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A Method for Predicting the Skin Permeability Coefficient of Organic Chemicals

A technology of organic chemicals and skin penetration, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as unfavorable model application and mechanism interpretation, inability to extract prediction rules, poor comprehensibility, etc., to facilitate analysis and practical application, wide coverage of activity, strong predictive ability

Active Publication Date: 2018-06-15
NANJING INST OF ENVIRONMENTAL SCI MINIST OF ECOLOGY & ENVIRONMENT OF THE PEOPLES REPUBLIC OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the neural network is a black box operation, and the prediction rules cannot be extracted. There may be a contradiction between the prediction ability and the training ability, and the incomprehensibility is poor, which is not conducive to the application of the model and the explanation of the mechanism.

Method used

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  • A Method for Predicting the Skin Permeability Coefficient of Organic Chemicals
  • A Method for Predicting the Skin Permeability Coefficient of Organic Chemicals
  • A Method for Predicting the Skin Permeability Coefficient of Organic Chemicals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] Example 1: The given chemical substance 6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine (SMILES: CCNclnc(Cl)nc(NC(C )C)n1), predict its skin permeability coefficient.

[0037] First, according to the molecular structure of the chemical substance, seven descriptors BEHm8, GGI2, RDF030v, Mor17v, G2s, H5m, and RTu+ were calculated using Dragon software; they were 1.893, 0.667, 0.959, -0.171, 0.208, 0.034, and 0.151, respectively. Hat is 0.213, within the scope of the model application domain, this model can be used for the skin permeability coefficient of 6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine For prediction, the descriptor values ​​are substituted into the built model as follows:

[0038] Log Fl=–0.323+1.893*(-0.51007)+0.667*(-0.31582)+0.959*(-0.06401)

[0039] -0.171*(-2.17293)+0.208*(-0.44581)+0.034*1.58672+0.151*2.54638=-1.83

[0040] Then 6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine is predicted to be -1.83, and the experim...

Embodiment 2

[0042] Prediction of skin permeability coefficient given 1,1,1-trichloroethane (SMILES: CC(Cl)(Cl)Cl). First, according to the molecular structure of the chemical substance, use Dragon software to calculate 7 kinds of descriptors BEHm8, GGI2, RDF030v, Mor17v, G2s, H5m, RTu+, which are 0, 0, 1.253, -0.044, 0.536, 0, 0.219, and Hat is 0.038 , within the scope of the model application domain, this model can be used to predict the skin permeability coefficient of 1,1,1-trichloroethane, and the descriptor values ​​are substituted into the built model as follows:

[0043] Log Fl=–0.323+0*(-0.51007)+0*(-0.31582)+1.253*(-0.06401)-0.044*(-2.17293)+

[0044] 0.536*(-0.44581)+0*1.58672+0.219*2.54638=0.23

[0045] Then 1,1,1-trichloroethane is predicted to be 0.23, and the experimental value is 0.21, which is close to the experimental results.

Embodiment 3

[0047] Given O,O-dimethyl-O-(2,4,5-trichlorophenyl)phosphorothioate (SMILES: COP(=S)(OC)Oc1cc(c(cc1Cl)Cl)Cl) prediction its skin permeability coefficient. First, according to the molecular structure of the chemical substance, use the Dragon software to calculate 7 kinds of descriptors BEHm8, GGI2, RDF030v, Mor17v, G2s, H5m, RTu+, respectively 2.335, 2.667, 2.392, 0.078, 0.222, 1.087, 0.185, Hat is 0.565, Not within the scope of the model's application domain. Since the scope of application of the model is analyzed and displayed with leverage and Williams diagrams. The abscissa of the Williams diagram is the leverage value (hat), and the ordinate is the standard residual (σ), from which we can see the X exception point and the Y exception point. There are no Y exception points in the Williams diagram training set and verification set data of the model, and there are no X exception points in the verification set data. Compound 20, compound 62 and compound 63 in the training s...

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Abstract

The invention relates to the field of health risk assessment testing strategies, in particular to a method for predicting the skin permeability coefficient of organic chemicals. On the basis of obtaining the molecular structure of the compound, the quantitative structure-activity relationship (QSAR) is used to construct a prediction model by calculating the descriptors that characterize the structural features. Compared with the traditional test method for measuring skin penetration parameters, it is in line with animal welfare protection and reduces test time and cost. , which can quickly and effectively predict the skin permeability coefficient. The present invention is strictly in accordance with the 5 standards proposed by the Organization for Economic Co-operation and Development (OECD) for the construction and use of QSAR models, by calculating the physical and chemical properties, electrical properties, topology and quantum chemical parameters of compounds as predictive descriptors, and using K-S grouping to The original data is classified, and 7 optimal descriptors are screened out. Using the clear, simple, fast, and transparent GA-MLR algorithm, the model application domain is clear, and it has good fitting effect, robustness, and predictive ability. The skin permeability coefficient prediction model can accurately and efficiently predict the skin permeability coefficient of compounds, and provides an effective method for the health hazard assessment of organic compounds.

Description

technical field [0001] The invention relates to the field of health risk assessment testing strategies, in particular to a method for predicting the skin permeability coefficient of organic chemicals. technical background [0002] Compounds that penetrate the body through the skin may produce symptoms such as skin irritation, inflammation and allergy. The skin is often exposed to compounds either consciously or unconsciously, for which reason skin absorbability of compounds is an important part of the safety evaluation process. The skin permeability coefficient is a key indicator for the risk assessment of skin contact with chemicals. In the REACH regulations, when the annual output or import volume exceeds 1t, all substances must be tested for skin sensitivity. When the annual output or import volume is less than 1t, the Classification and assessment of skin sensitivity can be based on available information, (Q)SAR, and cross-comparisons. [0003] According to the OECD ch...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 范德玲刘济宁王蕾汪贞周林军郭敏古文石利利
Owner NANJING INST OF ENVIRONMENTAL SCI MINIST OF ECOLOGY & ENVIRONMENT OF THE PEOPLES REPUBLIC OF CHINA
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