Literature DB >> 18393868

Approaches and resources for prediction of the effects of non-synonymous single nucleotide polymorphism on protein function and interactions.

S Teng1, E Michonova-Alexova, E Alexov.   

Abstract

Almost all (99.9%) nucleotide bases are exactly the same in all people, however, the remaining 0.1% account for about 1.4 million locations where single-base DNA differences/polymorphisms (SNPs) occur in humans. Some of these SNPs, called non-synonymous SNPs (nsSNPs), result in a change of the amino acid sequences of the corresponding proteins affecting protein functions and interactions. This review summarizes the plausible mechanisms that nsSNPs may affect the normal cellular function. It outlines the approaches that have been developed in the past to predict the effects caused by nsSNPs with special emphasis on the methods that use structural information. The review provides systematic information on the available resources for predicting the effects of nsSNPs and includes a comprehensive list of existing SNP databases and their features. While nsSNPs resulting in amino acid substitution in the core of a protein may affect protein stability irreversibly, the effect of an nsSNP resulting to a mutation at the surface of a protein or at the interface of protein-protein complexes, could, in principle be, subject of drug therapy. The importance of understanding the effects caused by nsSNP mutations at the protein-protein and protein-DNA interfaces is outlined.

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Year:  2008        PMID: 18393868     DOI: 10.2174/138920108783955164

Source DB:  PubMed          Journal:  Curr Pharm Biotechnol        ISSN: 1389-2010            Impact factor:   2.837


  27 in total

1.  Predicting folding free energy changes upon single point mutations.

Authors:  Zhe Zhang; Lin Wang; Yang Gao; Jie Zhang; Maxim Zhenirovskyy; Emil Alexov
Journal:  Bioinformatics       Date:  2012-01-11       Impact factor: 6.937

2.  Natural variability of minimotifs in 1092 people indicates that minimotifs are targets of evolution.

Authors:  Kenneth F Lyon; Christy L Strong; Steve G Schooler; Richard J Young; Nervik Roy; Brittany Ozar; Mark Bachmeier; Sanguthevar Rajasekaran; Martin R Schiller
Journal:  Nucleic Acids Res       Date:  2015-06-11       Impact factor: 16.971

3.  Exploring the use of molecular dynamics in assessing protein variants for phenotypic alterations.

Authors:  Aditi Garg; Debnath Pal
Journal:  Hum Mutat       Date:  2019-07-12       Impact factor: 4.878

Review 4.  Bioinformatics and variability in drug response: a protein structural perspective.

Authors:  Jennifer L Lahti; Grace W Tang; Emidio Capriotti; Tianyun Liu; Russ B Altman
Journal:  J R Soc Interface       Date:  2012-05-02       Impact factor: 4.118

5.  Smoking, the xenobiotic pathway, and clubfoot.

Authors:  Amy Sommer; Susan H Blanton; Katelyn Weymouth; Christine Alvarez; B Stephen Richards; Douglas Barnes; Jacqueline T Hecht
Journal:  Birth Defects Res A Clin Mol Teratol       Date:  2010-12-01

6.  Structural assessment of the effects of amino acid substitutions on protein stability and protein protein interaction.

Authors:  Shaolei Teng; Anand K Srivastava; Charles E Schwartz; Emil Alexov; Liangjiang Wang
Journal:  Int J Comput Biol Drug Des       Date:  2011-02-04

7.  Computational analysis of missense mutations causing Snyder-Robinson syndrome.

Authors:  Zhe Zhang; Shaolei Teng; Liangjiang Wang; Charles E Schwartz; Emil Alexov
Journal:  Hum Mutat       Date:  2010-09       Impact factor: 4.878

8.  Modeling effects of human single nucleotide polymorphisms on protein-protein interactions.

Authors:  Shaolei Teng; Thomas Madej; Anna Panchenko; Emil Alexov
Journal:  Biophys J       Date:  2009-03-18       Impact factor: 4.033

Review 9.  Molecular mechanisms of disease-causing missense mutations.

Authors:  Shannon Stefl; Hafumi Nishi; Marharyta Petukh; Anna R Panchenko; Emil Alexov
Journal:  J Mol Biol       Date:  2013-07-16       Impact factor: 5.469

10.  A Y328C missense mutation in spermine synthase causes a mild form of Snyder-Robinson syndrome.

Authors:  Zhe Zhang; Joy Norris; Vera Kalscheuer; Tim Wood; Lin Wang; Charles Schwartz; Emil Alexov; Hilde Van Esch
Journal:  Hum Mol Genet       Date:  2013-05-21       Impact factor: 6.150

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