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

A technology for organic chemicals and biological enrichment, applied in special data processing applications, instruments, electrical digital data processing, etc. The effect of cohesion and shortcut data support

Active Publication Date: 2014-04-30
DALIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The fitting effect and predictive ability of the local model are relatively high, but because it is constructed for a specific type of compound, it cannot meet the demand for a large number of different types of chemical data acquisition
Although the general model meets the needs of chemical management to quickly obtain different types of compounds, it still lacks a wide range of compounds covered. The model is simple, the prediction rules are transparent, and the mechanism is easy to explain. BCF-QSAR model with application domain characterization

Method used

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

Examples

Experimental program
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Effect test

Embodiment 1

[0026] Compound 1,2,3,6,7,8-hexachlorodibenzo-p-dioxin (CAS No. 57653-85-7) was randomly given, and its bioconcentration factor was predicted. First optimize the molecular structure of 1,2,3,6,7,8-hexachlorodibenzo-p-dioxin, and then calculate 12 descriptors MLOGP2, FO2[C-Cl] based on the optimized molecular structure , the values ​​of nROH, P-117, Mor25m, N%, X4v, O-058, LLS_01, H4v, SM12_AEA(dm), O-057 are 20.902, 12, 0, 0, 1.239, 0, 2.907, 0 , 0.67, 0.24, 8.004, 0. According to the formula (2), the Euclidean distance of the eigenvector is 0.514 (<1.438). Within the scope of the model application domain, this model can be used to predict 1,2,3,6,7,8-hexachlorobiphenyl And - for - the bioaccumulation factor of dioxin, the value of logBCF is 3.926 when the descriptor value is substituted into the built model, and the experimental value is 3.927, and the prediction result is good.

Embodiment 2

[0028] The compound bisphenol A (CAS No. 80-05-7) was randomly given, and its bioconcentration factor was predicted. First optimize the molecular structure of bisphenol A, and then based on the optimized molecular structure, calculate 12 kinds of descriptors MLOGP2, FO2[C-Cl], nROH, P-117, Mor25m, N%, X4v, O-058, LLS_01, The values ​​of H4v, SM12_AEA(dm), and O-057 are 10.928, 0, 0, 0, 0.375, 0, 1.923, 0, 0.83, 0.285, 6.164, and 2, respectively. According to the formula (2), the Euclidean distance of the eigenvector is 0.645 (<1.438). Within the scope of the model application domain, the model can be used to predict the bioconcentration factor of bisphenol A, and the descriptor value can be substituted into the established The model has a logBCF value of 1.639, of which the experimental value is 1.641, and the prediction result is good.

Embodiment 3

[0030] The compound 2,4,6-trichloroaniline (CAS No. 634-93-5) was randomly given, and its bioaccumulation factor was predicted. First optimize the molecular structure of 2,4,6-trichloroaniline, and then based on the optimized molecular structure, calculate 12 kinds of descriptors MLOGP2, FO2[C-Cl], nROH, P-117, Mor25m, N%, X4v, The values ​​of O-058, LLS_01, H4v, SM12_AEA(dm), and O-057 are 10.982, 6, 0, 0, 0.191, 7.1, 1.37, 0, 0.83, 0.077, 5.225, and 0, respectively. According to the formula (2), the Euclidean distance of the eigenvector is 0.267 (<1.438). Within the scope of the model application domain, this model can be used to predict the bioaccumulation factor of 2,4,6-trichloroaniline, which will Substituting the descriptor value into the built model has a logBCF value of 2.133, of which the experimental value is 2.001, and the prediction result is good.

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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.

Description

technical field [0001] The invention relates to a technique for predicting biological enrichment factors of organic chemicals by using a multiple linear regression algorithm to establish a quantitative structure-activity relationship (QSAR), and belongs to the field of ecological risk assessment test strategies. Background technique [0002] Some toxic substances can be bioaccumulated and passed through the food chain, posing a potential threat to human health. Bioaccumulation is a process of balanced distribution of chemical substances between living organisms and environmental media. A phenomenon in which the concentration exceeds that in the surrounding environment. The bioconcentration factor (BCF) can effectively evaluate the potential enrichment capacity of pollutants, which is defined as the ratio of the concentration in the organism to the concentration in the environmental medium when the pollutant reaches an equilibrium state. Understanding and determining the ac...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 乔显亮郑玉婷李雪花陈景文杨先海
Owner DALIAN UNIV OF TECH
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