Uroporphyrinogen decarboxylase is a cytosolic enzyme involved in the biosynthetic pathway of heme production. Decreased activity of this enzyme results in porphyria cutanea tarda and hepato erythropoietic porphyria. Nonsynonymous single nucleotide polymorphisms (nsSNPs) alter protein sequence and can cause disease. Identifying the deleterious nsSNPs that contribute to disease is an important task. We used five different in silico tools namely SIFT, PANTHER, PolyPhen2, SNPs&amp;GO, and I-mutant3 to identify deleterious nsSNPs in UROD gene. Further, we used molecular dynamic (MD) approach to evaluate the impact of deleterious mutations on UROD protein structure. By comparing the results of all the five prediction results, we screened 35 (51.47 %) nsSNPs as highly deleterious. MD analysis results show that all the three L161Q, L282R, and I334T deleterious variants were affecting the UROD protein structural stability and flexibility. Our findings provide strong evidence on the effect of deleterious nsSNPs in UROD gene. A detailed MD study provides a new insight in the conformational changes occurred in the mutant structures of UROD protein. © 2014, Springer Science+Business Media New York.

George Priya Doss C

Department of Integrative Biology

School of Bio Sciences and Technology

Vellore Campus

Magesh R.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

Cell Biochemistry and Biophysics

Background: In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of F8 and F9 from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge. Methods. We performed an in silico analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability. Results: Out of 510 nsSNPs in F8, 378 nsSNPs (74%) were predicted to be 'intolerant' by SIFT, 371 nsSNPs (73%) were predicted to be 'damaging' by PolyPhen and 445 nsSNPs (87%) as 'less stable' by I-Mutant2.0. In F9, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both F8 and F9. Conclusions: The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These in silico tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes. © 2012 Doss; licensee BioMed Central Ltd.

Fulltext

Journal of Biomedical Science

In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

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 within silicoprediction 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 inHGDgene causing alkaptonuria.

The Scientific World Journal

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

Protein Engineering Design and Selection

Comparison of a molecular dynamics model with the X-ray structure of the N370S acid- -glucosidase mutant that causes Gaucher disease

Human Mutation

Performance of mutation pathogenicity prediction methods on missense variants

Computational analysis of missense mutations causing Snyder-Robinson syndrome

Computational Identification of Pathogenic Associated nsSNPs and its Structural Impact in UROD Gene: A Molecular Dynamics Approach

Journal	Data powered by TypesetCell Biochemistry and Biophysics
Publisher	Data powered by TypesetSpringer Science and Business Media LLC
ISSN	1085-9195
Open Access	No