title: Computational biology approaches for selecting host-pathogen drug targets.
abstract: The proliferation of genomic platform data, ranging from silencing RNAs through mRNA and microRNA expression to proteomics, is providing new insights into the interplay between human and pathogen genes during infection: the so-called 'host-pathogen interactome'. Exploiting the interactome for novel human drug targets could provide new therapeutic avenues towards the treatment of infectious disease, which could ameliorate the growing clinical challenge of drug-resistant infections. Using the hepatitis C virus interactome as an example, here we suggest a computational biology framework for identifying and prioritizing potential human host targets against infectious diseases.
authors.affiliation: Computational Biology, GlaxoSmithKline, 1250 South Collegeville Road, UP1345, PO Box 5089, Collegeville, PA 19426-0989, USA.
authors.forename: James R
authors.initials: JR
authors.lastname: Brown
authors.forename: Michal
authors.initials: M
authors.lastname: Magid-Slav
authors.forename: Philippe
authors.initials: P
authors.lastname: Sanseau
authors.forename: Deepak K
authors.initials: DK
authors.lastname: Rajpal
mesh_terms: D000818:Animals; D003141:Communicable Diseases / Q000188:drug therapy* / Q000382:microbiology; D019295:Computational Biology / Q000379:methods*; D016503:Drug Delivery Systems; D004352:Drug Resistance, Microbial; D016174:Hepacivirus / Q000187:drug effects; D006526:Hepatitis C / Q000188:drug therapy / Q000821:virology; D054884:Host-Pathogen Interactions; D006801:Humans