Chemogenomics and orthology-based design of antibiotic combination therapies.

ABSTRACT: Combination antibiotic therapies are being increasingly used in the clinic to enhance potency and counter drug resistance. However, the large search space of candidate drugs and dosage regimes makes the identification of effective combinations highly challenging. Here, we present a computational approach called INDIGO, which uses chemogenomics data to predict antibiotic combinations that interact synergistically or antagonistically in inhibiting bacterial growth. INDIGO quantifies the influence of individual chemical-genetic interactions on synergy and antagonism and significantly outperforms existing approaches based on experimental evaluation of novel predictions in Escherichia coli Our analysis revealed a core set of genes and pathways (e.g. central metabolism) that are predictive of an

SUBMITTER: Chandrasekaran S 

PROVIDER: S-EPMC5289223 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature