Predictive systems biology approach to broad-spectrum, host-directed drug target discovery in infectious diseases

Pac Symp Biocomput. 2013:17-28.

Abstract

Knowledge of immune system and host-pathogen pathways can inform development of targeted therapies and molecular diagnostics based on a mechanistic understanding of disease pathogenesis and the host response. We investigated the feasibility of rapid target discovery for novel broad-spectrum molecular therapeutics through comprehensive systems biology modeling and analysis of pathogen and host-response pathways and mechanisms. We developed a system to identify and prioritize candidate host targets based on strength of mechanistic evidence characterizing the role of the target in pathogenesis and tractability desiderata that include optimal delivery of new indications through potential repurposing of existing compounds or therapeutics. Empirical validation of predicted targets in cellular and mouse model systems documented an effective target prediction rate of 34%, suggesting that such computational discovery approaches should be part of target discovery efforts in operational clinical or biodefense research initiatives. We describe our target discovery methodology, technical implementation, and experimental results. Our work demonstrates the potential for in silico pathway models to enable rapid, systematic identification and prioritization of novel targets against existing or emerging biological threats, thus accelerating drug discovery and medical countermeasures research.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Validation Study

MeSH terms

  • Algorithms
  • Animals
  • Communicable Diseases, Emerging / drug therapy*
  • Computational Biology
  • Computer Simulation
  • Drug Discovery / methods*
  • Drug Discovery / statistics & numerical data
  • Host-Pathogen Interactions
  • Humans
  • Knowledge Bases
  • Mice
  • Models, Biological
  • Pilot Projects
  • Systems Biology