Chemogenomics and orthology‐based design of antibiotic combination therapies

View/ Open
Author
Chandrasekaran, Sriram
Sahin, Nil
Yilancioglu, Kaan
Kazan, Hilal
Published Version
https://doi.org/10.15252/msb.20156777Metadata
Show full item recordCitation
Chandrasekaran, Sriram, Melike Cokol‐Cakmak, Nil Sahin, Kaan Yilancioglu, Hilal Kazan, James J Collins, and Murat Cokol. 2016. “Chemogenomics and orthology‐based design of antibiotic combination therapies.” Molecular Systems Biology 12 (5): 872. doi:10.15252/msb.20156777. http://dx.doi.org/10.15252/msb.20156777.Abstract
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 antibiotic interactions. By identifying the interactions that are associated with orthologous genes, we successfully estimated drug‐interaction outcomes in the bacterial pathogens Mycobacterium tuberculosis and Staphylococcus aureus, using the E. coli INDIGO model. INDIGO thus enables the discovery of effective combination therapies in less‐studied pathogens by leveraging chemogenomics data in model organisms.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289223/pdf/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:31731667
Collections
- HMS Scholarly Articles [17875]
Contact administrator regarding this item (to report mistakes or request changes)