Experiences with the Application of QSAR in the Routine of the Notification Procedure

Abstract

On behalf of the Umweltbundesamt the Fraunhofer Gesellschaft has developed a software system (SAR-system) comprising more than 90 estimation models for endpoints relevant in environmental risk assessment. These estimation models are based on the approach of quantitative structure-activity relationships (QSAR). All models were checked for their validity and application range. In the last months the Umweltbundesamt started to test the applicability of some models concerning the endpoints fish acute toxicity, daphnia acute toxicity and ready (i.e., ultimate) biodegradability in the daily routine of the notification procedure. For testing these models the corresponding confidential data given in the dossiers of substances notified 1993 in Germany, were used. We were able to make calculations for 36% of the notified substances. For the remaining 64% of the chemicals it was impossible to accomplish SAR estimations due to several reasons, e.g., ionic structure of the compounds. Different results for the applicability of the mentioned endpoints are obtained. The predictions of the fish and Daphnia toxicity are in sufficient agreement with the experimental results, in case of the fish toxicity we receive 58% agreement, for the Daphnia toxicity 56% The corresponding values which were obtained in the US EPA/E.C. Joint Project on the evaluation of (quantitative) structure activity relationships were 82.3% and 70.9% About 300 different models were used for the calculations of these endpoints within the framework of the EPA/EC project. The SAR-system presented here contains 8 models for estimating the fish toxicity and 6 models for the Daphnia toxicity. For the prediction of the biodegradability the results obtained with the SAR-system are rather poor and have to be improved. Meanwhile the SAR-system is commercially available and can be ordered at the Fraunhofer Institute for Environmental Chemistry and Ecotoxicology, Schmallenberg (Germany).     

QAAR exploration on pesticides with high solubility:An investigation on sulfonylurea herbicide dimers formed through π–π stacking interactions

Bioactive compounds could form aggregates that influence the bio-interactive processes. In this letter,based on p–p stacking models, quantitative aggregation–activity relationship(QAAR) studies were carried out on a series of sulfonylurea herbicides with good solubility. Four QAAR/QSAR models were constructed, which indicated that the bioactivity may strongly depend on both the characters of the dimeric aggregates and the monomer. The QAAR approach based on dimer-aggregates was also applicable for the highly water-soluble sulfonylurea herbicides that can form p–p stacking interactions.It was expected that the QAAR studies based on molecular aggregation state would be applied to other pesticide systems.     

Development of an information-intensive structure–activity relationship model and its application to human respiratory chemical sensitizers

Structure–activity relationship (SAR) models are recognized as powerful tools to predict the toxicologic potential of new or untested chemicals and also provide insight into possible mechanisms of toxicity. Models have been based on physicochemical attributes and structural features of chemicals. We describe herein the development of a new SAR modeling algorithm called cat-SAR that is capable of analyzing and predicting chemical activity from divergent biological response data. The cat-SAR program develops chemical fragment-based SAR models from categorical biological response data (e.g. toxicologically active and inactive compounds). The database selected for model development was a published set of chemicals documented to cause respiratory hypersensitivity in humans. Two models were generated that differed only in that one model included explicate hydrogen containing fragments. The predictive abilities of the models were tested using leave-one-out cross-validation tests. One model had a sensitivity of 0.94 and specificity of 0.87 yielding an overall correct prediction of 91%. The second model had a sensitivity of 0.89, specificity of 0.95 and overall correct prediction of 92%. The demonstrated predictive capabilities of the cat-SAR approach, together with its modeling flexibility and design transparency, suggest the potential for its widespread applicability to toxicity prediction and for deriving mechanistic insight into toxicologic effects.     

脂质体电动色谱用于预测皮肤渗透性的定量保留活性关系的建立

脂质体电动色谱 （Liposome electrokinetic chromatography,LEKC）是一种简单快速的评价药物与生物膜相互作用的方法。本文建立了脂质体电动色谱作为高通量筛选皮肤渗透性的体外分析方法。将脂质体电动色谱中保留因子的对数值（log k）作为自变量建立了定量保留活性关系式。采用SPSS分析软件对于16种结构不同的化合物进行分析,结果表明log k与皮肤渗透性常数线性相关性良好( R²=0.886)。采用交互验证评价了该模型的预测能力。在定量保留活性关系中的一个变量和传统定量构效关系中的三个变量可解释的能力( R² =0.704)相似。文中建立的定量保留活性关系模型对于新化合物早期的筛选可提供一种有效快捷的方法。