Lipophilicity and Biological Activity

It is considered that our understanding of the role of lipophilicity in drug action is the single most significant result to come from the development of QSARs over the past three decades [84],

Quantitative correlations with lipophilicity have been established with regard to relative potencies at receptor sites, the regulation of drug transport, protein binding, pharmacokinetics, toxicity, drug metabolism, and enzyme induction.

Such correlations have been established in the fields of human drug research embracing both pharmacodynamics and chemotherapy. Many studies have been made that are of interest in the development of pesticides, weedkillers, and other agrochem-icals. A field of quite recent interest is that of ecological toxicity, studies having been made of the role of lipophilicity in soil adsorption, environmental toxicity - particularly toxicity to species of fish - and environmental persistence (cf. Chapter 19).

Many histories of QSAR in drug research have been written [31, 85-88] and all refer back to Overton's studies at the turn of the century. Overton [5] noticed correlations between oil-water partition coefficients and narcotic potencies in tadpoles, and concluded that narcosis was due to physical changes affected in the . lipid constituents of cells. In particular, Overton reasoned that in order to understand the action of an anesthetic in man, knowledge would be required of its ability to penetrate cells, the fat con tent of the animal, and the partition coefficient between water and the relevant lipid! Though there were various other investigations in the next 60 years, these seemed concerned only with narcotic or anesthetic activity. The much wider relevance and applicability of lipophilicity only became appreciated following the seminal studies of Corwin Hansch in the early 1960s.

In 1962, Hansch [89] defined the "hydrophobic" substituent constant, n, and showed for a series of substituted phenoxyacetic acids that variation in biological activity (concentration to induce a 10 % growth in a plant cell culture) could be described by Eq. (18), parabolic in n, and linear in the Hammett constant, a. So started, in the unlikely field of botany, the era of QSAR.

By 1964, the Hansch group had settled on the octanol/water system as the standard for measuring partition coefficients, and had described further examples of parabolic relationships between relative biological activity and lipophilicity. This sometimes involved lipophilicity of the complete molecule, expressed as logP, and sometimes involved variation in lipophilicity at a substituent position, as in the example above. Reasons for the parabolic relationship were put forward. Mathematical modeling, by Penniston and coworkers in 1969 [90] of the transport of molecules through a series of membranes, supported the expectation of a parabolic relationship between the probability . of a molecule traversing a given number of lipid barriers in a given time, and its logP value. In 1977, Kubinyi [91] put forward both kinetic and equilibrium models to justify the expectation of bilinear relationships to describe drug transport in terms of logP. Many bilinear equations have now been found. Investigations into the role of lipophilicity in drug transport were reviewed in 1990 by Dearden [92].

Both parabolic and bilinear relationships allow one to derive the optimum value of logP for transport to a given location, within the time of a biological assay. Evidence for an optimum in lipophilicity for CNS depressants was found by 1968 [93]. Hansch was then able to assert that in order for drugs to gain rapid access to the CNS, they should preferably have a logP value near 2.0. Subsequently, studies on anesthetics, hypnotics, and other CNS agents have been made and have given birth to the "Principle of Minimal Hydrophobicity in Drug Design" [87], The thrust of this is that to keep drugs out of the CNS, and thereby avoid CNS-related side effects such as depression, weird dreams, and sedation, one should design drugs so that logP is considerably lower than 2.0. This ploy has been successful in the new generation of non-sedative antihistamines.

That we require drugs to have lower rather than higher lipophilicity depends also on other observations made over the past 30 years. Many studies on plants, animals, fish, various organelles such as liver microsomes, and enzymes have shown a linear increase in toxicity or inhibitory action in a series of compounds as logP or n increases [94].

A very high lipophilicity should also be avoided because of adverse effects on protein binding, and on drug absorption, including solubility [95],

Linear, and sometimes parabolic relationships have been found between lipophilicity and drug metabolism, either in whole animals, in liver microsomes, or by specific enzymes such as cytochrome P-450. Metabolism can be undesirable for two reasons: it may limit drug bioavailability, or it may produce toxic metabolites [95].

The ideal drug candidate, going into human studies, should have already been designed with the idea of keeping lipophilicity as low as possible, provided that this can be done without great loss of affinity to the target receptor. The receptor will commonly be the substrate binding site, or perhaps an allosteric site on an enzyme, or some control site on a cell surface. The receptor may therefore be part of a protein, and ligands may bind deep in "pockets" or on the surface of that protein. Just as the coefficients in a parabolic or bilinear QSAR can give information on the optimum lipophilicity for transport, the coefficient in the x term of a linear QSAR developed for a receptor (protein) can be diagnostic of the mode of receptor binding. Evidence from studies of enzyme inhibitors suggests that the coefficient in tc is near 0.5 when a substituent "contacts" a surface, but near 1.0 when engulfed in a pocket. Many examples come from enzymes whose structures and binding sites have been established by X-ray crystallography [96].

Over the past 20 years, the Hansch group has collected into their database some 6000 sets of data, with attendant QSAR equations, from physical organic chemistry, medicinal chemistry, and toxicology. By 1993 [97] this database contained about 3000 biological QSARs, only 15 % of which lack a term for lipophilicity! Lipophilicity is clearly a major determinant of biological activity.

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