Association Analysis of Vascular Endothelial Growth Factor A (VEGFA) Polymorphism in Rheumatoid Arthritis using Computational Approaches

Abstract

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by joint inflammation leading to pannus formation which results in cartilage destruction promoting bone erosion. The pathological hallmark of RA includes synovial hyperplasia and synovial angiogenesis. RA is directly associated with active tissue neovascularization. Vascular endothelial Growth factor A (VEGFA), an endothelial cell-specific proangiogenic molecule is triggered by hypoxic cells. VEGFA promotes the angiogenic phenotype of RA by enhancing vascular permeability, angiogenesis, endothelial cell proliferation and migration, and its levels are upregulated in RA. The global rate of RA is approximately 0.5-1% (world-wide) whereas it accounts for more than 1.9% approximately in population of Pakistan. By keeping in consideration, the incidence rate of RA we were aimed to investigate functional and pathogenic VEGFA variants which are the leading cause of angiogenesis and to identify impact of point mutation in VEGFA’s interaction with VEGFR2 and how these polymorphisms effect the susceptibility and severity of RA. In this study we investigated the most damaging non-synonymous SNPs of VEGFA using extensive computational pipeline, that alter the structure and function of this protein. We further identified the domains of VEGFA to locate our pathogenic variants followed by mining of evolutionary conservation profile of all the variants to determine the extent of their deleterious nature in which we identified that most of the conserved variations are part of first domain (PDGF/VEGF) and few of the mutations were lying in the second domain (Heparin-Binding domain). We also investigated impact of these point mutations on the stability of VEGFA where almost all the mutations were responsible for decreasing the protein stability. We predicted the phenotypic effect of all the variants by which we concluded that all the selected damaging SNPs were buried inside the protein core. After that structural analysis was performed to determine impact of single nucleotide polymorphism on structure of VEGFA. In order to validate our structures, we constructed Ramachandran plots for native and mutants which confirmed that all of our residues are lying in allowed region, for further validation we used ERRAT which predicted overall quality factor which was more than 95% for all models confirming the validity of our models. The prediction of protein-protein interaction showed interaction of VEGFA with other proteins, where the interaction score of VEGFA was highest with FLT1, FLT4, KDR, NRP1 AND NRP2. Based on the interactions we performed Protein-Protein docking between VEGFA and KDR which encodes VEGFR2. We found few conserved interactions and number of new polar contacts among wild type and mutants with VEGFR2. From the simulations, we concluded that mutant R108Q was the most stabilizing mutant among all others whereas R82Q, C86Y, and R108W complexed with VEGFR2 were comparatively less stabilizing as compared to the wild type. By the end of this research, we obtained five highly pathogenic nsSNPs of VEGFA among them R108Q was the most stable in complexed with VEGFR2. This study provides insight into pathogenic nsSNPs that can affect VEGFA protein structure and function. These high-risk variants must be taken into consideration for genetic screening of patients suffering from RA.