Literature DB >> 17498919

Distribution analysis of nonsynonymous polymorphisms within the human kinase gene family.

Ali Torkamani1, Nicholas J Schork.   

Abstract

The human kinase gene family is composed of 518 genes that are involved in a diverse spectrum of physiological functions. They are also implicated in a number of diseases and encompass 10% of current drug targets. Contemporary, high-throughput sequencing efforts have identified a rich source of naturally occurring single nucleotide polymorphisms (SNPs) in kinases, a subset of which occur in the coding region of genes (cSNPs) and result in a change in the encoded amino acid sequence (nonsynonymous coding SNP; nscSNPs). What fraction of this naturally occurring variation underlies human disease is largely unknown (uDC), and much of it is assumed not to be disease causing (DC). We pursued a comprehensive computational analysis of the distribution of 1463 nscSNPs and 999 DC nscSNPs within the kinase gene family and have found that DCs are overrepresentated in the kinase catalytic domain and in receptor structures. In addition, the frequencies with which specific amino acid changes occur differ between the DCs and the uDCs, implying different biological characteristics for the two sets of human polymorphisms. Our results provide insights into the sequence and structural phenomena associated with naturally occurring kinase nscSNPs that contribute to human diseases.

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Year:  2007        PMID: 17498919     DOI: 10.1016/j.ygeno.2007.03.006

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  13 in total

1.  Congenital disease SNPs target lineage specific structural elements in protein kinases.

Authors:  Ali Torkamani; Natarajan Kannan; Susan S Taylor; Nicholas J Schork
Journal:  Proc Natl Acad Sci U S A       Date:  2008-06-25       Impact factor: 11.205

2.  HUMAN KINASES DISPLAY MUTATIONAL HOTSPOTS AT COGNATE POSITIONS WITHIN CANCER.

Authors:  Jonathan Gallion; Angela D Wilkins; Olivier Lichtarge
Journal:  Pac Symp Biocomput       Date:  2017

Review 3.  Kinase mutations in human disease: interpreting genotype-phenotype relationships.

Authors:  Piya Lahiry; Ali Torkamani; Nicholas J Schork; Robert A Hegele
Journal:  Nat Rev Genet       Date:  2010-01       Impact factor: 53.242

4.  Investigating the linkage between disease-causing amino acid variants and their effect on protein stability and binding.

Authors:  Yunhui Peng; Emil Alexov
Journal:  Proteins       Date:  2016-01-11

5.  Characterization of pathogenic germline mutations in human protein kinases.

Authors:  Jose M G Izarzugaza; Lisa E M Hopcroft; Anja Baresic; Christine A Orengo; Andrew C R Martin; Alfonso Valencia
Journal:  BMC Bioinformatics       Date:  2011-07-05       Impact factor: 3.169

6.  Disease-related mutations predicted to impact protein function.

Authors:  Christian Schaefer; Yana Bromberg; Dominik Achten; Burkhard Rost
Journal:  BMC Genomics       Date:  2012-06-18       Impact factor: 3.969

Review 7.  Analytical methods for inferring functional effects of single base pair substitutions in human cancers.

Authors:  William Lee; Peng Yue; Zemin Zhang
Journal:  Hum Genet       Date:  2009-05-12       Impact factor: 4.132

Review 8.  Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics.

Authors:  Alfonso Valencia; Manuel Hidalgo
Journal:  Genome Med       Date:  2012-07-30       Impact factor: 11.117

9.  Mutations in the KDM5C ARID Domain and Their Plausible Association with Syndromic Claes-Jensen-Type Disease.

Authors:  Yunhui Peng; Jimmy Suryadi; Ye Yang; Tugba G Kucukkal; Weiguo Cao; Emil Alexov
Journal:  Int J Mol Sci       Date:  2015-11-13       Impact factor: 5.923

10.  Structure-functional prediction and analysis of cancer mutation effects in protein kinases.

Authors:  Anshuman Dixit; Gennady M Verkhivker
Journal:  Comput Math Methods Med       Date:  2014-04-08       Impact factor: 2.238

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