QSAR analysis and experimental evaluation of new quinazoline-containing hydroxamic acids as histone deacetylase 6 inhibitors

ABSTRACT

Histone deacetylase inhibitors represent the most important class of drugs for the treatment of human cancer and other diseases due to their influence on cell growth, differentiation, and apoptosis. Among the well-known eighteen histone deacetylases, histone deacetylase 6 (HDAC6), which is involved in oncogenesis, cell survival, and cancer cell metastasis, is of great importance. Using the CDK and alvaDesc molecular descriptors and the Random Forest and EXtreme Gradient Boosting methods, we propose a number of adequate QSAR classification models, which are integrated into a consensus model and are freely available on the OCHEM web platform (https://ochem.eu). The consensus QSAR model is used for virtual screening of a series of seven new compounds, the derivatives of N-((hydroxyamino)-oxoalkyl)-2-(quinazoline-4-ilamino)-benzamides, the synthesis schemes of which are also presented in this work. In vitro evaluation of the inhibitory activity (IC₅₀) of this series of compounds against HDAC6 allowed us to confirm the results of virtual screening and to reveal promising compounds V-2 and V-4, IC₅₀ of which is 3.25 nM and 0.04 nM, respectively. The subsequent in silico evaluation of the main ADMET properties of active compounds V-2 and V-4 allowed us to find that they have acceptable pharmacokinetic parameters and level of acute toxicity.

KEYWORDS:

• Hydroxamic acids
• quinazoline derivatives
• QSAR
• machine learning
• HDAC6
• ADMET

Acknowledgements

The authors thank Dr. Igor Tetko from the OCHEM Team (https://ochem.eu/) for use of the free software.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Part of this work was supported by the budget of the IPAC RAS State Targets – 2022 [topic No. FFSN-2021-0004].