Rapid Analysis of Pharmacology for Infectious Diseases

Andrew L. Hopkins, G. Richard Bickerton, Ian M. Carruthers, Stephen K. Boyer, Harvey Rubin, John P. Overington

    Research output: Contribution to journalReview articlepeer-review

    17 Citations (Scopus)


    Pandemic, epidemic and endemic infectious diseases are united by a common problem: how do we rapidly and cost-effectively identify potential pharmacological interventions to treat infections? Given the large number of emerging and neglected infectious diseases and the fact that they disproportionately afflict the poorest members of the global society, new ways of thinking are required to develop high productivity discovery systems that can be applied to a large number of pathogens. The growing availability of parasite genome data provides the basis for developing methods to prioritize, a priori potential drug targets and analyze the pharmacological landscape of an infectious disease. Thus the overall objective of infectious disease informatics is to enable the rapid generation of plausible, novel medical hypotheses of testable pharmacological experiments, by uncovering undiscovered relationships in the wealth of biomedical literature and databases that were collected for other purposes. In particular our goal is to identify potential drug targets present in a pathogen genome and prioritize which pharmacological experiments are most likely to discover drug-like lead compounds rapidly against a pathogen (i.e. which specific compounds and drug targets should be screened, in which assays and where they can be sourced). An integral part of the challenge is the development and integration of methods to predict druggability, essentiality, synthetic lethality and polypharmocology in pathogen genomes, while simultaneously integrating the inevitable issues of chemical tractability and the potential for acquired drug resistance from the start.

    Original languageEnglish
    Pages (from-to)1292-1300
    Number of pages9
    JournalCurrent Topics in Medicinal Chemistry
    Issue number10
    Publication statusPublished - May 2011


    • Chemogenomics
    • target identification
    • druggable genome
    • MODELS
    • GENOME
    • GENES


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