CoMSIA Study on Substituted Aryl Alkanoic Acid Analogs as GPR40 Agonists

Authors

  • Aaditya Bhatt,

    1. Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
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  • Pallav D. Patel,

    1. Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
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  • Maulik R. Patel,

    1. Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
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  • Satyakam Singh,

    1. Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
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  • Cesar A. Lau-Cam,

    1. Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St John’s University, 8000 Utopia Parkway, Queens, NY 11439, USA
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  • Tanaji T. Talele

    Corresponding authorSearch for more papers by this author

Corresponding author: Tanaji T. Talele, talelet@stjohns.edu

Abstract

GPR40, a G-protein-coupled receptor has been well established to play a crucial role in regulating blood glucose levels. Hence, GPR40 is a potential target for future antidiabetic agents. The present 3D QSAR study is aimed at delineating structural parameters governing GPR40 agonistic activity. To meet this objective, a comparative molecular similarity indices analysis for 63 different GPR40 agonists was performed using two methods; a ligand-based 3D QSAR model employing the atom fit alignment method and a receptor-based 3D QSAR model that was derived from the predicted binding conformations obtained by docking all the GPR40 agonists at the active site of GPR40. The results of these studies showed the ligand-based model to be superior (inline image value of 0.610) to the receptor-based model (inline image value of 0.519) in terms of statistical data. The predictive ability of these models was evaluated using a test set of 15 compounds not included in the preliminary training set of 48 compounds. The predictive r2 values for the ligand- and the receptor-based models were found to be 0.863 and 0.599, respectively. Further, interpretation of the comparative molecular similarity indices analysis contour maps with reference to the active site of GPR40 provided an insight into GPR40-agonist interactions.

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