Publication: Network-based strategies can help mono-and poly-pharmacology drug discovery: a systems biology view
dc.contributor.coauthor | Nussinov, Ruth | |
dc.contributor.department | Department of Computer Engineering | |
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.kuauthor | Engin, Hatice Billur | |
dc.contributor.kuauthor | Gürsoy, Attila | |
dc.contributor.kuauthor | Keskin, Özlem | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.date.accessioned | 2024-11-09T23:53:51Z | |
dc.date.issued | 2014 | |
dc.description.abstract | The cellular network and its environment govern cell and organism behavior and are fundamental to the comprehension of function, misfunction and drug discovery. Over the last few years, drugs were observed to often bind to more than one target; thus, polypharmacology approaches can be advantageous, complementing the "one drug - one target" strategy. Targeting drug discovery from the systems biology standpoint can help in studies of network effects of mono- and poly-pharmacology. In this mini-review, we provide an overview of the usefulness of network description and tools for mono- and poly-pharmacology, and the ways through which protein interactions can help single- and multi-target drug discovery efforts. We further describe how, when combined with experimental data, modeled structural networks which can predict which proteins interact and provide the structures of their interfaces, can model the cellular pathways, and suggest which specific pathways are likely to be affected. Such structural networks may facilitate structure-based drug design; forecast side effects of drugs; and suggest how the effects of drug binding can propagate in multi-molecular complexes and pathways. | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.indexedby | PubMed | |
dc.description.issue | 8 | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsoredbyTubitakEu | N/A | |
dc.description.sponsorship | TUBITAK [109T343, 109E207] | |
dc.description.sponsorship | National Cancer Institute, National Institutes of Health [HHSN261200800001E] | |
dc.description.sponsorship | Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research This work has been supported by TUBITAK (Research Grant Numbers: 109T343 and 109E207). This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract number HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. This research was supported (in part) by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. | |
dc.description.volume | 20 | |
dc.identifier.doi | 10.2174/13816128113199990066 | |
dc.identifier.eissn | 1873-4286 | |
dc.identifier.issn | 1381-6128 | |
dc.identifier.scopus | 2-s2.0-84903728795 | |
dc.identifier.uri | https://doi.org/10.2174/13816128113199990066 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/15083 | |
dc.identifier.wos | 334309400005 | |
dc.keywords | Poly-pharmacology | |
dc.keywords | Network pharmacology | |
dc.keywords | Protein-protein interaction inhibitors | |
dc.keywords | Systems biology | |
dc.keywords | Protein-protein interfaces | |
dc.keywords | Modeling | |
dc.keywords | Protein-protein interactions | |
dc.keywords | Small-molecule inhibitors | |
dc.keywords | Druggable binding-sites | |
dc.keywords | Hot-spots | |
dc.keywords | Signal-transduction | |
dc.keywords | Transient pockets | |
dc.keywords | Database | |
dc.keywords | Interfaces | |
dc.keywords | Targets | |
dc.keywords | Cells | |
dc.language.iso | eng | |
dc.publisher | Bentham Science Publ Ltd | |
dc.relation.ispartof | Current Pharmaceutical Design | |
dc.subject | Pharmacology | |
dc.subject | Pharmacy | |
dc.title | Network-based strategies can help mono-and poly-pharmacology drug discovery: a systems biology view | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Engin, Hatice Billur | |
local.contributor.kuauthor | Keskin, Özlem | |
local.contributor.kuauthor | Gürsoy, Attila | |
local.publication.orgunit1 | College of Engineering | |
local.publication.orgunit2 | Department of Chemical and Biological Engineering | |
local.publication.orgunit2 | Department of Computer Engineering | |
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