Dataset Information

Structural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3?-hydroxysteroid dehydrogenase type 2.

ABSTRACT: Single-nucleotide polymorphisms (SNPs), a most common type of genetic mutations, result from single base pair alterations. Non-synonymous SNPs (nsSNP) occur in the coding regions of a gene and result in single amino acid substitution which might have the potential to affect the function as well as structure of the corresponding protein. In human the 3?-hydroxysteroid dehydrogenases/?(4,5)-isomerase type 2 (HSD3B2) is an important membrane-bound enzyme involved in the dehydrogenation and ?(4,5)-isomerization of the ?(5)-steroid precursors into their respective ?(4)-ketosteroids in the biosynthesis of steroid hormones such as glucocorticoids, mineralocorticoids, progesterone, androgens, and estrogens in tissues such as adrenal gland, ovary, and testis. Most of the nsSNPs of HSD3B2 are still uncharacterized in terms of their disease causing potential. So, this study has been undertaken to explore and extend the knowledge related to the effect of nsSNPs on the stability and function of the HSD3B2. In this study sixteen nsSNP of HSD3B2 were subjected to in silico analysis using nine different algorithms: SIFT, PROVEAN, PolyPhen, MutPred, SNPeffect, nsSNP Analyzer, PhD SNP, stSNP, and I Mutant 2.0. The results obtained from the analysis revealed that the prioritization of diseases associated amino acid substitution as evident from possible alteration in structure-function relationship. Structural phylogenetic analysis using ConSurf revealed that the functional residues are highly conserved in human HSD3B2; and most of the disease associated nsSNPs are within these conserved residues. Structural theoritical models of HSD3B2 were created using HHPred, Phyre2 and RaptorX server. The predicted models were evaluated to get the best one for structural understanding of amino acid substitutions in three dimensional spaces.

SUBMITTER: Goswami AM

PROVIDER: S-EPMC4539073 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Structural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3β-hydroxysteroid dehydrogenase type 2.

Goswami Achintya Mohan AM

Meta gene 20150808

Single-nucleotide polymorphisms (SNPs), a most common type of genetic mutations, result from single base pair alterations. Non-synonymous SNPs (nsSNP) occur in the coding regions of a gene and result in single amino acid substitution which might have the potential to affect the function as well as structure of the corresponding protein. In human the 3β-hydroxysteroid dehydrogenases/Δ(4,5)-isomerase type 2 (HSD3B2) is an important membrane-bound enzyme involved in the dehydrogenation and Δ(4,5)-i ...[more]

PMID: 26288759

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Project description:The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 Genomes database provides a critical opportunity for further interpreting disease associations with single nucleotide polymorphisms (SNPs) discovered from genetic association studies. Currently, direct sequencing of candidate genes or regions on a large number of subjects remains both cost- and time-prohibitive.To accelerate the translation from discovery to functional studies, we propose an in silico gene sequencing method (ISS), which predicts phased sequences of intragenic regions, using SNPs. The key underlying idea of our method is to infer diploid sequences (a pair of phased sequences/alleles) at every functional locus utilizing the deep sequencing data from the 1000 Genomes Project and SNP data from the HapMap Project, and to build prediction models using flanking SNPs. Using this method, we have developed a database of prediction models for 611 known genes. Sequence prediction accuracy for these genes is 96.26% on average (ranges 79%-100%). This database of prediction models can be enhanced and scaled up to include new genes as the 1000 Genomes Project sequences additional genes on additional individuals. Applying our predictive model for the KCNJ11 gene to the Wellcome Trust Case Control Consortium (WTCCC) Type 2 diabetes cohort, we demonstrate how the prediction of phased sequences inferred from GWAS SNP genotype data can be used to facilitate interpretation and identify a probable functional mechanism such as protein changes.Prior to the general availability of routine sequencing of all subjects, the ISS method proposed here provides a time- and cost-effective approach to broadening the characterization of disease associated SNPs and regions, and facilitating the prioritization of candidate genes for more detailed functional and mechanistic studies.

Dataset Information

Structural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3?-hydroxysteroid dehydrogenase type 2.

Publications

Structural modeling and in silico analysis of non-synonymous single nucleotide polymorphisms of human 3β-hydroxysteroid dehydrogenase type 2.

Similar Datasets

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