A Cell-Based Molecular Transport Simulator for Pharmacokinetic Prediction and Cheminformatic Exploration

Abstract

In the body, cell monolayers serve as permeability barriers, determining transport of drug molecules from one organ or tissue compartment to another. After oral administration, for example, drug transport across the epithelial cell monolayer lining the lumen of the intestine determines the fraction of drug in the gut that is absorbed by the body. By modeling passive transcellular transport properties in the presence of an apical to basolateral concentration gradient, we demonstrate how a computational, cell-based molecular transport simulator can be used to define a physicochemical property space occupied by molecules with desirable permeability and intracellular retention characteristics. Considering extracellular domains of cell surface receptors located on the opposite side of a cell monolayer as a drug's desired site-of-action, simulation of transcellular transport can be used to define the physicochemical properties of molecules with maximal transcellular permeability but minimal intracellular retention. Arguably, these molecules would possess very desirable features: least likely to exhibit non-specific toxicity, metabolism and side effects associated with high (undesirable) intracellular accumulation; and, most likely to exhibit favorable bioavailability and efficacy associated with maximal rates of transport across cells and minimal intracellular retention, resulting in (desirable) accumulation at the extracellular site-of-action. Calculated permeability predictions showed good correlations with PAMPA, Caco2, and intestinal permeability measurements, without "training" the model and without resorting to statistical regression techniques to "fit" the data. Therefore, cell-based molecular transport simulators could be useful in silico screening tools for chemical genomics and drug discovery.

Effect of Phospholipidosis on the Cellular Pharmacokinetics of Chloroquine

“…Previously, we developed a computational model of cell pharmacokinetics to predict the intracellular accumulation and transcellular transport properties of small molecules across the cell monolayer (Zhang et al, 2006(Zhang et al, , 2010. By using the weakly dibasic, high-solubility drug chloroquine (CQ) (pK a 1 ϭ 9.96 and pK a 2 ϭ 7.47) as a test compound, the model was capable of capturing the transcellular transport kinetics for the first 4 h of drug treatment but underestimated the intracellular accumulation beyond the first 5 min of incubation (Zhang et al, 2010).…”

“…f represents the ratio of the activities (a n , a d1 , and a d2 ) and the total concentration. It can be calculated from lipid fraction and ionic strength in each compartment and the sorption coefficient for each species as estimated from logP o/w (Trapp and Horobin, 2005;Zhang et al, 2006) or the measured cellular partition coefficient (Zhang et al, 2010). In eq.…”

Membrane Permeability – Measurement and Prediction in Drug Discovery

“…A similarly training-independent strategy, using a mechanism-based compartmental model, was followed by Zhang et al [111] to bin compounds as high or low permeability in relationship to the reference compound, metoprolol. The interesting outcome of this model is that it allows to define a physico-chemical space within which molecules display the maximal transcellular permeability with minimal intracellular retention, reducing the risk of exhibiting undesirable side effects.…”

A Cheminformatic Toolkit for Mining Biomedical Knowledge

“…Systems biology can provide the conceptual framework for understanding the relationship between the different phenotypic states of the cell at a molecular level (e.g. through mathematical modeling of mechanistic physiological phenomena, or through Bayesian, statistical analysis of causal networks of gene or protein expression patterns (109)(110)(111)(112)(113)(114)(115)(116)(117)). Mathematical modeling can also be used to predict important cellular variables related to transport (42,(117)(118)(119)(120)(121)(122)(123)(124)(125) and distribution of small molecules (117,126,127) as well as the global effects of metabolic perturbations (16,20,128).…”

“…Quantitative structure-property relationships and mechanistic models have been developed for studying the intracellular distribution of molecules in different organelles inside cells (117,126,127,(140)(141)(142)(143)(144)(145), and for predicting the ability of small molecules to traverse cell monolayers and intracellular membranes (42,64,(118)(119)(120)(121)(122)(123)(124)(125)(146)(147)(148)(149). Many QSAR models for predicting membrane passage, intracellular accumulation and absorption have been published over the years, and can be compiled into a comprehensive database (73).…”