Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Cold Spring Harbor S...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Cold Spring Harbor Symposia on Quantitative Biology
Article . 2011 . Peer-reviewed
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 2 versions
addClaim

Metabolomics in Drug Target Discovery

Authors: J D, Rabinowitz; J G, Purdy; L, Vastag; T, Shenk; E, Koyuncu;

Metabolomics in Drug Target Discovery

Abstract

Most diseases result in metabolic changes. In many cases, these changes play a causative role in disease progression. By identifying pathological metabolic changes, metabolomics can point to potential new sites for therapeutic intervention. Particularly promising enzymatic targets are those that carry increased flux in the disease state. Definitive assessment of flux requires the use of isotope tracers. Here we present techniques for finding new drug targets using metabolomics and isotope tracers. The utility of these methods is exemplified in the study of three different viral pathogens. For influenza A and herpes simplex virus, metabolomic analysis of infected versus mock-infected cells revealed dramatic concentration changes around the current antiviral target enzymes. Similar analysis of human-cytomegalovirus-infected cells, however, found the greatest changes in a region of metabolism unrelated to the current antiviral target. Instead, it pointed to the tricarboxylic acid (TCA) cycle and its efflux to feed fatty acid biosynthesis as a potential preferred target. Isotope tracer studies revealed that cytomegalovirus greatly increases flux through the key fatty acid metabolic enzyme acetyl-coenzyme A carboxylase. Inhibition of this enzyme blocks human cytomegalovirus replication. Examples where metabolomics has contributed to identification of anticancer drug targets are also discussed. Eventual proof of the value of metabolomics as a drug target discovery strategy will be successful clinical development of therapeutics hitting these new targets.

Related Organizations
Keywords

Aspartic Acid, Isotope Labeling, Drug Discovery, Humans, Metabolomics, Antineoplastic Agents, Antiviral Agents

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    83
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
83
Top 10%
Top 10%
Top 10%
gold
Related to Research communities
Cancer Research