Showing papers by "Xianliang Qiao published in 2014"

Predicting Gaseous Reaction Rates of Short Chain Chlorinated Paraffins with ·OH: Overcoming the Difficulty in Experimental Determination

Abstract: Short chain chlorinated paraffins (SCCPs) are under evaluation for inclusion in the Stockholm Convention on persistent organic pollutants. However, information on their reaction rate constants with gaseous ·OH (kOH) is unavailable, limiting the evaluation of their persistence in the atmosphere. Experimental determination of kOH is confined by the unavailability of authentic chemical standards for some SCCP congeners. In this study, we evaluated and selected density functional theory (DFT) methods to predict kOH of SCCPs, by comparing the experimental kOH values of six polychlorinated alkanes (PCAs) with those calculated by the different theoretical methods. We found that the M06-2X/6-311+G(3df,2pd)//B3LYP/6-311 +G(d,p) method is time-effective and can be used to predict kOH of PCAs. Moreover, based on the calculated kOH of nine SCCPs and available experimental kOH values of 22 PCAs with low carbon chain, a quantitative structure–activity relationship (QSAR) model was developed. The molecular structural ch...

Method for predicting fish bio-concentration factors of organic chemicals by quantitative structure-activity relationship

Abstract: The invention discloses a method for predicting fish bio-concentration factors of organic chemicals by the quantitative structure-activity relationship, and belongs to the field of ecological risk assessment and test strategies. According to the method, bio-concentration factor data of 780 types of organic compounds are collected from public databases or published papers; molecular structures of the organic compounds are optimized according to the density functional theory, and 4885 types of molecule descriptors of the organic compounds are preliminarily screened on the basis of the optimized molecular structures to acquire 3480 molecule descriptors; the organic compounds are divided into a training set and a verification set according to a ratio of 4:1, the training set is used for creating a predication model, and the verification set is used for external verification after model creation. The method has the advantages that the model is clear in application field and covers new pollutants, has good imitative effect, robustness and predication capability, and can effectively predict bio-concentration factors of different types of organic compounds; predication results of the method can provide important data support for risk assessment and management of the organic chemicals and are of great significance in ecological risk assessment.

Method for adopting quantitative structure-activity relationship model to predicting soil or sediment adsorption coefficients of organic compound

Abstract: The invention discloses a method for adopting a quantitative structure-activity relationship model to predicting soil or sediment adsorption coefficients of an organic compound. On the basis that a molecular structure of the organic compound is known, the soil or sediment adsorption coefficients of the organic compound can be quickly and efficiently predicted only by calculating a molecular descriptor with the molecular structure and applying a built QSAR (quantitative structure-activity relationship) model. The method is simple, quick, low in cost and capable of saving manpower, material resources and financial resources needed for experiment testing. Modeling is performed according to guidelines on building and using the QSAR model of the Organization for Economic Cooperation and Development, and a simple and transparent multiple linear regression analysis method is applied, so that easiness in understanding and applying is realized; the method has clear application domain, good fitting capacity, robustness and predicting capability; by the method, the soil or sediment adsorption coefficients of the organic compound in the application domain can be effectively predicted, and necessary basic data are provided for ecological risk evaluation and management of the compound; the method has important significance.

Effects of halogenation on binding interaction between halogenated thyroid disrupting chemicals and transthyretin

Abstract: Thyroid disrupting chemicals (TDCs) can compete for the binding sites of transport proteins with thyroid hormones (THs) and alter the homeostasis of THs. The halogen moieties in TDCs play key role in determining the interactions between TDCs and transthyretin (TTR). Herein, the effects of halogenation on the binding interaction was investigated by analyzing the TTR crystal structures, the TDCs-TTR complex from molecular simulation, and the relative competing potency of a chemical with T 4 binding to hTTR (log RP ). We found that the halogen moieties in TDCs can affect the binding interactions by forming halogen bonds and halogen-hydrogen bonds with TTR and through inductive effects and hydrophobic effects. The halogen bonds (mainly halogen-oxygen bonds) and halogen-hydrogen bonds enhance the binding between organic halogenated compounds and TTR. Besides, for the halogenated phenolic compounds, the inductive effect is a main factor determining the log RP values. The hydrophobic effect is a critical factor governing the interactions between non-ionizable compounds (e.g. polybrominated diphenyl ethers) and TTR.