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In Silico Models for Drug Discovery pp 13–30Cite as

In Silico Systems Biology Approaches for the Identification of Antimicrobial Targets

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 993))

Abstract

Classical antibiotic discovery efforts have relied mainly on molecular library screening coupled with target-based lead optimization. The conventional approaches are unable to tackle the emergence of antibiotic resistance and are failing to provide understanding of multiple mechanisms behind drug actions and the off-target effects. These insufficiencies have prompted researchers to focus on a multidisciplinary approach of systems biology-based antibiotic discovery. Systems biology is capable of providing a big-picture view for therapeutic targets through interconnected networks of biochemical reactions derived from both experimental and computational techniques. In this chapter, we have compiled software tools and databases that are typically used for target identification through in silico analyses. We have also identified enzyme- and broad-spectrum metabolite-based drug targets that have emerged through in silico systems microbiology.

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Authors and Affiliations

  1. Center for Advanced Drug Research (CADRE), SRI International, Harrisonburg, VA, USA

    Malabika Sarker, Carolyn Talcott & Amit K. Galande

Authors
  1. Malabika Sarker
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  2. Carolyn Talcott
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  3. Amit K. Galande
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Editors and Affiliations

  1. , Dept. of Microbiology & Immunology, Drexel University College of Medicine, Queen Lane 2900, Philadelphia, 19129, Pennsylvania, USA

    Sandhya Kortagere

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Sarker, M., Talcott, C., Galande, A.K. (2013). In Silico Systems Biology Approaches for the Identification of Antimicrobial Targets. In: Kortagere, S. (eds) In Silico Models for Drug Discovery. Methods in Molecular Biology, vol 993. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-342-8_2

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  • DOI: https://doi.org/10.1007/978-1-62703-342-8_2

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-341-1

  • Online ISBN: 978-1-62703-342-8

  • eBook Packages: Springer Protocols

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