Reliable structural information for rational design of benzoxazole type potential cholesteryl ester transfer protein (CETP) inhibitors through multiple validated modeling techniques

Abstract

The drug design and discovery of lipid modulators is very demanding as no new molecule has entered into the market in the last 35 years. Cholesteryl ester transfer protein (CETP) is a promising target as lipid modulators. Inhibition of the CETP enzyme reduces the risk of cardiovascular events. The first CETP inhibitor torcetrapib and related drug candidates failed in the clinical trial due to the off-target effects leading to high toxicity. Thus, newer CETP inhibitors have now paramount importance to accelerate the drug discovery efforts in the field of cardiovascular disease (CVD). In the present study, 140 benzoxazole compounds were studied by using different chemometric techniques, for example, pharmacophore mapping, molecular docking, three-dimensional quantitative structure–activity relationship comparative molecular field analysis (3D-QSAR CoMFA), topomer CoMFA and Bayesian classification, in order to generate complete and reliable information regarding the structural requirements for the CETP inhibition. The best pharmacophore hypothesis was statistically significant (regression coefficient of 0.957 and a lower root mean square of 0.890). Molecular docking study revealed that cyano-substituted compounds form hydrogen bond with targeted macromolecule. The 3D-QSAR CoMFA model also produced a leave-one-out (LOO) cross-validated Q² of 0.527, an R² of 0.853 and an R²_Pred of 0.603. Similarly, two topomer CoMFA models were also statistically significant and reliable in terms of their Q², R² and R²_Pred values. The Bayesian classification study also provided the excellent ROC values of 0.919 and 0.939 for training and test sets, respectively. Overall, this study may help in the rational design of newer benzoxazole type compounds with higher CETP inhibition.

Communicated by Ramaswamy H. Sarma

KEYWORDS:

• CETP inhibitor
• pharmacophore mapping
• 3D-QSAR
• CoMFA
• topomer CoMFA
• Bayesian classification

Acknowledgements

SAA sincerely acknowledges Jadavpur University, Kolkata, for awarding Junior Research Fellowship under State Government Fellowship Scheme of Jadavpur University, Kolkata, India. NA is thankful to UGC, New Delhi, India, for providing Rajiv Gandhi National Fellowship (RGNF). We thank the support from Jadavpur University, Kolkata, India, and Dr. Harisingh Gour University, Sagar, India, for providing the research facilities.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

TJ is thankful for the financial support from University with Potential for Excellence (UPE), Phase II Program of UGC, New Delhi, to Jadavpur University, Kolkata, India.