Literature DB >> 18348676

Identifying targets for drug discovery using bioinformatics.

Yi-Ping Phoebe Chen1, Feng Chen.   

Abstract

BACKGROUND: Drug discovery is the process of discovering and designing drugs, which includes target identification, target validation, lead identification, lead optimization and introduction of the new drugs to the public. This process is very important, involving analyzing the causes of the diseases and finding ways to tackle them.
OBJECTIVE: The problems we must face include: i) that this process is so long and expensive that it might cost millions of dollars and take a dozen years; and ii) the accuracy of identification of targets is not good enough, which in turn delays the process. Introducing bioinformatics into the drug discovery process could contribute much to it. Bioinformatics is a booming subject combining biology with computer science. It can explore the causes of diseases at the molecular level, explain the phenomena of the diseases from the angle of the gene and make use of computer techniques, such as data mining, machine learning and so on, to decrease the scope of analysis and enhance the accuracy of the results so as to reduce the cost and time.
METHODS: Here we describe recent studies about how to apply bioinformatics techniques in the four phases of drug discovery, how these techniques improve the drug discovery process and some possible difficulties that should be dealt with.
RESULTS: We conclude that combining bioinformatics with drug discovery is a very promising method although it faces many problems currently.

Mesh:

Year:  2008        PMID: 18348676     DOI: 10.1517/14728222.12.4.383

Source DB:  PubMed          Journal:  Expert Opin Ther Targets        ISSN: 1472-8222            Impact factor:   6.902


  18 in total

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4.  Significant cancer prevention factor extraction: an association rule discovery approach.

Authors:  Jesmin Nahar; Kevin S Tickle; A B M Shawkat Ali; Yi-Ping Phoebe Chen
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5.  Probing the structure of Leishmania major DHFR TS and structure based virtual screening of peptide library for the identification of anti-leishmanial leads.

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6.  Elucidation of the molecular mechanisms of a salicylhydrazide class of compounds by proteomic analysis.

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Review 7.  Computational systems biology approaches to anti-angiogenic cancer therapeutics.

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8.  The diversity and antimicrobial activity of Preussia sp. endophytes isolated from Australian dry rainforests.

Authors:  Rachel R Mapperson; Michael Kotiw; Rohan A Davis; John D W Dearnaley
Journal:  Curr Microbiol       Date:  2013-08-23       Impact factor: 2.188

Review 9.  Design and development of molecular imaging probes.

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Journal:  Curr Top Med Chem       Date:  2010       Impact factor: 3.295

Review 10.  Neuropeptide signalling systems - An underexplored target for venom drug discovery.

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Journal:  Biochem Pharmacol       Date:  2020-06-30       Impact factor: 5.858

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