Adme And Multimechanism Screens

In silico property prediction is needed more than ever to cope with the screening overload. Improved prediction technologies are continuing to emerge [13,14]. However, reliably measured physicochemical properties to use as ''training sets'' for new target applications have not kept pace with the in silico methodologies.

Prediction of ADME properties should be simple, since the number of descriptors underlying the properties is relatively small, compared to the number associated with effective drug-receptor binding space. In fact, prediction of ADME is difficult! The current ADME experimental data reflect a multiplicity of mechanisms, making prediction uncertain. Screening systems for biological activity are typically single mechanisms, where computational models are easier to develop [1].

For example, aqueous solubility is a multimechanism system. It is affected by lipophilicity, H bonding between solute and solvent, intramolecular H bonding, intermolecular hydrogen and electrostatic bonding (crystal lattice forces), and charge state of the molecule. When the molecule is charged, the counterions in solution may affect the measured solubility of the compound. Solution microequi-libria occur in parallel, affecting the solubility. Few of these physicochemical factors are well understood by medicinal chemists, who are charged with making new molecules that overcome ADME liabilities without losing potency.

Another example of a multi-mechanistic probe is the Caco-2 permeability assay (a topic covered in various sections of the book). Molecules can be transported across the Caco-2 monolayer by several mechanisms operating simultaneously, but to varying degrees, such as transcellular passive diffusion, paracellular passive diffusion, lateral passive diffusion, active influx or efflux mediated by transporters, passive transport mediated by membrane-bound proteins, receptor-mediated endo-cytosis, pH gradient, and electrostatic-gradient driven mechanisms. The P-glyco-protein (P-gp) efflux transporter can be saturated if the solute concentration is high enough during the assay. If the substance concentration is very low (perhaps because not enough of the compound is available during discovery), the importance of efflux transporters in gastrointestinal tract (GIT) absorption can be overestimated, providing the medicinal chemist with an overly pessimistic prediction of intestinal permeability [8,15,16]. Metabolism by the Caco-2 system can further complicate the assay outcome.

Compounds from traditional drug space (''common drugs''—readily available from chemical suppliers), often chosen for studies by academic laboratories for assay validation and computational model-building purposes, can lead to misleading conclusions when the results of such models are applied to 'real' discovery compounds, which most often have extremely low solubilities [16].

Computational models for single mechanism assays (e.g., biological receptor affinity) improve as more data are accumulated [1]. In contrast, computational models for multimechanism assays (e.g., solubility, permeability, charge state) worsen as more measurements are accumulated [1]. Predictions of human oral absorption using Caco-2 permeabilities can look very impressive when only a small number of molecules is considered. However, good correlations deteriorate as more molecules are included in the plot, and predictivity soon becomes meaningless. Lipinski states that ''The solution to this dilemma is to carry out single mechanism ADME experimental assays and to construct single mechanism ADME computational models. The ADME area is at least 5 or more years behind the biology therapeutic target area in this respect'' [1].

The subject of this book is to examine the components of the multimechanistic processes related to solubility, permeability, and charge state, with the aim of advancing improved strategies for in vitro assays related to drug absorption.

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