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279Val→Phe Polymorphism of lipoprotein-associated phospholipase A2 resulted in changes of folding kinetics and recognition to substrate

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction PLA2G7 encodes Lp-PLA2 having role in the formation of atherosclerotic plaques by catalyzing its substrate, phosphatydilcholine (PC), to be pro-inflammatory substances. The increased risk for coronary artery disease (CAD) in Asian population has been related with this enzyme. 279Val→Phe variant was reported to have a protective role against CAD due to, in part, secretion defect or loss of enzymatic function. Therefore, We study folding kinetics and enzyme-substrate interaction in 279Val→Phe by using clinical and computational biology approach. Methods Polymorphisms were detected by genotyping among 103 acute myocardial infarction patients and 37 controls. Folding Lp-PLA2 was simulated using GROMACS software by assessing helicity, hydrogen bond formation and stability. The interactions of Lp-PLA2 and its substrate were simulated using Pyrx software followed by molecular dynamics simulation using YASARA software. Result Polymorphism of 279Val→Phe was represented by the change of nucleotide from G to T of 994th PLA2G7 gene. The folding simulation suggested a decreased percentage of α-helix, hydrogen bond formation, hydrogen bond stability and hydrophobicity in 279Val→Phe. The PC did not interact with active site of 279Val→Phe as paradoxically observed in 279 valine. 279Val→Phe polymorphism is likely to cause unstable binding to the substrate and decrease the enzymatic activity as observed in molecular dynamics simulations. The results of our computational biology study supported a protected effect of 279Val→Phe Polymorphism showed by the odd ratio for MI of 0.22 (CI 95% 0.035-1.37) in this study. Conclusion 279Val→Phe Polymorphism of Lp-PLA2 may lead to decrease the enzymatic activity via changes of folding kinetics and recognition to its substrate.

Original languageEnglish
Pages (from-to)199-207
Number of pages9
JournalComputational Biology and Chemistry
Volume59
DOIs
Publication statusPublished - 1 Dec 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Enzymatic activity
  • Folding kinetic
  • Lp-PLA
  • Polymorphism

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