dc.contributor.author | Mitsopoulos, C | |
dc.contributor.author | Schierz, AC | |
dc.contributor.author | Workman, P | |
dc.contributor.author | Al-Lazikani, B | |
dc.date.accessioned | 2020-07-23T15:00:02Z | |
dc.date.issued | 2015-12-23 | |
dc.identifier.citation | PLoS computational biology, 2015, 11 (12), pp. e1004597 - ? | |
dc.identifier.issn | 1553-734X | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/3852 | |
dc.identifier.eissn | 1553-7358 | |
dc.identifier.doi | 10.1371/journal.pcbi.1004597 | |
dc.description.abstract | The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. | |
dc.format | Electronic-eCollection | |
dc.format.extent | e1004597 - ? | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | PUBLIC LIBRARY SCIENCE | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.subject | Humans | |
dc.subject | Neoplasms | |
dc.subject | Neoplasm Proteins | |
dc.subject | Antineoplastic Agents | |
dc.subject | Drug Delivery Systems | |
dc.subject | Drug Therapy, Computer-Assisted | |
dc.subject | Protein Interaction Mapping | |
dc.subject | Signal Transduction | |
dc.subject | Algorithms | |
dc.subject | Models, Biological | |
dc.subject | Computer Simulation | |
dc.subject | Drug Discovery | |
dc.subject | Molecular Targeted Therapy | |
dc.title | Distinctive Behaviors of Druggable Proteins in Cellular Networks. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2015-10-13 | |
rioxxterms.versionofrecord | 10.1371/journal.pcbi.1004597 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2015-12-23 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | PLoS computational biology | |
pubs.issue | 12 | |
pubs.notes | Not known | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Therapeutics | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Therapeutics | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Therapeutics/Computational Biology and Chemogenomics | |
pubs.publication-status | Published | |
pubs.volume | 11 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Computational Biology and Chemogenomics | |
dc.contributor.icrauthor | Mitsopoulos, Konstantinos | |
dc.contributor.icrauthor | Workman, Paul | |
dc.contributor.icrauthor | Al-Lazikani, Bissan | |