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Updated: Apr 21, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Delving Into the Depths of AGTR2: In Silico Identification of Deleterious Nonsynonymous SNPs Associated With
Muhammad Waleed Iqbal1, Muhammad Shahab1, Xinxiao Sun1
1College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China, buct.edu.cn.
Background And Aim:
Nonsynonymous single nucleotide polymorphisms (nsSNPs) in angiotensin Type II receptor (AGTR2) have been identified as a potential cause of cardiovascular illness in humans. Identifying structurally and functionally relevant alterations in AGTR2 is critical to investigate possible therapeutic targets.
Methods:
A comprehensive computational pipeline was employed to evaluate deleterious nsSNPs using multiple prediction algorithms, including SIFT, PolyPhen-2, CADD, REVEL, Mutation Assessor, MetaLR, I-Mutant, MutPred, and Phylo3D. Molecular docking and molecular dynamic simulation strategies were further utilized to thoroughly validate these nsSNPs. Additionally, gene-gene interaction networks were constructed to explore AGTR2's functional associations.
Results:
Our findings indicated that four nsSNPs, including rs200599388, rs1556673810, rs3729979, and rs1556673736, potentially have the most deleterious effect on the AGTR2 gene. MD simulations revealed that these variants induced increased structural fluctuations and conformational instability compared with the wild-type protein. Gene-gene interaction analysis indicated that AGTR2 participates in several key regulatory pathways relevant to cardiovascular physiology.
Conclusion:
These findings will form the basis to design precision medicines for cardiovascular diseases in the future and welcome further preclinical and clinical investigations.
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