QSPR Study of the Water Solubility of a Diverse Set of Agrochemicals : Hybrid ( GA / MLR ) Approach = Etude QSPR de la Solubilité Aqueuse d'un Ensemble de Divers Produits Agrochimiques : Approche Hybride ( AG / RLM )
| Autor: | Hamza Haddag, Nabil Bouarra, Amel Bouakkadia, Djelloul Messadi |
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| Rok vydání: | 2016 |
| Předmět: |
Quantitative structure–activity relationship
Correlation coefficient Feature selection 02 engineering and technology 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences 0104 chemical sciences Set (abstract data type) Test set Molecular descriptor Ordinary least squares Linear regression Econometrics 0210 nano-technology Biological system Mathematics |
| Zdroj: | Synthèse : Revue des Sciences et de la Technologie. :12-21 |
| ISSN: | 1111-4924 |
| DOI: | 10.12816/0027948 |
| Popis: | A quantitative structure- property relationship (QSPR) was performed for the prediction of the aqueous solubility of pesticides belonging to four chemical classes: acid, urea, triazine, and carbamate. The entire set of 77 pesticides was divided into a training set of 58 pesticides and a test set of 19 pesticides according to the Snee technique. A six descriptor model, with squared correlation coefficient (R 2 ) of 0.8895 and standard error of estimation (s) of 0.52 log unit, was developed by applying multiple linear regression analysis using the ordinary least square regression method and genetic algorithm- variable subset selection. The reliability of the proposed model was further illustrated using various evaluation techniques: leave- one- out cross- validation, bootstrap, randomization tests, and validation through the test set. |
| Databáze: | OpenAIRE |
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