QSAR quantitative structure-activity interpreting equation

As previously mentioned, the acronym QSAR stands for the quantitative structure-activity relationship. However, there may be some ambiguity associated with the attribute quantitative. It does not necessarily follows that results expressed or having numerical representation are necessarily quantitative. Qualitative results can equally be numerically represented. Strictly speaking, we define and view QSAR models as quantitative only when the numerically expressed models allow meaningful interpretation of the numerical results obtained for the structure-activity relationship within the basic concepts of the particular model. This means that the physicochemical models should allow quantitative interpretation of the numerical physicochemical descriptors used and that the structure-mathematical models should allow quantitative interpretation of the numerical structure-mathematical descriptors used. We will use the symbol qsar and QSAR as the abbreviation for qualitative structure-activity relationship. Such are the relationships that are non-numerical and the relationships that may be numerical but the variables used are interrelated and thus do not allow unique interpretation of the MRA equations. Because all molecular descriptors hitherto used in QSAR, whether they are based on physicochemical properties, quantum mechanical calculations, or molecular graphs, are all interrelated, it follows that all such hitherto reported results, without further elaboration, remain essentially qualitative, being qsar rather than QSAR. 

Let us start with a comment on the quantitative and the qualitative character of many structure-property and structure-activity studies. Just because results of a QSAR study are expressed in numbers does not necessarily mean that the result is quantitative if one is interested in the interpretation of the structure-property or structure-activity model considered. The result is a quantitative prediction of numerical values for the property considered from the regression equation but, at best, qualitative results relating to the interpretation of the model. In order that results qualify as quantitative in that respect, they ought to satisfy certain conditions. One such condition, which is essential for structural interpretation of the results, is that they contain all the information that is necessary to determine, for each descriptor used, how much it individually contributed to the resulting regression. In what... 

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