Document Detail


Linear and nonlinear quantitative structure-property relationship models for solubility of some anthraquinone, anthrone and xanthone derivatives in supercritical carbon dioxide.
MedLine Citation:
PMID:  18267136     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A quantitative structure-property relation (QSPR) study was conducted on the solubility in supercritical fluid carbon dioxide (SCF-CO2) of some recently synthesized anthraquinone, anthrone and xanthone derivatives. The data set consisted of 29 molecules in various temperatures and pressures, which form 1190 solubility data. The combined data splitting-feature selection (CDFS) strategy, which previously developed in our research group, was used as descriptor selection and model development method. Modeling of the relationship between selected molecular descriptors and solubility data was achieved by linear (multiple linear regression; MLR) and nonlinear (artificial neural network; ANN) methods. The QSPR models were validated by cross-validation as well as application of the models to predict the solubility of three external set compounds, which did not have contribution in model development steps. Both linear and nonlinear methods resulted in accurate prediction whereas more accurate results were obtained by ANN model. The respective root mean square error of prediction obtained by MLR and ANN models were 0.284 and 0.095 in the term of logarithm of g solute m(-3) of SCF-CO2. A comparison was made between the models selected by CDFS method and the conventional stepwise feature selection method. It was found that the latter produced models with higher number of descriptors and lowered prediction ability, thus it can be considered as an over-fitted model.
Authors:
Bahram Hemmateenejad; Mojtaba Shamsipur; Ramin Miri; Maryam Elyasi; Farzaneh Foroghinia; Hashem Sharghi
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-01-15
Journal Detail:
Title:  Analytica chimica acta     Volume:  610     ISSN:  1873-4324     ISO Abbreviation:  Anal. Chim. Acta     Publication Date:  2008 Mar 
Date Detail:
Created Date:  2008-02-12     Completed Date:  2008-08-07     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0370534     Medline TA:  Anal Chim Acta     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  25-34     Citation Subset:  IM    
Affiliation:
Medicinal & Natural Product Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. hemmatb@sums.ac.ir
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MeSH Terms
Descriptor/Qualifier:
Anthracenes / chemistry*
Anthraquinones / chemistry*
Carbon Dioxide / chemistry*
Models, Theoretical
Quantitative Structure-Activity Relationship
Solubility
Xanthones / chemistry*
Chemical
Reg. No./Substance:
0/Anthracenes; 0/Anthraquinones; 0/Xanthones; 124-38-9/Carbon Dioxide

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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