Identification of 156 novel SNPs in 29 genes encoding G-protein coupled receptors

Iida, Aritoshi; Nakamura, Yusuke

doi:10.1007/s10038-005-0238-8

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…Analyzing and mapping SNPs in a publicly available genome have been an effective method to discover potential drug targets for genetic diseases [Botstein and Risch, 2003;Iida and Nakamura, 2005]. The general approach for SNP analysis is to first choose a candidate gene, screen for SNPs, and then to determine haplotypes, haplotype frequencies, and risk (disease association or drug response) associated with each haplotype [Mount and Pandey, 2005].…”

Section: Genetics Analysis Reveals Clues To Gpcrs Identificationmentioning

confidence: 99%

Computational identification and analysis of G protein‐coupled receptor targets

Feng

Jiang

2006

Drug Development Research

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The completion of the human genome sequence has provided a large pool of potential drug targets for disease therapy. G protein–coupled receptors (GPCRs), which are central to signaling networks that regulate basic cellular processes, represent the most important known class of therapeutic targets for multiple disease states. Bioinformatics approaches can be applied to facilitate the identification of novel GPCRs, understanding their physiological and pathological roles, and screening for drug discovery. The present review summarizes current bioinformatics approaches that can be used to identify and analyze GPCR targets. In addition, the limitations of these technologies with the intention of setting reasonable expectations are also discussed together with some potential avenues for GPCR research. Drug Dev. Res. 67:771–780, 2006. © 2007 Wiley‐Liss, Inc.

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Section: Genetics Analysis Reveals Clues To Gpcrs Identificationmentioning

confidence: 99%

Computational identification and analysis of G protein‐coupled receptor targets

Feng

Jiang

2006

Drug Development Research

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“…Many GPCRs still are categorized as 'orphan' receptors; whether these orphan receptors will provide additional targets for drug development remains to be seen. The diversity of this receptor group is increased by the existence of numerous single nucleotide polymorphisms (SNPs) (Iida and Nakamura, 2005;Iida et al, 2004), as well as splicing and editing variants; the exact number of these remains unknown for most, if not all, GPCRs, but the GPCR database (http://www.gpcr.org/7tm/mutation/index.html) has listed '7244 point mutations for 363 proteins extracted from 1454 articles'.…”

Section: Screening the Receptoromementioning

confidence: 99%

Screening the receptorome

Kroeze

Roth

2006

J Psychopharmacol

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The term 'receptorome' is now being used to describe receptors, ion channels and transporters in the human genome that are potential drug targets. These proteins comprise a considerable fraction of the human genome, and include the G protein-coupled receptors, which are the targets for many medications. In this review, we summarize recent advances in the field, including the concept that the ultimate goal of drug discovery may not be the development of highly selective single-target drugs, the idea that potential side-effects can also be the goal of multi-target drug screening, and a discussion of the application of computational screening and public domain databases available to interested investigators.

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“…As a result, we identified a total of 7552 genetic variations that include 6733 SNP and 819 genetic variations of other types. ( 7–28 ) Simultaneously, we constructed fine‐scale and high‐density SNP maps at these genomic loci (Fig. 1).…”

Section: Identification Of 7552 Genetic Variations Within 267 Genes Rmentioning

confidence: 99%

“…Consequently, we identified a total of 7552 genetic variations among 267 gene loci, and constructed comprehensive SNP maps. ( 7–28 ) The first phase of the SNP database of representative drug‐related genes is now complete. In this review, we introduce the outline of our database with several distinctive features that have been established:…”

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confidence: 99%

Japanese single nucleotide polymorphism database for 267 possible drug‐related genes

et al. 2005

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A combination of genetic variations and various environmental factors define unique human characteristics, including individual responsiveness to drugs, severity of disease and susceptibility to common diseases. Among the genetic differences present in human populations, polymorphisms in genes that encode various enzymes, transporters and receptors involved in the metabolism of drugs are considered to be medically important because some can affect therapeutic efficacy of drugs and risk of adverse reaction.(1,2) For example, it is known that some genetic variations in the thiopurine S-methyltransferase gene cause severe adverse drug reactions to anticancer drugs or immunosuppressants, (3,4) and variations in the dihydropyrimidine dehydrogenase, uridine diphosphate glycosyltransferase 1A1, and glutathione S-transferase genes are correlated with serious toxicities following administration of 5-fluorouracil, irinotecan and cisplatin, respectively. In the year 2000, the Japanese single nucleotide polymorphism (SNP) database (JSNP) project was launched to build the infrastructure for genome-wide association studies of common diseases and drug reactions (efficacy as well as adverse reaction) as a part of the Japanese Millennium Genome project.(6) Simultaneously, we also began to screen genetic variations in the genomic regions corresponding to genes encoding various enzymes, transporters and receptors involved in drug reactions. Consequently, we identified a total of 7552 genetic variations among 267 gene loci, and constructed comprehensive SNP maps. The first phase of the SNP database of representative drug-related genes is now complete. In this review, we introduce the outline of our database with several distinctive features that have been established: 1 Unique database of drug-related genes. As we almost completely screened the genomic regions covering drug-related genes, we were able to find SNP that may influence the quality or quantity of gene products by association studies, if some of them affect the efficacy or adverse reactions of the drugs. 2 Real SNP. A certain proportion of SNP deposited to the dbSNP database at the National Center for Biotechnology Information (NCBI) are not real SNP, but misidentified SNP due to sequencing errors. However, all genetic variations that we identified by means of a combination of polymerase chain reaction (PCR) and direct sequencing are really polymorphic among the Japanese population. 3 Population-based database. This is a specialized database for the Japanese population. The presence or absence of SNP as well as their allelic frequencies are significantly different among different ethnic groups. (29,30) However, as the international HapMap data showed the very high similarity between the Japanese and Han Chinese populations, our data should be useful for other Asian populations, and should also be a good reference for people in other countries. Subjects and strategySamples of peripheral blood were obtained with written informed consent from 48 Japanese volunteers for the...

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Identification of 156 novel SNPs in 29 genes encoding G-protein coupled receptors

Cited by 7 publications

References 27 publications

Computational identification and analysis of G protein‐coupled receptor targets

Computational identification and analysis of G protein‐coupled receptor targets

Screening the receptorome

Japanese single nucleotide polymorphism database for 267 possible drug‐related genes

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