Title:Computational and Pharmacogenomic Insights on Hypertension Treatment: Rational Drug Design and Optimization Strategies
Volume: 21
Issue: 1
Author(s): Lakshmanan Loganathan, Krishnasamy Gopinath, Vadivel Murugan Sankaranarayanan, Ritushree Kukreti, Kannan Rajendran, Jung-Kul Lee*Karthikeyan Muthusamy*
Affiliation:
- Department of Chemical Engineering, Konkuk University, 1 Hwayang-Dong, Gwangjin-Gu, Seoul,Korea
- Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu,India
Keywords:
Computational mutagenesis, drug discovery, hypertension, blood pressure, pharmacogenomics, SNPs, RAAS.
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.