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Title
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Classification models for neocryptolepine derivatives as inhibitors of the -haematin formation
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Author
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Abstract
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| This paper describes the construction of a QSAR model to relate the structures of various derivatives of neocryptolepine to their anti-malarial activities. QSAR classification models were build using Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART), Partial Least Squares Discriminant Analysis (PLS-DA), Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Support Vector Machines for Classification (SVM-C), using four sets of molecular descriptors as explanatory variables. Prior to classification, the molecules were divided into a training and a test set using the duplex algorithm. The different classification models were compared regarding their predictive ability, simplicity, and interpretability. Both binary and multi-class classification models were constructed. For classification into three classes, CART and One-Against-One (OAO)-SVM-C were found to be the best predictive methods, while for classification into two classes, LDA, QDA and CART were. |
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Language
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English
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Source (journal)
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Analytica chimica acta. - Amsterdam, 1947, currens
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Publication
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Amsterdam
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2011
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ISSN
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0003-2670
[print]
1873-4324
[online]
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DOI
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10.1016/J.ACA.2011.04.019
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Volume/pages
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705
:1/2
(2011)
, p. 98-110
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ISI
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000295993900014
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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