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Novel nonlinear high-efficient model building method and application of phenols for toxicity prediction and evaluation of photogenic bacteria

A toxicity prediction, non-linear technique, applied in the field of chemistry

Inactive Publication Date: 2013-05-01
HUNAN AGRICULTURAL UNIV
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Problems solved by technology

Therefore, the current QSAR research on the toxicity of phenol analogs still faces many puzzles.

Method used

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  • Novel nonlinear high-efficient model building method and application of phenols for toxicity prediction and evaluation of photogenic bacteria
  • Novel nonlinear high-efficient model building method and application of phenols for toxicity prediction and evaluation of photogenic bacteria
  • Novel nonlinear high-efficient model building method and application of phenols for toxicity prediction and evaluation of photogenic bacteria

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Embodiment Construction

[0016] The method of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0017] Materials and methods

[0018] data set

[0019] According to the substituent types of 18 experimentally determined phenols reported in the prior art, we designed 13 virtual phenols for evaluation. The 18 experimental phenols and 13 virtual phenols are listed in Table 1. Bacteria were exposed to the tested phenol (in 3% NaCl solution) for 15 minutes and their toxicity values ​​were determined by MICROTOX tester. EC50 values ​​were calculated and converted to logarithmic EC50 (log EC 50 , mol L -1 ) for QSAR research. 18 log EC collected 50 Experimental value [Log EC 50 (expt.) ] between 2.220 and 5.870. In order to obtain a statistically robust QSAR model and compare the results with SLR and SVR, the 18 experimental phenolics in Table 1 were divided into a training set (15 compounds) and a test set accordi...

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Abstract

The invention discloses a novel nonlinear high-efficient model building method and application of phenols for toxicity prediction and evaluation of photogenic bacteria. A non-linear SVR (Sustained Virological Response) technology is utilized to carry out QSAR (Quantitative Structure Activity Relationship) research on the toxicity of the photogenic bacteria represented as logEC50 through eighteen phenol compounds in the prior art. The work aims to look for a more reliable QSAR model with more reasonable characteristics through a nonlinear chemometric tool based on low-dimension characteristic data and high-dimension characteristic data, and analyze in detail the most valuable model relative to the toxicity and the most important molecular characteristic thereof. The novel nonlinear high-efficient model building method and the application of the phenols for the toxicity prediction and evaluation of the photogenic bacteria provide effective theoretical references for the design of phenol analogues for strengthening or weakening the toxicity of the photogenic bacteria.

Description

technical field [0001] The invention belongs to the technical field of chemistry, and relates to a construction method and application of a novel nonlinear high-efficiency model for predicting and evaluating the toxicity of phenol to photobacteria. Background technique [0002] With the rapid development of the economy, the environmental problems related to chemicals have become increasingly prominent. Therefore, the toxicity risk assessment of organic pollutants is very important. Phenol is one of the most common environmental pollutants, especially in wastewater. Due to its toxicity and persistence in the environment, phenol is regarded as an environmental pollutant of priority concern. Bright luminous bacteria (Photobacterium phosphoreum) is a luminescent bacterium in seawater, and its light intensity varies with toxic substances inhibiting bacterial growth (i.e., cell density ) changes, making it an important indicator for chemical toxicity measurement and water quality...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 周玮袁哲明吴树波代志军陈渊韩娜
Owner HUNAN AGRICULTURAL UNIV
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