Literature DB >> 16442527

Functional impacts of non-synonymous single nucleotide polymorphisms: selective constraint and structural environments.

Lei Bao1, Yan Cui.   

Abstract

In this work, we studied the correlations between selective constraint, structural environments and functional impacts of non-synonymous single nucleotide polymorphisms (nsSNPs). We found that the relation between solvent accessibility and functional impacts of nsSNPs is not as simple as generally thought. Finer structural classifications need to be taken into account to reveal the complex relations between the characteristics of a structure environment and its influence on the functional impacts of nsSNPs. We introduced two parameters for each structural environment, consensus residue percentage and residue distribution distance, to characterize the selective constraint imposed by the environment. Both parameters significantly correlate with the functional bias of nsSNPs across the structural environments. This result shows that selective constraint underlies the bias of a structural environment towards a certain type of nsSNPs (disease-associated or benign).

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Year:  2006        PMID: 16442527     DOI: 10.1016/j.febslet.2006.01.035

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  4 in total

1.  A novel computational and structural analysis of nsSNPs in CFTR gene.

Authors:  C George Priya Doss; R Rajasekaran; C Sudandiradoss; K Ramanathan; R Purohit; R Sethumadhavan
Journal:  Genomic Med       Date:  2008-05-14

2.  Structural and functional restraints on the occurrence of single amino acid variations in human proteins.

Authors:  Sungsam Gong; Tom L Blundell
Journal:  PLoS One       Date:  2010-02-12       Impact factor: 3.240

3.  An ANN model for the identification of deleterious nsSNPs in tumor suppressor genes.

Authors:  Vinod Chandra; Rejimoan Ramakrishnan; Shalini Ramanathan
Journal:  Bioinformation       Date:  2011-03-02

4.  Coupled mutation finder: a new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations.

Authors:  Mehmet Gültas; Martin Haubrock; Nesrin Tüysüz; Stephan Waack
Journal:  BMC Bioinformatics       Date:  2012-09-11       Impact factor: 3.169

  4 in total

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