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Status: Bibliographieeintrag

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Verfasst von:Kalinina, Olga V. [VerfasserIn]   i
 Wichmann, Oliver [VerfasserIn]   i
 Apic, Gordana [VerfasserIn]   i
 Russell, Robert B. [VerfasserIn]   i
Titel:Combinations of protein-chemical complex structures reveal new targets for established drugs
Verf.angabe:Olga V. Kalinina, Oliver Wichmann, Gordana Apic, Robert B. Russell
E-Jahr:2011
Jahr:May 5, 2011
Umfang:8 S.
Fussnoten:Gesehen am 07.07.2022
Titel Quelle:Enthalten in: Public Library of SciencePLoS Computational Biology
Ort Quelle:San Francisco, Calif. : Public Library of Science, 2005
Jahr Quelle:2011
Band/Heft Quelle:7(2011), 5, Artikel-ID e1002043, Seite 1-8
ISSN Quelle:1553-7358
Abstract:Biological networks are powerful tools for predicting undocumented relationships between molecules. The underlying principle is that existing interactions between molecules can be used to predict new interactions. Here we use this principle to suggest new protein-chemical interactions via the network derived from three-dimensional structures. For pairs of proteins sharing a common ligand, we use protein and chemical superimpositions combined with fast structural compatibility screens to predict whether additional compounds bound by one protein would bind the other. The method reproduces 84% of complexes in a benchmark, and we make many predictions that would not be possible using conventional modeling techniques. Within 19,578 novel predicted interactions are 7,793 involving 718 drugs, including filaminast, coumarin, alitretonin and erlotinib. The growth rate of confident predictions is twice that of experimental complexes, meaning that a complete structural drug-protein repertoire will be available at least ten years earlier than by X-ray and NMR techniques alone.
DOI:doi:10.1371/journal.pcbi.1002043
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1371/journal.pcbi.1002043
 Volltext: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002043
 DOI: https://doi.org/10.1371/journal.pcbi.1002043
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Drug interactions
 Protein interaction networks
 Protein interactions
 Protein structure
 Protein structure comparison
 Protein structure databases
 Protein structure networks
 Protein structure prediction
K10plus-PPN:1809399769
Verknüpfungen:→ Zeitschrift

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