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计算与药物基因组学在高血压治疗中的研究进展:合理药物设计与优化策略。

Computational and Pharmacogenomic Insights on Hypertension Treatment: Rational Drug Design and Optimization Strategies.

机构信息

Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India.

Department of Chemical Engineering, Konkuk University, 1 Hwayang-Dong, Gwangjin-Gu, Seoul, Korea.

出版信息

Curr Drug Targets. 2020;21(1):18-33. doi: 10.2174/1389450120666190808101356.

Abstract

BACKGROUND

Hypertension is a prevalent cardiovascular complication caused by genetic and nongenetic factors. Blood pressure (BP) management is difficult because most patients become resistant to monotherapy soon after treatment initiation. Although many antihypertensive drugs are available, some patients do not respond to multiple drugs. Identification of personalized antihypertensive treatments is a key for better BP management.

OBJECTIVE

This review aimed to elucidate aspects of rational drug design and other methods to develop better hypertension management.

RESULTS

Among hypertension-related signaling mechanisms, the renin-angiotensin-aldosterone system is the leading genetic target for hypertension treatment. Identifying a single drug that acts on multiple targets is an emerging strategy for hypertension treatment, and could be achieved by discovering new drug targets with less mutated and highly conserved regions. Extending pharmacogenomics research to include patients with hypertension receiving multiple antihypertensive drugs could help identify the genetic markers of hypertension. However, available evidence on the role of pharmacogenomics in hypertension is limited and primarily focused on candidate genes. Studies on hypertension pharmacogenomics aim to identify the genetic causes of response variations to antihypertensive drugs. Genetic association studies have identified single nucleotide polymorphisms affecting drug responses. To understand how genetic traits alter drug responses, computational screening of mutagenesis can be utilized to observe drug response variations at the protein level, which can help identify new inhibitors and drug targets to manage hypertension.

CONCLUSION

Rational drug design facilitates the discovery and design of potent inhibitors. However, further research and clinical validation are required before novel inhibitors can be clinically used as antihypertensive therapies.

摘要

背景

高血压是一种由遗传和非遗传因素引起的常见心血管并发症。由于大多数患者在治疗开始后很快对单药治疗产生耐药性,血压(BP)管理较为困难。尽管有许多降压药物可供选择,但有些患者对多种药物没有反应。确定个性化的降压治疗方法是更好地管理 BP 的关键。

目的

本综述旨在阐明合理药物设计和其他方法,以开发更好的高血压管理方法。

结果

在与高血压相关的信号机制中,肾素-血管紧张素-醛固酮系统是高血压治疗的主要遗传靶点。发现一种作用于多个靶点的单一药物是治疗高血压的一种新兴策略,可以通过发现突变较少且高度保守的区域的新药物靶点来实现。将药物基因组学研究扩展到接受多种降压药物治疗的高血压患者,可以帮助识别高血压的遗传标志物。然而,关于药物基因组学在高血压中的作用的现有证据有限,主要集中在候选基因上。高血压药物基因组学研究旨在确定对降压药物反应变化的遗传原因。遗传关联研究已经确定了影响药物反应的单核苷酸多态性。为了了解遗传特征如何改变药物反应,可以利用诱变的计算筛选来观察药物在蛋白质水平上的反应变化,这有助于识别新的抑制剂和药物靶点来管理高血压。

结论

合理药物设计有助于发现和设计有效的抑制剂。然而,在新型抑制剂可作为抗高血压治疗方法临床应用之前,还需要进一步的研究和临床验证。

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