QSPR Correlation of Melting Point for Drug Compounds Based on Different Sources of Molecular Descriptors

Five linear QSPR models for melting points (MP) of drug-like compounds are developed based on three different packages for molecular descriptor generation and a combined set of all descriptors. A data set of 323 gaseous, liquid, and solid compounds was used for this study. Two models from the combin...

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Bibliographic Details
Published in:Journal of chemical information and modeling 2006-03, Vol.46 (2), p.930-936
Main Authors: Modarresi, Hassan, Dearden, John C, Modarress, Hamid
Format: Article
Language:English
Subjects:
Correlation analysis
Databases as Topic
Genetic algorithms
Models, Chemical
Molecular biology
Pharmaceutical Preparations - chemistry
Quantitative Structure-Activity Relationship
Regression analysis
Transition Temperature
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Summary:Five linear QSPR models for melting points (MP) of drug-like compounds are developed based on three different packages for molecular descriptor generation and a combined set of all descriptors. A data set of 323 gaseous, liquid, and solid compounds was used for this study. Two models from the combined set of descriptors based on stepwise regression and genetic algorithm (GA) descriptor selection methods have acceptable prediction abilities. The statistical results of these models are r 2 = 0.673 and root-mean-square error (RMSE) of 40.4 °C for stepwise regression-based quantitative structure−property relationships (QSPRs) and r 2 = 0.660 and RMSE of 41.1 °C for GA-based QSPRs. Interpretation of descriptors of all models showed a strong correlation of hydrogen bonding and molecular complexity with melting points of drug-like compounds.
ISSN:1549-9596
1549-960X
DOI:10.1021/ci050307n