Investigating Structural Requirements of Some Pyrimidine-linked Benzimidazole Derivatives as Anticancer Agents Against MCF-7 Cancerous Cell Line Through the use of 2D and 3D QSARs

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Author(s): Kale Mayura*, Khan Sharuk, Hature Jyoti.

Journal Name: Current Chemical Biology

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Background: Cancer is an extremely fast, unrestrained and pathological propagation of cells. Yet there is no cancer treatment that is 100% efficient against scattered cancer. Heterocycles have been considered as a boon to treat several cancers of which pyrimidine is a core nucleus and holds an important place in cancer chemotherapy which is reflected in the use of drugs such as 5-fluorouracil, erlotinib, gefitinib and caneratinib. Also, many good antitumor active agents possess benzimidazoleas its core nucleus.

Objective: To design novel pyrimidine-linked benzimidazoles and to explore their structural requirements related to anticancer potential.

Method: 2D and 3D Quantitative structure–activity relationship (QSAR) studies were carried out on a series of already synthesized 27 pyrimidine-benzimidazole derivatives.

Results: Statistically significant and optimum 2D-QSAR model was developed by using step-wise variable multiple linear regression method, yielding correlation coefficient r2 = 0.89, cross-validated squared correlation coefficient q2 = 0.79 and external predictive ability of pred_r2 = 0.73 Best 3D-QSAR model was developed by employing molecular field analysis using step-wise variable k-nearest neighbor method which showed good correlative and predictive abilities in terms of q2 =0.77 and pred_r2= 0.93.

Conclusion: These 2D and 3D models were found to give dependable indications which helped to optimize the pyrimidine-benzimidazole derivatives of the data set. The data yielded by 2D- QSAR and 3D-QSAR models will aid in giving better perceptions about structural requirements for developing newer anticancer agents.

Keywords: MCF-7; 2D-QSAR; 3D-QSAR; MLR; kNN-MFA; anticancer activitMCF-7; 2D-QSAR; 3D-QSAR; MLR; kNN-MFA; anticancer activity

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(E-pub Ahead of Print)
DOI: 10.2174/2212796813666190207144407