Predictive hybrid paradigm for cytotoxic activity of 1,3,4-thiadiazole derivatives as CDK6 inhibitors against human (MCF-7) breast cancer cell line and its structural modifications: rational for novel cancer therapeutics

Abstract

The dysregulation of cyclin-CDK6 interactions has been implicated in human breast cancer, providing a rationale for more therapeutic options. Recently, ATP-competitive inhibitors have been employed for managing breast cancer. These molecules, like most natural CDKs inhibitors, potently bind in the ATP-binding site of CDK6 to regulate trans-activation. Nonetheless, only a few numbers of these molecules are approved to mitigate breast cancer, thus, ensuring that the search for more selective inhibitors continues. In this study, we attempted to establish the selective predictive models for identifying potent CDK6 inhibitors against a human breast cancer cell-line using a dataset of fifty-two 1,3,4-thiadiazole derivatives. The significant eight descriptor hybrid QSAR models generated exhibited encouraging statistical attributes including $R^2$> 0.70, Q²_LOO > 0.70, Q²_LMO > 0.60, $Q_{f_n}^2$ > 0.6. Furthermore, the study designed new compounds based on the activity and structural basis for selectivity of compounds for CDK6. While demonstrating good potency and modest selectivity, the compound C16, which showed significantly high activity of 5.5607 µM and binding energy value of −9.0 Kcal/mol, was used as template for compounds design to generate 10 novel series of 1,3,4-thiadiazole analogues containing benzisoselenazolone scaffolds, with significant pharmacological activity and better selectivity for CDK6. By our rationale, four of the designed compounds (C16b, C16h, C16i, and C16j) with activity values of 6.2584 µM, 6.7812 µM, 6.4717 µM, and 6.2666 µM respectively, and binding affinities of −10.0 kcal/mol, −9.9 kcal/mol, −9.9 kcal/mol, and −9.9 kcal/mol respectively, may emerge as therapeutic options for breast cancer treatment after extensive in vitro and in vivo studies.

Communicated by Ramaswamy H. Sarma

Keywords:

• CDK6 inhibitors
• genetic-algorithm multiple linear regression (GA-MLR)
• human breast cancer cell line
• quantitative structure activity relationship (QSAR)
• molecular docking simulation
• structural modification

Acknowledgements

The authors gratefully appreciated Dr. Suyant Pant, National Institute of Pharmaceutical Education and Research Kolkata-700054, west Bengal India, for his contributions and encouragement to carry out this work. In addition, we are grateful to Prof. Paola Gramatica for the issued license and permission to use the QSARIN v 2.2.4 software.

Disclosure statement

We declare no known competing financial interests or personal relationships that could have appeared to influence this current study.

Authors’ contributions

The study in this manuscript was collaboratively executed by the aforementioned authors. POC conceptualize the idea and design the experiment described in this study. POC, HIU, and OI were involved in the investigation process of this study by conducting the experiment, analysing and evaluating the results given in this study. CBO and OMO were involved in the validation and visualization of the molecular interactions of the reported complexes. OJO and MOE drafted the manuscript and were involved in the methodology. The overall study was carried out under the supervision of OI and HIU. All the authors read and edited the manuscript prior to submission.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.