Drug activity

When the property being described is a physical property, such as the boiling point, this is referred to as a quantitative structure-property relationship (QSPR). When the property being described is a type of biological activity, such as drug activity, this is referred to as a quantitative structure-activity relationship (QSAR). Our discussion will first address QSPR. All the points covered in the QSPR section are also applicable to QSAR, which is discussed next. 

In the case of drug design, it may be desirable to use parabolic functions in place of linear functions. The descriptor for an ideal drug candidate often has an optimum value. Drug activity will decrease when the value is either larger or smaller than optimum. This functional form is described by a parabola, not a linear relationship. 

Ideally, the results should be validated somehow. One of the best methods for doing this is to make predictions for compounds known to be active that were not included in the training set. It is also desirable to eliminate compounds that are statistical outliers in the training set. Unfortunately, some studies, such as drug activity prediction, may not have enough known active compounds to make this step feasible. In this case, the estimated error in prediction should be increased accordingly. 

Once a number of lead compounds have been found, computational and laboratory techniques are very successful in rehning the molecular structures to yield greater drug activity and fewer side elfects. This is done both in the laboratory and computationally by examining the molecular structures to determine which aspects are responsible for both the drug activity and the side effects. These are the QSAR techniques described in Chapter 30. Recently, 3D QSAR has become very popular for this type of application. These techniques have been very successful in the rehnement of lead compounds. 

It is emphasized that drug activity is observed through a translation process controlled by cells. The aim of pharmacology is to derive system-independent constants characterizing drug activity from the indirect product of cellular response. 

CmC, a preservative in commercial preparations of some intravenous drugs, activates CICR in a way similar to that of caffeine. 4-CmC is more potent than caffeine and shows isoform-dependent activation profiles it is much less effective in RyR3 than RyRl or RyR2. 

If the individual has not taken or received an opiate, naloxone has no drug activity. 

Once candidate molecules have been selected, there is an increased possibility for more in-depth in silico studies for toxic effects. These could, for instance, take the form of attempts to design out toxicities from a fundamental point of view, or may involve de novo modeling efforts. For instance, just as drug activity is optimized by QSAR, toxicity could also be minimized. 

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