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In Silico Models for Drug Resistance

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In Silico Models for Drug Discovery

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

Abstract

Resistance to drugs that treat infectious disease is a major problem worldwide. The rapid emergence of drug resistance is not well understood. We present two in silico models for the discovery of drug resistance mechanisms and for combating the evolution of resistance, respectively. In the first model, we computationally investigated subgraphs of a biological interaction network that show substantial adaptations when cells transcriptionally respond to a changing environment or treatment. As a case study, we investigated the response of the malaria parasite Plasmodium falciparum to chloroquine and tetracycline treatments. The second model involves a machine learning technique that combines clustering, common distance similarity measurements, and hierarchical clustering to propose new combinations of drug targets.

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Acknowledgments

Many thanks go to Karine Le Roch, Svetlana Bulashesva, Benedikt Brors, Gunnar Schramm, Anna-Lena Kranz, Roland Eils, and Rainer Koenig for many useful discussions and contributions.

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Authors and Affiliations

  1. Bio-informatic Research Group, Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Segun Fatumo, Marion Adebiyi & Ezekiel Adebiyi

  2. Institute of Structural and Molecular Biology, University College London, London, UK

    Segun Fatumo

Authors
  1. Segun Fatumo
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  2. Marion Adebiyi
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  3. Ezekiel Adebiyi
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Editor information

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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Fatumo, S., Adebiyi, M., Adebiyi, E. (2013). In Silico Models for Drug Resistance. 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_4

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  • DOI: https://doi.org/10.1007/978-1-62703-342-8_4

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-341-1

  • Online ISBN: 978-1-62703-342-8

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