Association analysis of Vascular Endothelial Growth Factor-A (VEGF-A) polymorphism in rheumatoid arthritis using computational approaches

Abstract

Rheumatoid arthritis (RA), is marked 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. Active tissue neovascularization is observed in RA. Vascular endothelial Growth factor A (VEGFA), an endothelial cell-specific proangiogenic molecule is triggered by hypoxic cells and its levels are upregulated in RA. The aim of this study was to investigate functional and pathogenic VEGFA variants and to identify the impact of point mutation in VEGFA's interaction with VEGFR2 and how these polymorphisms affect the susceptibility and severity of RA. We investigated impact of these point mutations on the stability of VEGFA using various computational tools. These mutations were further identified by conservational profile as they are highly involved as structural and functional mutations. Furthermore, these selected variants were modelled and docked against targeted domain regions IGD2 and IGD3 of VEGFR2. Further molecular dynamic simulations were performed using Gromacs. Out of 168 nsSNPS, 19 were highlighted as highly pathogenic using insilico prediction tools. InterPro and ConSurf revealed domains and conserved variants respectively. After stability analysis, we concluded that almost all the mutations were responsible for decreasing the protein stability. HOPE predicted that all the selected damaging nsSNPs were present in the domain which is essential for the functioning of VEGFA protein. Constructed Ramachandran plot and ERRAT validated the quality of all the models. Based on the interactions predicted by STRING database, we performed Protein-Protein docking between VEGFA and VEGFR2. We found few conserved interactions and 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. 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.

Figure 1

(A) Flow chart representing the comparison of Normoxic and hypoxic conditions in a cell that triggers activation of VEGFA protein. (B) Flow chart representing the domains of VEGFR2. (C) Diagrammatic representation of VEGFA-VEGFR2 downstream signaling pathways ^,.

Figure 2

Flow chart showing the methodology performed for current research.

Figure 3

(A) Vertical Bar graph representing the annotation of VEGFA-206 transcript. (B) Pie chart showing percentages of mutants predicted by SIFT, Polyphen, Cadd, Revel, MetaLR, and Mutation Assessor. (C) Pie chart showing percentages of mutants predicted by PhD-SNP, Panther, Pmut, Mutpred2, SNPs &GO, and SNAP2.

Figure 4

(A) Conservation profile of VEGFA Predicted by ConSurf. (B) Cartoon structure of VEGFA (C) Surface structure of VEGFA.

Figure 5

A Super-imposed structures of wild and mutants. (A) R49C with wild. (B) V59M with wild. (C) V78M with wild. (D) R82Q with wild. (E) C86Y with wild. (F) E90K with wild. (G) R108Q with wild. (H) R108W with wild.

Figure 6

(A) Bar graph showing the quality factor of wild and all the mutants predicted by ERRAT. (B) Protein–Protein Interaction predicted by STRING database.

Figure 7

Docked complexes of Wild and Mutant VEGFA with IgD2 and IgD3 domains of VEGFR2.

Figure 8

(A) Root mean square deviation (RMSD) of all the complexes. (B) SASA graph of wild and all the mutant complexes (C) Root mean square fluctuation (RMSF) of wild-type complexed with VEGFR2, V78M complexed with VEGFR2, R82Q complexed with VEGFR2, C86Y complexed with VEGFR2, R108Q complexed with VEGFR2 and R108W complexed with VEGFR2.