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The Scientific World Journal
Volume 2012, Article ID 738423, 9 pages
Research Article

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

1Department of Biotechnology, Faculty of Biomedical Sciences, Technology & Research, Sri Ramachandra University, Chennai 600116, India
2Centre for Nanobiotechnology, Medical Biotechnology Division, School of Biosciences and Technology, VIT University, Tamil Nadu, Vellore 632014, India

Received 13 September 2011; Accepted 31 October 2011

Academic Editor: Andrew Walley

Copyright © 2012 R. Magesh and C. George Priya Doss. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria.