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Related Experiment Videos

Mining nematode genome data for novel drug targets.

Jeremy M Foster1, Yinhua Zhang, Sanjay Kumar

  • 1Molecular Parasitology, New England Biolabs, 32 Tozer Road, Beverly, MA 01915, USA.

Trends in Parasitology
|March 1, 2005
PubMed
Summary

Large-scale sequencing and functional analysis of nematode genes offer a powerful new way to find drug targets. This review outlines resources and strategies for efficiently mining genomic data to identify potential therapeutic targets in nematodes.

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Area of Science:

  • Genomics
  • Nematology
  • Drug Discovery

Background:

  • Over 400,000 expressed sequence tags (ESTs) from 30+ nematode species are available.
  • Full genomic sequences for select nematodes are being determined.
  • Functional analyses in Caenorhabditis elegans have elucidated the roles of most predicted genes.

Purpose of the Study:

  • To describe available information sources for nematode genomic data.
  • To present strategies for efficient mining of nematode genomic databases.
  • To leverage genomic data for identifying pre-validated drug targets.

Main Methods:

  • Mining of nematode genomic databases.
  • Utilizing expressed sequence tag (EST) data.
  • Leveraging functional genomics data from model organisms like Caenorhabditis elegans.

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Main Results:

  • An unprecedented volume of nematode DNA sequence data is accessible.
  • Comprehensive gene function data is becoming available.
  • Opportunities exist for identifying validated drug targets through genomic data mining.

Conclusions:

  • The wealth of nematode genomic and functional data presents a significant opportunity for drug target identification.
  • Efficient strategies and databases are crucial for exploiting this data.
  • This approach can expedite the discovery of novel therapeutic targets in nematodes.