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Method for constructing quantitative structure-activity relationship model to predict silicone oil-air partition coefficient of hydrophobic compound

A technique for hydrophobic compounds and quantitative structure-activity relationships, applied in chemical data mining, chemical statistics, chemical machine learning, etc. It is easy to understand and apply, save manpower, and low cost.

Active Publication Date: 2017-12-26
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] At present, it is used at home and abroad to predict K SiO / A The QSAR method is rare. In the document "Chemical Engineering Journal.2017,310:72-78", the functional group of the substance is distinguished, and the air-silicone oil partition coefficient P of each type of substance is established with the Wiener index as a single parameter. The QSAR model, the correlation coefficient R 2 is very close to 1, although the prediction model has its own characteristics, there are also some shortcomings
These deficiencies are mainly reflected in the following aspects: first, a single descriptor cannot comprehensively capture the physical and chemical properties of a large number of compounds, and a single correlation cannot be applied to all compounds; second, the descriptors used are not suitable for Mechanism explanation, and it is a more complex form of exponential or power; third, there are fewer data sets when building a model for each functional group, and the reliability is low; fourth, the obtained model does not include other organic compounds, and cannot be used for gas analysis. predict

Method used

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  • Method for constructing quantitative structure-activity relationship model to predict silicone oil-air partition coefficient of hydrophobic compound
  • Method for constructing quantitative structure-activity relationship model to predict silicone oil-air partition coefficient of hydrophobic compound
  • Method for constructing quantitative structure-activity relationship model to predict silicone oil-air partition coefficient of hydrophobic compound

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Dimethyl sulfide: First, check the molecular structure information of dimethyl sulfide on the organic small molecule biological activity database (PubChem), and then use the B3LYP / 6-311G** method in the quantum chemistry software Gaussian to calculate α, E LUMO -E HOMO These 2 descriptors. Its h is calculated by Williams graph method i The value is 0.024-3, indicating that this compound is within the application domain of the QSAR model constructed in the specific embodiment of the present invention.

[0056] Substituting into the constructed QSAR model, the logK of dimethyl sulfide SiO / A The experimental value is 2.15, and the prediction steps based on the QSAR model are as follows:

[0057] logK SiO / A =2.888+0.025×41.038–0.244×6.780=2.26

[0058] The error is only 0.11, which is in good agreement with the experimental value.

Embodiment 2

[0060] Dimethyl disulfide: first check the molecular structure information of dimethyl disulfide on PubChem, and then use the B3LYP / 6-311G** method in the quantum chemistry software Gaussian to calculate α, E LUMO -E HOMO These two descriptors; use the Williams graph method to calculate its h iThe value is 0.031-3, indicating that this compound is within the application domain of the QSAR model constructed in the specific embodiment of the present invention.

[0061] Substituting into the constructed QSAR model, the logK of dimethyl disulfide SiO / A The experimental value is 2.86, and the prediction steps based on the QSAR model are as follows:

[0062] logK SiO / A =2.888+0.025×61.192–0.244×5.736=3.02

[0063] The error is only 0.16, which is in good agreement with the experimental value.

Embodiment 3

[0065] 2-Chlorophenol: first check the molecular structure information of 2-chlorophenol on PubChem, and then use the B3LYP / 6-311G** method in the quantum chemistry software Gaussian to calculate α, E LUMO -E HOMO These two descriptors; use the Williams graph method to calculate its h i The value is 0.109<h*(warning value)=0.25, standard residual (SE)=1.633<3, indicating that this compound is within the application domain of the QSAR model constructed in the specific embodiment of the present invention.

[0066] Substituting into the constructed QSAR model, the logK of 2-chlorophenol SiO / A The experimental value is 4.25, and the prediction steps based on the QSAR model are as follows:

[0067] logK SiO / A =2.888+0.025×85.194–0.244×5.254=3.74

[0068] The error is only 0.51, which is in good agreement with the experimental value.

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Abstract

The invention discloses a method for constructing a quantitative structure-activity relationship model to predict a silicone oil-air partition coefficient of a hydrophobic compound. According to the method, the model is adopted for predicting the silicone oil-air partition coefficient, wherein logKSiO / A = 2.888 + 0.025 * alpha - 0.244 * (ELUMO-EHOMO), logKSiO / A represents the silicone oil-air partition coefficient, alpha represents an average molecular polarizability, and (ELUMO-EHOMO) represents an energy difference between a lowest unoccupied molecular orbit and a highest occupied molecular orbit. According to the method, the silicone oil-air partition coefficient of the hydrophobic compound can be quickly and efficiently predicted simply by calculating molecular descriptors with structural characteristics and applying the constructed QSAR model; the method is simple, quick and low in cost, and the labor, materials and financial resources needed for experimental tests can be saved.

Description

technical field [0001] The invention relates to the field of modeling prediction of the concentration ratio of compounds in the organic phase and the gas phase, in particular to a method for predicting the silicone oil-air partition coefficient (logK SiO / A )Methods. Background technique [0002] Many emerging biological processes involve secondary nonaqueous liquid phases, such as separating critical substrates or products to enhance interphase mass transfer, avoid concentration suppression, or in situ product extraction. Environmental biotechnology involves the use of microorganisms for various important biotransformations related to energy and the environment. In order to solve the problem of transferring hydrophobic substances from the gaseous state to the aqueous phase, some researchers have explored the addition of a second non-aqueous liquid phase to improve the gas Liquid mass transfer rate, two-phase partitioning bioreactor (TPPB) came into being, this non-aqueous p...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16C20/70
Inventor 马邕文渠艳飞万金泉王艳关泽宇闫志成
Owner SOUTH CHINA UNIV OF TECH
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