人工神经网络预测非环状亚硝胺急性毒性的QSAR研究

在DFT-B3LYP/6-311+G(d,p)水平对60种非环状亚硝胺分子结构进行几何全优化,通过多元逐步线性回归(MSR)分析筛选出9个量子化学描述符作为自变量,log LD50(lethal dose 50％,LD50:大鼠口服急性毒性)作为因变量,采用人工神经网络(ANN)方法构建QSAR模型.经Levenber...     

QSAR models for biocides: The example of the prediction of Daphnia magna acute toxicity

ABSTRACT

Biocides are multi-component products used to control undesired and harmful organisms able to affect human or animal health or to damage natural and manufactured products. Because of their widespread use, aquatic and terrestrial ecosystems could be contaminated by biocides. The environmental impact of biocides is evaluated through eco-toxicological studies with model organisms of terrestrial and aquatic ecosystems. We focused on the development of in silico models for the evaluation of the acute toxicity (EC₅₀) of a set of biocides collected from different sources on the freshwater crustacean Daphnia magna, one of the most widely used model organisms in aquatic toxicology. Toxicological data specific for biocides are limited, so we developed three models for daphnid toxicity using different strategies (linear regression, random forest, Monte Carlo (CORAL)) to overcome this limitation. All models gave satisfactory results in our datasets: the random forest model showed the best results with a determination coefficient r² = 0.97 and 0.89, respectively, for the training (TS) and the validation sets (VS) while linear regression model and the CORAL model had similar but lower performance (r² = 0.83 and 0.75, respectively, for TS and VS in the linear regression model and r² = 0.74 and 0.75 for the CORAL model).     

Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas)

CORrelation And Logic (CORAL) is a software that generates quantitative structure activity relationships (QSAR) for different endpoints. This study is dedicated to the QSAR analysis of acute toxicity in Fathead minnow (Pimephales promelas). Statistical quality for the external test set is a complex function of the split (into training and test subsets), the number of epochs of the Monte Carlo optimization, and the threshold that is a criterion for dividing the correlation weights into two classes rare (blocked) and not rare (active). Computational experiments with three random splits (data on 568 compounds) indicated that this approach can satisfactorily predict the desired endpoint (the negative decimal logarithm of the 50% lethal concentration, in mmol/L, pLC₅₀). The average correlation coefficients (r²) are 0.675 ± 0.0053, 0.824 ± 0.0242, 0.787 ± 0.0101 for subtraining, calibration, and test set, respectively. The average standard errors of estimation (s) are 0.837 ± 0.021, 0.555 ± 0.047, 0.606 ± 0.049 for subtraining, calibration, and test set, respectively. The CORAL software together with three random splits into subtraining, calibration, and test sets can be downloaded on the Internet ( http://www.insilico.eu/coral/ ). © 2012 Wiley Periodicals, Inc.     

Validation and extension of a similarity-based approach for prediction of acute aquatic toxicity towards Daphnia magna

Quantitative structure–activity relationship (QSAR) models for predicting acute toxicity to Daphnia magna are often associated with poor performances, urging the need for improvement to meet REACH requirements. The aim of this study was to evaluate the accuracy, stability and reliability of a previously published QSAR model by means of further external validation and to optimize its performance by means of extension to new data as well as a consensus approach. The previously published model was validated with a large set of new molecules and then compared with ChemProp model, from which most of the validation data were taken. Results showed better performance of the proposed model in terms of accuracy and percentage of molecules outside the applicability domain. The model was re-calibrated on all the available data to confirm the efficacy of the similarity-based approach. The extended dataset was also used to develop a novel model based on the same similarity approach but using binary fingerprints to describe the chemical structures. The fingerprint-based model gave lower regression statistics, but also less unpredicted compounds. Eventually, consensus modelling was successfully used to enhance the accuracy of the predictions and to halve the percentage of molecules outside the applicability domain.     

