Pesticides Research, 94 – Quantitative Structure-Activity Relationships (QSAR) and Pesticides

Quantitative Structure-Activity Relationships (QSAR) and Pesticides

1 Introduction

The study on the relationships between molecular structure and physico-chemical and biological response, collectively known as Structure-Activity Relationships (SAR), is a rapidly growing field of research in chemistry and biology. Some areas of the application of SAR include the design of more active and less toxic agricultural products (Martin 1978).

Basically, a SAR analysis consists of comparison between experimental values by mathematical variance analysis (e.g. regression analysis, discriminant analysis, factorial analysis and pattern recognition techniques) and a selection of the best correlation values. The best-fitted correlations are then used to develop a mathematical expression to estimate end-values from known substances to unknown substances.

When performing a SAR analysis, it is assumed that the chemical or biological response produced by a substance (usually an organic compound) is a direct function of its chemical structure, and that the same substance will always produce the same response, under a given set of experimental conditions.

However, ”chemical structure” cannot be dealt with directly. Instead quantities, usually of a numerical nature, which are derived from and represent the chemical structures, are used. These quantities are called molecular descriptors. The molecular descriptors are of various types:

fragments (e.g. counts of atoms, bonds of various types, rings, ring atoms, molecular weight)
topological (e.g. molecular connectivity, molecular symmetry)
geometrical (e.g. molecular surface area and volume)
physico-chemical (e.g. molar refraction, log Kow) or substructural (e.g. topological
physico-chemical properties of substructures as embedded in the structure).

The more relevant to the chemical and to the observed responses the molecular descriptors become, the more exact the approximation will be and the more valid and useful the relationship will be.

Based on the work already performed on these initial analyses, this report uses the most promising descriptors. As most of the preliminary work has been done on simpler molecules, an evaluation at this stage may result in a less promising result. However, it has been found reasonable to perform such an analysis to assess the current stage of the use of QSARs on pesticides.

The fast development in models (i.e. mathematical expressions) has resulted in a constant rewriting to include the most recent relationships during the processing of this report. The inclusion of QSAR in the formal EU technical guidance document on risk assessment (TGD 1996) has made it imperative to present a report on QSARs and pesticides at this stage.

The statistical procedure used to derive QSAR models is linear regression analysis and it can be either single or multivariable depending on the number of structural descriptors used in a particular analysis. The regression method affords transparent relations and simple mathematical equations and leads to quantitative correlations. However, for a successful and meaningful regression analysis, precise and accurate input data are required (Karcher and Devilliers 1990).

It is important to keep in mind that the values used may be averages or

otherwise selected data and do not demonstrate the variation inherent in biological systems in contradiction to the precise estimates made from mathematical expressions. It is easy to become mesmerised by the string of precise numbers being churned out by computers and to forget that the biological data going in are not anywhere near so precise (Dagani 1981).

It is important not to exaggerate the predictive accuracy of models, especially where the experimental data are either limited or controversial (Hart 1991). The weight in evaluation of QSAR results should be placed on the level of magnitude and not the exact value which can only be established by experimental studies performed by internationally accepted guidelines. Different methods or guidelines for physical, chemical and ecotoxicological tests can be used but priority to EU recommended methods is given in Commission Directive 92/69/EEC and 87/302/EEC (revision of Annex V in 67/548/EEC) or revised versions e.g. OECD technical guidelines (OECD 1993),

Thus, QSARs can be used to assist data evaluation to contribute to the decision on whether further testing is necessary to clarify an endpoint of concern and to establish input parameters which are necessary to conduct the exposure or effect assessment.