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Quantitative structure activity relationship model for predicting water-phase reaction rate constant of organic matter and sulfuric acid free radical in water phase

A technology of reaction rate constant and quantitative structure, applied in measurement devices, computer materials science, electrical digital data processing, etc., can solve problems such as lack of calculation formulas, lack of models, difficulty in large batches, etc. The effect of low material consumption and good prediction ability

Active Publication Date: 2017-11-07
DALIAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

Inventions described in this patented technology allow us to accurately predict how different substances affect human health or environmental safety. These models have various features like accuracy, ease of implementation, flexibility, reliability, etc., making them useful tools for researchers studying harmful materials from industrial sources. They may be applied across diverse industries where there exist many potential threatening agents. Overall, they offer valuable insights into biological processes related to contamination mitigations.

Problems solved by technology

This patented technical problem addressed in this patents relates to developing new materials called AOSZroxons that could effectively treat harmful metals like chromium dioxyanions (Cr(OH)-Xa complex structures containing multiple atoms, specifically sulfoxides and nitrogen bases. These materials were developed through experiments conducted under specific conditions and found effective applications in industries where heavy metal contamination occurs frequently. However, current analyte measurement tools require long periods of experimentation and may result in errors due to factors other than just the presence of these agents themselves.

Method used

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  • Quantitative structure activity relationship model for predicting water-phase reaction rate constant of organic matter and sulfuric acid free radical in water phase
  • Quantitative structure activity relationship model for predicting water-phase reaction rate constant of organic matter and sulfuric acid free radical in water phase
  • Quantitative structure activity relationship model for predicting water-phase reaction rate constant of organic matter and sulfuric acid free radical in water phase

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] Randomly given carboxylic acid compound succinic acid (CAS No. 110-15-6), predict its value. First optimize the molecular structure of succinic acid, and then based on the optimized molecular structure, calculate 8 kinds of molecular descriptors AVS_B(p), E HOMO , GATS3m, SaaaC, nArNO 2 , the values ​​of MPC05, IC1 and SpMax_EA(dm) are 2.79, -11.506, 1.293, 0, 0, 1.609, 2.522, 0.334, respectively. h=0.036* , so the compound is in the application domain. Substituting the descriptor value into the built model, the calculation result is 6.72, the experimental value is 6.85, and the prediction result is good.

Embodiment 2

[0032] Randomly given the compound acrylonitrile (CAS No. 107-13-1) containing carbon-carbon double bond and cyano group, predict its value.

[0033] First optimize the molecular structure of acrylonitrile, and then based on the optimized molecular structure, calculate 8 kinds of molecular descriptors AVS_B(p), E HOMO , GATS3m, SaaaC, nArNO 2 , the values ​​of MPC05, IC1 and SpMax_EA(dm) are 3.081, -10.982, 0.903, 0, 0, 0, 2.128, 0.678, respectively. h=0.131* , so the compound is within the application domain of the model. Substituting the descriptor value into the built model, the calculation result is 7.90, the experimental value is 7.91, and the prediction result is good.

Embodiment 3

[0035] The antibiotic compound sulfathiazole (CAS No. 72-14-0) containing amino and sulfur atoms is randomly given, and its value.

[0036] First optimize the molecular structure of sulfathiazole, and then based on the optimized molecular structure, calculate 8 kinds of molecular descriptors AVS_B(p), E HOMO , GATS3m, SaaaC, nArNO 2 , the values ​​of MPC05, IC1 and SpMax_EA(dm) are 3.53, -8.886, 1.084, 0, 0, 3.555, 3.433, 0, respectively. h=0.032* , so the compound is within the application domain of the model. Substituting the descriptor value into the built model, the calculation result is 10.69, the experimental value is 10.44, and the prediction result is good.

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Abstract

The invention discloses a method for predicting the water-phase reaction rate constant of organic matter and a sulfuric acid free radical in a water phase through quantitative structure activity relationship. Based on a compound structure, a molecular descriptor with a structural feature is calculated, and by the adoption of a multiple linear regression method, a QSAR model of an organic compound kso4- is constructed. Establishment of the model strictly confirms to the constructing and using guideline of the QSAR model from organization for economic cooperation and development, the constructed model has a definite application field, contains 197 kinds of organic compounds of different structures, and contains compounds containing carbon-carbon double bonds, carbon-carbon triple bonds, a hydroxyl group, phenolic hydroxyl, a carbonyl group, an aldehyde group, a carboxy group, an ester group, an amide group, nitro, an amino group, a cyano-group, an ether bond, a disulfide bond, fluorine, chlorine, bromine, iodine, arsenium and other radical groups. The mode has good fitting capacity, robustness and predicting capacity, can rapidly and accurately predict the kso4- value of the organic compound, and reference is provided for application of an advanced oxidation process based on a sulfuric acid free radical.

Description

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Claims

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Application Information

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Owner DALIAN UNIV OF TECH
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