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Identifier |
000442915 |
Title |
Ανακάλυψη αναστολέων της κινάσης CK1 με την χρήση υπολογιστικών μεθόδων |
Alternative Title |
Discovery of kinase CK1 inhibitors using computer aided methods |
Author
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Ορφανάκης, Εμμανουήλ Γ.
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Transcriber
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Κατερινόπουλος, Χαράλαμπος
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Reviewer
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Μικρός, Εμμανουήλ
Μυριανθόπουλος, Βασίλειος
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Abstract |
In recent years, there has been widespread use of computer methodologies in research to
discover new drugs. In the present study, efforts were made, with the use of computational
methods, to discover molecules with inhibitory activity against the four CK1 isoforms. Those
kinases constitute major pharmacological targets for treating various pathologies. The search
of CK1 inhibitor candidates was conducted in four open access molecule databases. Three
different highly potent and reliable algorithms were used for the virtual screening process.
Firstly, a theoretical model was constructed and validated with the use of available
experimental data. Consequently, structure-based methods, as well as ligand-based methods,
were applied. Binding and valuation calculations were used at two levels of protein
modulation accuracy. In addition, a virtual evaluation was performed by comparing the threedimensional structural similarity between the molecules under study and known inhibitors of
the investigated kinases (ligand-based). Finally, the results obtained through the different
techniques mentioned were compared and a group of molecules with high probability of being
biologically active against the CK1 kinases were selected. The binding of these lead
compounds to the target kinases was studied by molecular dynamics simulations to draw
conclusions about the time-dependent dimension of the interaction. Compounds that exhibit
optimal characteristics and potential promising biological activity will be tested
experimentally as potential inhibitors of the aforementioned proteins.
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Language |
Greek |
Subject |
Computational tools |
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In silico studies |
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In silico μελέτες |
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Protein inhibition |
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Αναστολή πρωτεϊνών |
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Υπολογιστικά εργαλεία |
Issue date |
2021-11-24 |
Collection
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School/Department--School of Sciences and Engineering--Department of Chemistry--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/3/1/a/metadata-dlib-1634291282-553632-10775.tkl
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Views |
242 |
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