Change search
ReferencesLink to record
Permanent link

Direct link
Drug combinatorics and side effect estimation on the signed human drug-target network
University of Politecn Cataluna, Spain.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-4142-6502
2016 (English)In: BMC Systems Biology, ISSN 1752-0509, E-ISSN 1752-0509, Vol. 10, no 74Article in journal (Refereed) Published
Abstract [en]

Background: The mode of action of a drug on its targets can often be classified as being positive (activator, potentiator, agonist, etc.) or negative (inhibitor, blocker, antagonist, etc.). The signed edges of a drug-target network can be used to investigate the combined mechanisms of action of multiple drugs on the ensemble of common targets. Results: In this paper it is shown that for the signed human drug-target network the majority of drug pairs tend to have synergistic effects on the common targets, i.e., drug pairs tend to have modes of action with the same sign on most of the shared targets, especially for the principal pharmacological targets of a drug. Methods are proposed to compute this synergism, as well as to estimate the influence of the drugs on the side effect of another drug. Conclusions: Enriching a drug-target network with information of functional nature like the sign of the interactions allows to explore in a systematic way a series of network properties of key importance in the context of computational drug combinatorics.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD , 2016. Vol. 10, no 74
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-131906DOI: 10.1186/s12918-016-0326-8ISI: 000383020500001PubMedID: 27526853OAI: oai:DiVA.org:liu-131906DiVA: diva2:1034863
Note

Funding Agencies|Swedish Research Council [2015-04390]

Available from: 2016-10-13 Created: 2016-10-11 Last updated: 2016-11-07

Open Access in DiVA

fulltext(1509 kB)11 downloads
File information
File name FULLTEXT01.pdfFile size 1509 kBChecksum SHA-512
a53a7a8ebcc55dd6036d83d986c1fd23780274a47f4ce6ee3d4545fcf3e2707be891051e05c82f456ffc1a94f6730fa9da4121dbd6754b780aa1f4aff5857219
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Altafini, Claudio
By organisation
Automatic ControlFaculty of Science & Engineering
In the same journal
BMC Systems Biology
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 11 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 23 hits
ReferencesLink to record
Permanent link

Direct link