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Cell Biochemistry and Biophysics

, Volume 68, Issue 1, pp 97–109 | Cite as

Computational Screening of Disease-Associated Mutations in OCA2 Gene

  • Balu Kamaraj
  • Rituraj PurohitEmail author
Original Paper

Abstract

Oculocutaneous albinism type 2 (OCA2), caused by mutations of OCA2 gene, is an autosomal recessive disorder characterized by reduced biosynthesis of melanin pigment in the skin, hair, and eyes. The OCA2 gene encodes instructions for making a protein called the P protein. This protein plays a crucial role in melanosome biogenesis, and controls the eumelanin content in melanocytes in part via the processing and trafficking of tyrosinase which is the rate-limiting enzyme in melanin synthesis. In this study we analyzed the pathogenic effect of 95 non-synonymous single nucleotide polymorphisms reported in OCA2 gene using computational methods. We found R305W mutation as most deleterious and disease associated using SIFT, PolyPhen, PANTHER, PhD-SNP, Pmut, and MutPred tools. To understand the atomic arrangement in 3D space, the native and mutant (R305W) structures were modeled. Molecular dynamics simulation was conducted to observe the structural significance of computationally prioritized disease-associated mutation (R305W). Root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessibility surface area, hydrogen bond (NH bond), trace of covariance matrix, eigenvector projection analysis, and density analysis results showed prominent loss of stability and rise in mutant flexibility values in 3D space. This study presents a well designed computational methodology to examine the albinism-associated SNPs.

Keywords

Deleterious OCA2 Melanin Pigmentation Flexibility Stability 

Abbreviations

nsSNPs

Non-synonymous single nucleotide polymorphism

OCA2

Oculocutaneous albinism type 2

MDS

Molecular dynamics simulation

RMSD

Root-mean-square deviation

RMSF

Root-mean-square fluctuation

Rg

Radius of gyration

SASA

Solvent-accessible surface area

Nh bonds

Number of hydrogen bonds

PCA

Principal component analysis

Notes

Acknowledgments

The authors gratefully acknowledge the management of Vellore Institute of Technology University for providing the facilities to carry out this work. The authors thank the anonymous reviewers for their helpful comments and critical reading of the manuscript.

Conflict of interest

Authors have no potential conflict of interest to disclose.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Bioinformatics Division, School of Bio Sciences and Technology (SBST)Vellore Institute of Technology UniversityVelloreIndia
  2. 2.Human Genetics FoundationTorinoItaly

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