硝基芳烃对梨形四膜虫毒性的QSAR研究

用30种硝基芳烃化合物DFT-B3LYP/6-311G**全优化计算结构参数: 最高占有和最低未占分子轨道能级(E_HOMO和E_LUMO)、次最高占有和次最低未占分子轨道能级(E_NHOMO和E_NLUMO)、前线轨道能级差(ΔE＝E_LUMO－E_HOMO)、分子的总能量(E_T)、硝基和硝基碳上净电荷(Q_NO2和Q_C-NO2)、与卤素相连碳原子上的净电荷(Q_C-X)、分子偶极矩(μ)和分子体积(V), 结合文献中的疏水性参数(log K_ow), 按取代基类型和数目分类进行其对梨形四膜虫急性毒性(－log IC₅₀)的定量构效关系(QSARs)研究. 结果表明, 前线轨道能级对硝基芳烃毒性作用有重要贡献, 硝基芳烃对梨形四膜虫的毒性作用主要以与生物分子发生电子转移等化学反应为主, 单硝基芳烃的毒性作用还与疏水性有关. 卤素的存在增加了硝基芳烃化合物的毒性, 卤素易被亲核取代. 对30种标题物作多元线性回归, 所得模型(－log IC₅₀＝18.037＋10.446Q_NO2－41.323ΔE－20.471E_NLUMO＋24.989E_NHOMO, n＝30, R＝0.962, SE＝0.185, F＝78.640, Sig.＝0.000)具有较高毒性预测作用.     

QSAR modeling and chemical space analysis of antimalarial compounds

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.     

Repeatability analysis of the Tetrahymena pyriformis population growth impairment assay

Assessments necessary to ensure the safety of both humans and the environment are challenged by the sheer number of chemicals in use today. Chemical legislation, such as REACH, aims to use alternative methods to reduce the reliance on in vivo animal testing. Consequently, databases such as the TETRATOX database, containing data from the Tetrahymena pyriformis population growth impairment assay, have been used extensively to develop computational models which aid in priority setting and initial hazard assessments. To use any toxicological data, an assessment of quality is required. One important aspect of quality is the repeatability of the assay. This study considered TETRATOX assay data for 85 structurally and mechanistically diverse compounds. The repeatability of replicate determinations was assessed and factors relating to repeatability are discussed. Despite the majority of compounds demonstrating excellent repeatability, it was found that the mechanism of action is likely to be a modulating factor, with compounds acting via electrophilic mechanisms being more likely to exhibit reduced repeatability than those acting via narcotic mechanisms. It is evident from this study that the TETRATOX assay is a robust and highly repeatable assay, suitable for use in toxicological modelling studies and priority setting.     

Piecewise hypersphere modeling by particle swarm optimization in QSAR studies of bioactivities of chemical compounds

As the structural diversity in a quantitative structure-activity relationship (QSAR) model increases, constructing a good model becomes increasingly difficult, and simply performing variable selection might not be sufficient to improve the model quality to make it practically usable. To combat this difficulty, an approach based on piecewise hypersphere modeling by particle swarm optimization (PHMPSO) is developed in this paper. It treats the linear models describing the sought-for subsets as hyperspheres which have different radii in the data space. According to the attribute of each hypersphere, all compounds in the training set are allocated to hyperspheres to construct submodels, and particle swarm optimization (PSO) is applied to search the optimal hyperspheres for finding satisfactory piecewise linear models. A new objective function is formulated to determine the appropriate piecewise models. The performance is assessed using three QSAR data sets. Experimental results have shown the good performance of this technique in improving the QSAR modeling.     

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].