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In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies

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Abstract

P-glycoprotein (P-gp) is a plasma membrane efflux transporter belonging to ATP-binding cassette superfamily, responsible for multidrug resistance in tumor cells. Over-expression of P-gp in cancer cells limits the efficacy of many anticancer drugs. A clear understanding of P-gp substrate binding will be advantageous in early drug discovery process. However, substrate poly-specificity of P-gp is a limiting factor in rational drug design. In this investigation, we report a dynamic trans-membrane model of P-gp that accurately identified the substrate binding residues of known anticancer agents. The study included homology modeling of human P-gp based on the crystal structure of C. elegans P-gp, molecular docking, molecular dynamics analyses and binding free energy calculations. The model was further utilized to speculate substrate propensity of in-house anticancer compounds. The model demonstrated promising results with one anticancer compound (NSC745689). As per our observations, the molecule could be a potential lead for anticancer agents devoid of P-gp mediated multiple drug resistance. The in silico results were further validated experimentally using Caco-2 cell lines studies, where NSC745689 exhibited poor permeability (P app 1.03 ± 0.16 × 10−6 cm/s) and low efflux ratio of 0.26.

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Authors and Affiliations

  1. Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar, 160 062, Punjab, India

    Rameshwar Prajapati, Udghosh Singh, Abhijeet Patil & Abhay T. Sangamwar

  2. Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar, Punjab, India

    Kailas S. Khomane, Pravin Bagul & Arvind K. Bansal

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  1. Rameshwar Prajapati
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  2. Udghosh Singh
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  3. Abhijeet Patil
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  7. Abhay T. Sangamwar
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Correspondence to Abhay T. Sangamwar.

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Prajapati, R., Singh, U., Patil, A. et al. In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies. J Comput Aided Mol Des 27, 347–363 (2013). https://doi.org/10.1007/s10822-013-9650-x

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