Affiliation:
1. Amity Institute of Biotechnology, Amity University, Kolkata, India
2. Department of Biochemistry and Biophysics, University of Kalyani, Kalyani, Nadia, India
Abstract
Background:
Integrin αV, encoded by ITGAV gene, is one of the most studied protein
subunits, closely associated with liver, pancreatic and stomach cancer progression and metastasis
via regulation of angiogenesis. The occurrence of Single Nucleotide Polymorphisms (SNPs) in cancer-
associated proteins is a key determinant for varied susceptibility of an individual towards cancer.
Methodology:
The study investigated the deleterious effects of these cancer-associated SNPs on
the protein’s structure, stability and cancer causing potential using an in silico approach. Numerous
computational tools were employed that identified the most deleterious cancer-associated SNPs
and those to get actively involved in post-translational modifications. The impact of these SNPs on
the protein structure, function and stability was also examined.
Conclusion and Future Scope:
A total 63 non-synonymous SNPs in ITGAV gene were observed
to be associated in these three gastrointestinal cancers and among this, 63, 19 were the most deleterious
ones. The structural and functional importance of residues altered by most damaging SNPs
was analyzed through evolutionary conservation and solvent accessibility. The study also elucidated
three-dimensional structures of the 19 most damaging mutants. The analysis of conformational
variation identified 5 SNPs (D379Y, G188E, G513V, L950P, and R540L) in integrin αV, which influence
the protein’s structure. Three calcium binding sites were predicted at residues: D379, G384
and G408 and a peptide binding site at residue: R369 in integrin αV. Therefore, SNPs D379Y,
G384C, G408R and R369W have the potential to alter the binding properties of the protein. Screening
and characterization of deleterious SNPs could advance novel biomarker discovery and therapeutic
development in the future.
Publisher
Bentham Science Publishers Ltd.
Subject
Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine
Cited by
1 articles.
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