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

Quantitative Structure-Activity Relationships (QSAR) and Pesticides

4 Summary of conclusions

Traditional QSAR models are based on a few key physico-chemical data (typically melting point, octanol/water partition coefficient) which are then used to calculate other physico-chemical parameters if they are missing. The calculation equations should be based on experimental laboratory studies performed by accepted guidelines and the results based on regression analyses.

The conclusions of this project comparing experimental values with QSAR model estimations are summarised below. The main object was to study whether the currently recommended general QSARs could be used to perform acceptable estimates on pesticides physico-chemical properties and aquatic toxicity. The study was expanded by examining whether general or specific regression equations could be derived for log Kow and pesticides after subdivision into fungicides, herbicides, insecticides, plant growth regulators and rodenticides. No attempt has been made to improve on regression equations by removing outliers.

Melting point

The correlation between experimental and estimated melting points was low. The used method generally overestimated the melting point values. Thus, the currently best available method by Meylan and Howard (1994) is not recommendable for pesticides in its present form.

Water solubility

The estimations of water solubility were acceptable using the selected computerised QSAR model although the correlation coefficient for pesticides was smaller than for the data used to develop the model. A linear regression analysis based on log water solubility and log Kow of the pesticides used in this report resulted in a QSAR model with a slightly reduced correlation coefficient.

Vapour pressure

The presented QSAR model on vapour pressure was not able to perform a sufficient close correlation of experimental and estimated vapour pressures from the included pesticide data set. However, it should be noted that the experimental values were based on test results varying between 20°C and 25°C whereas the vapour pressures were estimated at 25°C.

Henry's Law constant

For Henry's Law constant, no conclusion can be drawn from the used pesticide data set since values estimated by calculation and by computer model may not be correct for the pesticide in question. However, it can be concluded that the two estimation methods are presenting comparable results.

Log Kow

The octanol/water partition coefficient log Kow could be reasonably well estimated from the QSAR models based on structure fragment analysis. The method is complicated and recommended to be performed by available computer models. However, an alternative QSAR model may be used based on water solubility. For the pesticides used in this report, it resulted in a lower correlation coefficient but both methods should be sufficient in a screening procedure.

Adsorption

The soil adsorption coefficient factor Koc is very important in the evaluation of the mobility of pesticides. Since the known methods for estimation are approximate at best, measured values should be used if they are available. If however, measured data on Koc for some reason are not present, the PCKOC programme (Meylan and Howard 1994) or the QSAR model to estimate Koc developed by Sabljic et al. (1995) and recommended in TGD (1996) can be used. Based on 338 pesticides in this project, a QSAR model was derived which had a correlation coefficient close to the model by Sabljic et al. (1995). For comparison of the outcome of each QSAR estimation on individual pesticides the results are presented in the appendix.

Ecotoxicity

It is important to realise that most of the QSARs developed and the QSARs presented above are based on chemicals that are biased toward industrial organic chemicals that are not overtly designed to have biological activity. Pesticides are mostly reacting in a specific mode of action and no QSARs have been recommended for substances that act by more specific modes of action (TGD 1996).

The situation with the present data set is that it has been chosen as a mixture of different pesticides to evaluate whether the evolved QSARs could be used in general. If another choice had been made, e.g. the used pesticides were selected according to function, mode of action or chemical class, another result may have appeared. However, the chosen pesticides included in this report represent too many chemical classes to collect a sufficient number in each class for analysis. On the other hand, the results demonstrate that the available QSAR models should be used with great precaution, as they are not developed specifically for pesticides.

QSARs have been developed with acceptable results for most industrial chemicals. The recommended QSARs on ecotoxicity were not recommendable for pesticides in general. However, the results cannot be used without further development for chemicals like pesticides with specific biological mode of action.

The study demonstrates that, by dividing the pesticides according to their mode of action, improved correlations could be found for some organisms and some modes of action. The problems in reaching an acceptable QSAR for estimating ecotoxicity may be multiple (cf. discussion in section 3.5.5).

Another explanation for the result could be that there is no direct relationship between log Kow and toxicity for specific acting substances.

The conclusion is that no QSARs of a sufficient and reliable quality are currently available for estimating ecotoxicity of pesticides. The values can only be acquired from regular studies.

The general idea is not that QSARs shall replace experimentally derived data for pesticides. It must be kept in the mind that the purpose of using QSAR models is to give a qualified estimate of an endpoint in replacement of a missing experimental data.

However, using the QSAR models with precaution and keeping in mind their background presents reasonable good estimates to perform preliminary assessments on physico-chemical properties and in very precautions way of degradation products and /or metabolites. As demonstrated by the studies by e.g. Nendza et al. (1991) and Vighi et al. (1991), positive results can be obtained but they must await a thorough evaluation before they can be recommended for pesticides in general or for specified groups.

Relating to degradation products and transformation products QSARs may be useful in the priority of toxicity studies and which endpoint should be studied.

QSARs have been found to have great predictive values for chemicals of less complicated structures or other modes of reaction than pesticides and the use is recommended in the TGD (1996) as a useful part of the risk assessment procedure. The area of developing QSAR models for more complicated structures and chemicals with specific modes of action is therefore currently an area of high priority.