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Computational biology approaches for selecting host-pathogen drug targets
James R Brown1, Michal Magid-Slav, Philippe Sanseau
1Computational Biology, GlaxoSmithKline, 1250 South Collegeville Road, UP1345, PO Box 5089, Collegeville, PA 19426-0989, USA.
Drug Discovery Today
|February 1, 2011
Summary
Genomic data reveals the host-pathogen interactome, offering new drug targets for infectious diseases. A computational framework prioritizes these targets, aiding in combating drug resistance.
Area of Science:
- Genomics
- Infectious Disease Research
- Computational Biology
Background:
- Genomic data from various platforms (RNA, miRNA, proteomics) illuminate host-pathogen interactions.
- The host-pathogen interactome is crucial for understanding infection dynamics.
- Drug-resistant infections pose a significant clinical challenge.
Purpose of the Study:
- To propose a computational biology framework for identifying and prioritizing human host targets against infectious diseases.
- To leverage the host-pathogen interactome for developing novel therapeutic strategies.
- To address the challenge of drug-resistant infections.
Main Methods:
- Analysis of genomic and proteomic data to map the host-pathogen interactome.
- Development of a computational framework for target identification and prioritization.
- Case study using the hepatitis C virus interactome.
Main Results:
- The study outlines a systematic approach to exploit interactome data for drug discovery.
- The framework enables the identification of potential human host targets.
- Prioritization of targets is based on their role in the host-pathogen interaction.
Conclusions:
- The host-pathogen interactome offers a rich source for novel drug targets.
- Computational frameworks are essential for efficiently identifying and prioritizing targets.
- This approach holds promise for developing new treatments for infectious diseases, including those with drug resistance.
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