度表达与高血压有关。接受抗高血压药物治疗的高血压患者中,大部分未能达到满意的血压(BP)控制水平。由于现有降压药物有许多严重或不可逆转的副作用,并导致进一步的并发症,如频繁排尿、头痛、头晕、干咳、低血糖、胃肠道出血、左心室功能障碍、高钾血症、贫血、血管性水肿和氮质血症。因此,需要识别新的降压药物,以抑制导致高血压的这些过度表达基因的表达。本研究旨在确定针对参与高血压的过度表达基因的药物靶点,以干预该疾病。从蛋白质数据库(PDB)中检索出编码过度表达基因内皮素-1的蛋白质的结构。对 5000 种植物化学物质进行了对接。根据 S 评分和均方根偏差(RMSD),选择了对内皮素-1 蛋白的前四个命中物。S 评分是一种分子对接评分,用于确定配体的首选取向、结合模式、位置和结合亲和力。RMSD 则是用于药物靶点识别的细化值。进行了吸收、分布、代谢、排泄和毒性分析(ADMET)。该研究为 HTN 病因提供了新的见解,并提高了我们对 BP 病理生理学的理解。这些发现有助于了解基因表达对 BP 调节的影响。这项研究可能有助于开发具有更好治疗效果和最小副作用的降压药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08b0/9387841/fb116e90dc88/pone.0269739.g001.jpg

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