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Atom-based pharmacophore modeling, CoMFA/CoMSIA-based 3D-QSAR studies and lead optimization of DPP-4 inhibitors for the treatment of type 2 diabetes

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Abstract

A dipeptidyl peptidase-4 (DPP-4) enzyme is responsible for degradation of GLP-1 incretin hormone and in cooperates in glucose metabolism. Inhibition of DPP-4 is a promising new approach for the treatment of type-2 diabetes with low risk of hypoglycemia. An analog-based design study was performed using pharmacophore modeling and 3D-QSAR to design potential lead compounds. A five-point pharmacophore model with two hydrogen bond acceptors (A), one hydrophobic (H), one positive (P), and one aromatic rings (R) as pharmacophore features was generated using 38 azabicyclo-derived dipeptidyl peptidase-IV inhibitors. The validated pharmacophore alignment was used for CoMFA and CoMSIA 3D-QSAR model development. The models generated from SYBYL shown a high cross-validated r 2 value of 0.63 and 0.61 for CoMFA and CoMSIA models. Systematic pharmacophore-based screening protocol was used to screen commercial databases. Hits retrieved were progressively passed through filters like predicted activity, fitness score, Lipinski screen, and docking scores. The survived seven hits were further visually analyzed which shows that all hits contain the same scaffold of piperazinum ring which can be replaced by the azabicyclo ring in the existing lead which may increase the potency of DPP-4 inhibitors.

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Acknowledgments

The authors pleased to acknowledge Prof. Dr. S. B. Bari (R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur, MS, India) for providing technical support. Financial support from Council of Scientific and Industrial Research, Delhi (CSIR, Delhi) is greatly acknowledged.

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  1. Institute of Pharmacy, Nirma University, S. G. Highway, Ahmedabad, 382481, Gujarat, India

    Shailesh V. Jain & Manjunath Ghate

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  1. Shailesh V. Jain
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  2. Manjunath Ghate
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Correspondence to Shailesh V. Jain.

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Jain, S.V., Ghate, M. Atom-based pharmacophore modeling, CoMFA/CoMSIA-based 3D-QSAR studies and lead optimization of DPP-4 inhibitors for the treatment of type 2 diabetes. Med Chem Res 23, 3436–3450 (2014). https://doi.org/10.1007/s00044-014-0923-2

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  • DOI: https://doi.org/10.1007/s00044-014-0923-2

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