Selectivity potency-based approach

Classical QSAR will continue to play its part in the optimization and selection of drug candidates. A fundamental difficulty with classical (property-based) QSAR is an over-reliance on the relevance of hydrophobicity, electrostatic and simple bulk steric effects as determinants of relative potency. We know that conformation is crucially important, but this is ignored in the classical approaches. The need for a structure-based QSAR method which also incorporates conformational flexibility might be met by development of a neural network (Livingstone and Salt, 1992 So and Richards, 1992) or machine learning program (King et al., 1992). 

Recently, much attention has been directed toward the synthesis of peptidomimetics. These compounds can replace native peptides in the interaction with receptors. They showed increased metabolic stability, better bioavailability, and longer duration of action than native peptides, thus displaying favorable pharmacological properties [52-54]. In this sense, the design and synthesis of conformationally restricted peptidomimetics is an important approach toward improving the potency, selectivity, and metabolic stability of peptide based chugs. 

Over the past decade there has been a substantial improvement in the ability to predict metabolism-based in vivo drug interactions from kinetic data obtained in vitro. This advance has been most evident for interactions that occur at the level of cytochrome P450 (CYP)-catalyzed oxidation and reflects the availability of human tissue samples, cDNA-expressed CYPs, and well-defined substrates and inhibitors of individual enzymes. The most common paradigm in the prediction of in vivo drug interactions has been first to determine the enzyme selectivity of a suspected inhibitor and subsequently to estimate the constant that quantifies the potency of reversible inhibition in vitro. This approach has been successful in identifying clinically important potent competitive inhibitors, such as quinidine, fluoxetine, and itraconazole. However, there is a continuing concern that a number of well-established and clinically important CYP-mediated drug interactions are not predictable from the classical approach that assumes reversible mechanisms of inhibition are ubiquitous. 

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