Rezaie keikhaie, Nasrin (2022) QSAR Modeling for Predicting Toxicity of Organic Chemicals to Tetrahymena Pyriformis Bacteria. Masters thesis, University of Zabol.
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Abstract
The chemicals hazard assessment is an important issue in environmental protection. However, there are many shortcomings in determining the empirical toxicity data, and there is a great way to achieve these methods. QSAR methods (quantitative structure-activity communication methods) have received special attention as an interesting complement or even an alternative to time-consuming and costly laboratory data. At present, QSAR establishes a relationship between the chemical structure of materials and various physical, chemical, and biological properties (including biopharmaceuticals, toxicology), and the obtained relation can be used to predict unmeasured or unknown properties. Additionally, modeling, testing and identifying new and biological active compounds in agriculture, industry and health leads to economic progress and improved quality of life. The widespread use of benzene derivatives in various industries, such as chemical industry, pharmaceuticals as solvents, insecticides, herbicides, etc leads to destructive effects of the environment around us, as well as the creation of environmental pollution in water and soil. From QSAR modeling in this research, will be used to obtain various structural parameters on the amount of organic chemical toxicity than tetrahymena pyriformis bacteria. The QSAR model for the desired compounds will be made using SMILES descriptors and Monte Carlo optimization method with Coral software. The simplified molecular structure to the symbol of the line (SMILES) specify the molecule to the linear form to describe chemical structures using ASCII strings. The Monte Carlo method is a computational algorithm that uses random sampling to calculate the results. The used compounds in this study are randomly divided into two series of training and testing. The best model is selected from among models based on statistics such as correlation coefficient and root of square trial error. The prediction of the toxicity of the test series compounds will be done by the QSAR model. The predictability of the created model is evaluated by cross-validation methods and calculation the prediction of test batch data prediction. Finally, this valid model will be used to predict the amount of toxicity of the unknown compounds.
| Item Type: | Thesis (Masters) |
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| Uncontrolled Keywords: | QSAR, toxicity, Tetrahymena Pyriformis, CORAL, Descriptor |
| Subjects: | Q Science > QD Chemistry |
| Depositing User: | Mrs najmeh khajeh |
| Date Deposited: | 01 Oct 2022 07:51 |
| Last Modified: | 01 Oct 2022 07:51 |
| URI: | http://eprints.uoz.ac.ir/id/eprint/3093 |
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