Center of Excellence In Genomic Medicine Research | Researches | Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression

Center of Excellence In Genomic Medicine Research

Document Details

Document Type	:	Article In Journal
Document Title	:	Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression
Document Language	:	English
Abstract	:	Toxicity evaluation is an extremely important process during drug development. It is usually initiated by experiments on animals, which is time-consuming and costly. To speed up such a process, a quantitative structure-activity relationship (QSAR) study was performed to develop a computational model for correlating the structures of 581 aromatic compounds with their aquatic toxicity to tetrahymena pyriformis. A set of 68 molecular descriptors derived solely from the structures of the aromatic compounds were calculated based on Gaussian 03, HyperChem 7.5, and TSAR V3.3. A comprehensive feature selection method, minimum Redundancy Maximum Relevance (mRMR)-genetic algorithm (GA)-support vector regression (SVR) method, was applied to select the best descriptor subset in QSAR analysis. The SVR method was employed to model the toxicity potency from a training set of 500 compounds. Five-fold cross-validation method was used to optimize the parameters of SVR model. The new SVR model was tested on an independent dataset of 81 compounds. Both high internal consistent and external predictive rates were obtained, indicating the SVR model is very promising to become an effective tool for fast detecting the toxicity.
ISSN	:	1949-2553
Journal Name	:	Oncotarget
Volume	:	8
Issue Number	:	30
Publishing Year	:	1438 AH 2017 AD
Article Type	:	Article
Added Date	:	Monday, July 1, 2019

Researchers

Researcher Name (Arabic)	Researcher Name (English)	Researcher Type	Dr Grade	Email
Qiang Su	Su, Qiang	Researcher	Doctorate
Wencong Lu	Lu, Wencong	Researcher	Doctorate
Dongshu Du	Du, Dongshu	Investigator	Doctorate	sdhzdds@163.com
Fuxue Chen	Chen, Fuxue	Investigator	Doctorate	chemfuxue@staff.shu.edu.cn
Bing Niu	Niu, Bing	Investigator	Doctorate	bniu@gordonlifescience.org
Kuo-Chen Chou	Chou, Kuo-Chen	Researcher	Doctorate

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