Structure - function relationships SARs

The solvent can be toxic itself, but it may also facilitate the toxicity of solutes. On gaining information from structure-activity relationships (SAR), it is possible to minimize the hazard while maintaining efficacy of function. Designing safer chemicals can be accomplished through several different strategies, the choice of which is largely dependent on the amount of information that exists on the substance of interest. 

Combining structure-activity relationship (SAR) analysis with an understanding of functional use for product components has provided a means to compare and begin to understand the importance of the relationship between functionality and environmental effects at the molecular level. At the core of functionality is molecular structure, which drives both performance and toxicity. In some cases, this insight helped drive the development of safer substitutes, whereas in others it brought out the inherent limitations in identifying safer alternatives based on currently available chemistries and technologies. 

Since one of the main aims of green chemistry is to reduce the use and/or production of toxic chemicals, it is important for practitioners to be able to make informed decisions about the inherent toxicity of a compound. Where sufficient ecotoxicological data have been generated and risk assessments performed, this can allow for the selection of less toxic options, such as in the case of some surfactants and solvents [94, 95]. When toxicological data are limited, for example, in the development of new pharmaceuticals (see Section 15.4.3) or other consumer products, there are several ways in which information available from other chemicals may be helpful to estimate effect measures for a compound where data are lacking. Of these, the most likely to be used are the structure-activity relationships (SARs, or QSARs when they are quantitative). These relationships are also used to predict chemical properties and behavior (see Chapter 16). There often are similarities in toxicity between chemicals that have related structures and/or functional subunits. Such relationships can be seen in the progressive change in toxicity and are described in QSARs. When several chemicals with similar structures have been tested, the measured effects can be mathematically related to chemical structure [96-98] and QSAR models used to predict the toxicity of substances with similar structure. Any new chemicals that have similar structures can then be assumed to elicit similar responses. 

This area is a development in the usage of NDDO models that emphasizes their utility for large-scale problems. Structure-activity relationships (SARs) are widely used in the pharmaceutical industry to understand how the various features of biologically active molecules contribute to their activity. SARs typically take the form of equations, often linear equations, that quantify activity as a function of variables associated with the molecules. The molecular variables could include, for instance, molecular weight, dipole moment, hydrophobic surface area, octanol-water partition coefficient, vapor pressure, various descriptors associated with molecular geometry, etc. For example, Cramer, Famini, and Lowrey (1993) found a strong correlation (r = 0.958) between various computed properties for 44 alkylammonium ions and their ability to act as acetylcholinesterase inhibitors according to the equation... 

The oldest publication on structure-activity relationships (SARs) known to us from the literature is a paper by Cros from 1861. He compared the toxic effect of alcohols in various species after different routes of administration. He found an increase in toxic effect with decreasing water solubility, that is increasing lipophilicity. Cros was also the first to detect a maximum in activity followed by a decrease, i.e. a non-linear relationship, as a function of solubility of alcohols in water. 

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