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dc.contributor.authorChandrasekaran, Sriram
dc.contributor.authorÇokol-Çakmak, Melike
dc.contributor.authorŞahin, Nil
dc.contributor.authorYılancıoğlu, Kaan
dc.contributor.authorKazan, Hilal
dc.contributor.authorCollins, James J.
dc.contributor.authorÇokol, Murat
dc.date.accessioned2019-12-30T11:28:50Z
dc.date.available2019-12-30T11:28:50Z
dc.date.issued2016
dc.identifier.citationChandrasekaran, S., Çokol-Çakmak, M., Şahin, N., Yılancıoğlu, K., Kazan, H., Collins, J. J. & Çokol, M. (2016). Chemogenomics and orthology‐based design of antibiotic combination therapies. Molecular Systems Biology, 12(872), 1-12.en_US
dc.identifier.issn1744-4292
dc.identifier.urihttp://hdl.handle.net/20.500.12566/183
dc.identifier.urihttps://doi.org/10.15252/msb.20156777
dc.description.abstractCombination 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 lessstudied pathogens by leveraging chemogenomics data in model organisms.en_US
dc.description.sponsorshipNo sponsoren_US
dc.language.isoenen_US
dc.publisherMolecular Systems Biologyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectChemogenomicsen_US
dc.subjectKemogenomiktr_TR
dc.subjectCombination therapyen_US
dc.subjectKombinasyon tedavisitr_TR
dc.subjectDrug resistanceen_US
dc.subjectİlaç direncitr_TR
dc.subjectMycobacterium tuberculosisen_US
dc.subjectMikobakterium tüberküloztr_TR
dc.subjectStaphylococcus aureusen_US
dc.subjectStaphylococcus aureustr_TR
dc.titleChemogenomics and orthology‐based design of antibiotic combination therapiesen_US
dc.typearticleen_US
dc.relation.publicationcategoryInternational publicationen_US
dc.identifier.wosWOS:000384711800004
dc.identifier.scopus2-s2.0-84971009551
dc.identifier.volume12
dc.identifier.issue872
dc.identifier.startpage1
dc.identifier.endpage12
dc.contributor.orcid0000-0003-2461-4579 [Kazan, Hilal]
dc.contributor.abuauthorKazan, Hilal
dc.contributor.YOKid107780 [Kazan, Hilal]
dc.contributor.ScopusAuthorID35094213400 [Kazan, Hilal]
dc.identifier.PubMedID27222539


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