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Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets

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Abstract

Targeting Proviral integration-site of murine Moloney leukemia virus 1 kinase, hereafter called Pim-1 kinase, is a promising strategy for treating different kinds of human cancer. Headed for this a total list of 328 formerly reported Pim-1 kinase inhibitors has been explored and divided based on the pharmacophoric features of the most active molecules into 10 subsets projected to represent potential active binding manners accessible to ligands within the binding pocket of Pim-1 kinase. Discovery Studio 4.1 (DS 4.1) was employed to detect potential pharmacophoric active binding manners anticipated by Pim-1 Kinase inhibitors. The pharmacophoric models were then allowed to compete within Quantitative Structure Activity Relationship (QSAR) framework with other 2D descriptors. Accordingly Genetic algorithm and multiple linear regression investigation were engaged to find the finest QSAR equation that has the best predictive power r 2262  = 0.70, F = 119.14, r 2LOO  = 0.693, r 2PRESS against 66 external test inhibitors = 0.71 q2 = 0.55. Three different pharmacophores appeared in the successful QSAR equation this represents three different binding modes for inhibitors within the Pim-1 kinase binding pocket. Pharmacophoric models were later used to screen compounds within the National Cancer Institute database. Several low micromolar Pim-1 Kinase inhibitors were captured. The most potent hits show IC50 values of 0.77 and 1.03 µM. Also, upon analyzing the successful QSAR Equation we found that some polycyclic aromatic electron-rich structures namely 6-Chloro-2-methoxy-acridine can be considered as putative hits for Pim-1 kinase inhibition.

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Acknowledgments

This project was sponsored by the Deanship of Scientific Research in Zarqa University. The author thanks the Faculty of pharmacy and Prof. Nancy Hakooz for their generous help and support.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, Faculty of Pharmacy, Zarqa University, Az-zarqa, Jordan

    Rand Shahin, Lubna Swellmeen & Nour Aboalhaija

  2. Department of Pharmacology, Faculty of Medicine, University of Jordan, Amman, Jordan

    Omar Shaheen

  3. Department of Pharmaceutical Sciences and Pharmacognosy, Faculty of Pharmacy, Applied Science University, Amman, Jordan

    Maha Habash

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  1. Rand Shahin
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Correspondence to Rand Shahin.

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Shahin, R., Swellmeen, L., Shaheen, O. et al. Identification of novel inhibitors for Pim-1 kinase using pharmacophore modeling based on a novel method for selecting pharmacophore generation subsets. J Comput Aided Mol Des 30, 39–68 (2016). https://doi.org/10.1007/s10822-015-9887-7

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