理论线性溶解能参数在苯砜基羧酸酯类化合物急性毒性QSAR研究中的应用

采用密度泛函理论方法,在B3LYP/6-31G(d)理论水平下,计算了45种苯砜基羧酸酯化合物的量子化学参数.经多元线性回归分析,得到描述此类化合物对发光菌急性毒性的模型:-lgEC50=3.02 6.24EHOMO-0.091μ-0.006P 1.22q(1)-6.67q(10),其中R=0.92,r2adj=0.82,F=42.0,q2=0.79.通过对模型进行分析,得到如下结论:苯环和酯基取代基的电负性越大,分子体积越小,毒性越大.该研究为探讨此类化合物急性毒性的机理奠定了理论基础.     

硝基芳烃对梨形四膜虫急性毒性的定量构效关系研究

硝基芳烃衍生物是炸药、染料、农药和有机合成的重要原料或中间体,应用极为广泛,但它们均为有毒物质,是我国松花江中主要有机污染物之一,其中有些化合物已被美国环保局列为优先监测污染物[1].     

氯代二苯并呋喃(PCDFs)毒性的QSAR研究

从1977年Oile首次报道城市垃圾及工业废弃物中的含氯化合物在焚烧过程中可能产生二噁英以来,人们对二噁英类化合物的产生及其对环境可能造成的危害进行了较为广泛的研究[1-3].氯代二苯并呋喃(PCDFs)是二噁英的一种,一方面由于它具有剧毒性,会导致内分泌系统和体内荷尔蒙平衡紊乱,另一方面它能对机体新陈代谢、免疫力和生殖系统造成长久的损伤,因此,有关此类化合物毒性的研究近年来受到了学术界的关注[4-7].     

QSAR for acetylcholinesterase inhibition and toxicity of two classes of phosphoramidothioates

Methamidophos (Met) is a weak inhibitor of housefly head AChE but at the same time it is highly toxic to the common housefly. The lethality of Met is believed to be due to AChE inhibition. An extensive QSAR study may help in determining the mode of action of Met in vivo and in vitro and provide a rational for its high insecticidal toxicity. Acephate (Ace), like Met, is a poor inhibitor of AChE in vitro and has a comparable to Met insect toxicity in vivo. Contrary to Met, though, Ace has much lower mammalian toxicity. Understanding the structural properties which make insecticides toxic to insects but not to mammals is of great importance, since mammals (including humans) are inadvertently exposed to these compounds. Our results were consistent with the model in which both the in vitro and in vivo toxicity of Met depends on the inhibition of the active center of AChE by the unchanged Met. An optimal susceptibility to hydrolysis is needed for Met and its analogs to have high insecticidal activity since in order to phosphorylate AChE they need to be hydrolyzed and at the same time their stability is of great importance in vivo for accumulating at the site of action. The insecticidal activity of Ace analogs may be due to direct interaction with the active center of the AChE. The mammalian toxicity of Ace analogs may be due to interaction with an 'allosteric' reaction center in the AChE.     

Assessment of the oral rat chronic lowest observed adverse effect level model in TOPKAT, a QSAR software package for toxicity prediction

The performance of the rat chronic lowest observed adverse effect level (LOAEL, the lowest exposure level at which there are biologically significant increases in the severity of adverse effects) model in Toxicity Prediction by Komputer Assisted Technology (TOPKAT), a commercial quantitative structure-activity relationship software package, was tested on a database of chemicals that are of interest to the U.S. EPA's Office of Pesticide Programs. The testing was repeated on a database of chemicals from three U.S. EPA sources that report peer-reviewed LOAELs. The results of this study were also contrasted with the results of the testing performed during TOPKAT's model-building process.     

Validation of DAPPER for 3D QSAR: conformational search and chirality metric

Adequate conformational searching of small molecules and inclusion of a chirality identifier are necessary features of any current technique for quantitative structure-activity relationships (QSAR). However, implementation of these features can be difficult and computationally expensive, and some techniques can still lead to insufficient treatment of molecular conformation. We select the standard systematic conformational search as the default search method for our recent 3D QSAR program, DAPPER, and develop a novel chirality metric for use in QSAR. These techniques are implemented in DAPPER and validated on standard data sets.