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Structure-activity relationships (SAR) are the traditional practices of medicinal chemistry which try to modify the effect or the potency (ie. Activity) of bioactive chemical compounds by modifying their chemical structure. Traditional medicinal chemists were using the chemical techniques of synthesis to insert new chemical groups into the biomedical compound and test the modifications in it's biological effect.
Additional recommended knowledge
That enables the determination of the chemical groups responsible for evoking the biological effect in the organism. Later this method has been developed to build mathematical relationships between a chemical structure and it's biological activity, know as Qsar .
SAR and SAR paradox
The basic assumption for all molecule based hypotheses is that similar molecules have similar activities. This principle is also called Structure-Activity Relationship (SAR). The underlying problem is therefore how to define a small difference on a molecular level, since each kind of activity, e.g. reaction ability, biotransformation ability, solubility, target activity, and so on, might depend on another difference. A good example was given in the bioisosterism review of Patanie/LaVoie.
From the computer science standpoint, the no-free-lunch theorem proves that no general algorithm can exist to define e.g. a small difference for always getting the best hypothesis.
In general, one is more interested in finding strong trends. Created hypotheses usually rely on a finite number of chemical data. Thus, the induction principle should be respected to avoid overfitted hypotheses and deriving overfitted and useless interpretations on structural/molecular data.
The SAR paradox refers to the fact that it is not the case that all similar molecules have similar activities.
|This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Structure-activity_relationship". A list of authors is available in Wikipedia.|