Abstract
P-glycoprotein (P-gp) is a multispecific transporter which has a natural detoxification role. The inhibition of substrate transport by P-gp can be presented by a number of parameters, including percentage inhibition and IC50. Inhibition constant, Ki, is believed to be a more universal parameter allowing easy comparison of data from different substrate conditions. The aim of this investigation was to use molecular descriptors of the inhibitors, docking scores, and the parameters of the probe substrate for the development of Quantitative Structure-Activity Relationships (QSARs) for the prediction of P-gp inhibition constants. QSARs were developed using a number of data mining and pre-processing feature selection methods. A chi-square based regression tree followed by a boosted trees model were the most accurate in the estimation of Ki. The selected models incorporated molecular descriptors of the inhibitors followed by the molecular descriptors of probe substrates, whereas no docking scores were selected by the models. Potent P-gp inhibitors showed higher lipophilicity and molecular weights than those molecules defined by Oprea's rule.
Highlights
One in four deaths in the United States is due to cancer and recently the American Cancer Society reported a total of 1,660,290 new cancer cases and 580,350 cancer deaths are projected to occur in the UnitedJ Drug Metab Toxicol, an open access journal ISSN: 2157-7609Citation: Sharifi M, Raevsky AV, Ghafourian T (2016) Effect of Molecular Structure, Substrate and Docking Scores on the Prediction of the Inhibition Constants of P-glycoprotein Inhibitors
In order to develop accurate models for the P-gp inhibition, this study used Ki values of large set of P-gp inhibitors calculated from the reported IC50 and the probe substrate’s Km and concentration values from the literature using Cheng and Prusoff’s equation
In comparison with IC50, this parameter allows a better comparison between inhibitory activities measured using different probe substrates and substrate concentrations
Summary
One in four deaths in the United States is due to cancer and recently the American Cancer Society reported a total of 1,660,290 new cancer cases and 580,350 cancer deaths are projected to occur in the UnitedJ Drug Metab Toxicol, an open access journal ISSN: 2157-7609. One in four deaths in the United States is due to cancer and recently the American Cancer Society reported a total of 1,660,290 new cancer cases and 580,350 cancer deaths are projected to occur in the United. States in 2013 [1]. The failure of cancer treatment can be attributed to a variety of different pharmacological and clinical reasons; but one major cause of the treatment failure is Multidrug Resistance (MDR) to chemotherapeutics [2]. MDR mechanisms can result in resistance to a number of structurally and functionally unrelated chemotherapeutic agents. P-gp, known as multidrug resistance protein 1 (MDR1), is a well-studied glycoprotein that demonstrated its function as a transporter of hydrophobic drugs, lipids, steroids and metabolic products [4]
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