Master'sOpen Access

CK2 (kasein kinase II) potansiyel inhibitörlerinin hesapsal olarak belirlenmesi

2022
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Advisor: Prof. Dr. Nihan Çelebi Ölçüm

Abstract (EN)

Protein kinase CK2 (casein kinase II) has been an important physiopathological target for the development of chemical inhibitors in recent years due to its physiological role in supporting the survival of the cell and its irregularity in many cancer cells. CX-4945, also known as Silmitasertib, (5-(3chlorophenylamino) benzo[c][2,6] naphthyridine-8-carboxylic acid), is so far the only drug candidate targeting CK2 that is in phase 2 human clinical trials. Therefore, there is significant interest in developing efficient CK2 inhibitors for cancer treatment. Although thienobenzocarbazoles, bioisosteres of pyridocarbazoles that display very high biological potency, have great potential for CK2 inhibition, their activities have not been explored computationally, nor experimentally. In this thesis, thienobenzocarbazoles were computationally explored as potent CK2 inhibitors. The binding patterns and affinities of thienobenzocarbazole derivatives to CK2 were investigated using docking studies and molecular dynamics simulations. With the aim of improving the binding affinities of the 33 parent thienobenzocarbazoles that were found to have relatively lower docking scores compared to CX-4945, selected compounds were further structurally modified using computational derivatization tools generating a new library of thienobenzocarbazole derivatives. Docking of these new derivatives to CK2 active site identified inhibitor candidates with improved affinities. Potential interactions between CK2 and selected inhibitor candidates were then investigated using molecular dynamics simulations in a dynamic and solvated environment. Our results suggest that thienobenzocarbazole derivative "K93" can be a promising candidate for additional development targeting CK2 inhibition.

Author

Dr. İpek Koca Kolukısa

How to Cite

İpek Koca Kolukısa (Master Thesis). CK2 (kasein kinase II) potansiyel inhibitörlerinin hesapsal olarak belirlenmesi, 2022, Yeditepe University.

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