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Updated: Jul 5, 2026
08:31
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
Biocomputational strategies for microbial drug target identification
Kishore R Sakharkar1, Meena K Sakharkar, Vincent T K Chow
1Human Genome Laboratory, Department of Microbiology, Yong loo Lin School of Medicine, National University of Singapore, Singapore.
Methods in Molecular Medicine
|April 26, 2008
Summary
This study introduces a subtractive genomics approach to rapidly identify novel bacterial drug targets essential for pathogen survival. This computational strategy aids in discovering new antibiotics by analyzing microbial genomes.
Area of Science:
- Microbial genomics
- Drug discovery
- Bioinformatics
Background:
- Over 300 bacterial genome sequences are available, with more ongoing projects.
- Identifying essential, non-human homologous bacterial genes is key for novel drug target discovery.
Purpose of the Study:
- To present and demonstrate a subtractive genomics approach for identifying potential drug targets in microbial genomes.
- To facilitate the discovery of new antibiotics.
Main Methods:
- Utilized a subtractive genomics strategy.
- Applied the approach to Pseudomonas aeruginosa genome.
- Compared computational findings with gene deletion experiments.
Main Results:
- The subtractive genomics approach successfully identified putative drug targets.
- Results aligned well with experimental gene deletion data.
- Demonstrated rapid potential drug target identification.
Conclusions:
- The subtractive genomics strategy is effective for in silico drug target identification.
- Large genomic databases are valuable tools in the post-genomic era for antibiotic discovery.
- Acknowledged limitations include potential missed distant gene relationships due to low alignment scores.
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