Identification of new inhibitors of the kinase acti­vity of CDK2 and CDK9 by molecular modeling and high-efficiency screening

G.V. Andrianov^*, I.G. Serebriiskii^**

Kazan Federal University, Kazan, 420008 Russia

Fox Chase Cancer Center, Philadelphia, 19111 USA

E-mail: ^*grigorii.andrianov@gmail.com, ^**ilya.serebriiskii@fccc.edu

Received September 30, 2021

ORIGINAL ARTICLE

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DOI: 10.26907/2542-064X.2021.4.543-556

For citation: Andrianov G.V., Serebriiskii I.G. Identification of new inhibitors of the kinase activity of CDK2 and CDK9 by molecular modeling and high-efficiency screening. Uchenye Zapiski Kazanskogo Universiteta. Seriya Estestvennye Nauki, 2021, vol. 163, no. 4, pp. 543–556. doi: 10.26907/2542-064X.2021.4.543-556. (In Russian)

Abstract

Kinases are important components of many signaling pathways in a cell, and therefore they are involved in the regulation of such diverse processes as trans­cription, cell cycle progression, apoptosis, cell differentiation, metabolism, and intercellular communication. Their increased activity often results in the development of various oncological, neurological, and cardiovascular diseases, as well as of immune system disorders. Treatment is most frequently based on an antagonistic approach, when a small molecule compound inhibits excessive kinase activity. However, the ATP-binding site of kinases is highly conserved, which often causes these ATP-competitive inhibitors to cross-react with a variety of other kinases, resulting in low selectivity. Thus, the discovery and development of new safe and effective inhibitors is a challenging task because it requires a comprehensive study of their effects on the human kinome. The experimental validation of possible candidates is an extremely expensive procedure, and narrowing down selection of candidate targets in silico became an attractive approach in early drug discovery. Various approaches to virtual screening were developed, with the goal to increase the cost-effectiveness of drug development manyfold by reducing the need for validation experiments. In this work, we applied a combination of different computational approaches to select 22 candidate inhibitors of the kinase activity of CDK2 and CDK9 and then tested them experimentally. Establishing a pipeline of virtual screening and subsequent validation made it possible to reveal the advantages and limitations of the methods used. About 1/3 of candidates were predicted correctly, including one compound with IC50 < 2 μM for both kinases.

Keywords: virtual screening, structural alignment, energy minimization of ligand-target complex, protein kinase, CDK2, CDK9

Acknowledgements. We are grateful to J. Karanicolas, Professor at Fox Chase Cancer Center, for making this research possible and to N.I. Akberova, Associate Professor of the Department of Biochemistry and Biotechnology at Kazan Federal University, PhD in Biology, for her critical reflections on the manus­cript and valuable advice.

The study was supported by the Kazan Federal University Strategic Academic Leadership Program.

Figure Captions

Fig. 1. a) structure of the catalytic domain of CDK9 (PDB: 3BLQ) and a focused view of the binding mode of ATP and the inhibitor in the ATP-binding pocket; b) non-selective action of the kinase inhibitor dasatinib (initially developed as an ABL kinase inhibitor) on the human kinome. Dasatinib-responsive kinases are shown as dark red dots.

Fig. 2. Virtual screening strategy for the identification of new kinase inhibitors: a) 2D library of compounds in text format; b) generation of 3D conformers for each compound in the library; c) 3D alignment of the conformers relative to the position of known kinase inhibitors; d) minimization of the energy of interaction of the aligned conformers in complex with the catalytic domain of kinases.

Fig. 3. Quantitative characteristics of aminothiazole-containing compounds in the Enamine libraries: a) structural similarity between the compounds studied and known kinase inhibitors; b) distribution of templates used for alignment, the dotted line shows 50% of compounds in the library; c) energy of interaction of the inhibitors with CDK2 and CDK9.

Fig. 4. In vitro validation of the selected compounds. Compounds marked with an asterisk * showed no inhibitory effects. 

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