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Molecular Classification of 5-Amino-2-Aroylquinolines and 4-Aroyl-6,7,8-Trimethoxyquinolines as Highly Potent Tubulin Polymerization Inhibitors

Molecular Classification of 5-Amino-2-Aroylquinolines and 4-Aroyl-6,7,8-Trimethoxyquinolines as Highly Potent Tubulin Polymerization Inhibitors

Francisco Torrens, Gloria Castellano
Copyright: © 2013 |Volume: 3 |Issue: 2 |Pages: 26
ISSN: 2155-4110|EISSN: 2155-4129|EISBN13: 9781466633629|DOI: 10.4018/ijcce.2013070101
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MLA

Torrens, Francisco, and Gloria Castellano. "Molecular Classification of 5-Amino-2-Aroylquinolines and 4-Aroyl-6,7,8-Trimethoxyquinolines as Highly Potent Tubulin Polymerization Inhibitors." IJCCE vol.3, no.2 2013: pp.1-26. http://doi.org/10.4018/ijcce.2013070101

APA

Torrens, F. & Castellano, G. (2013). Molecular Classification of 5-Amino-2-Aroylquinolines and 4-Aroyl-6,7,8-Trimethoxyquinolines as Highly Potent Tubulin Polymerization Inhibitors. International Journal of Chemoinformatics and Chemical Engineering (IJCCE), 3(2), 1-26. http://doi.org/10.4018/ijcce.2013070101

Chicago

Torrens, Francisco, and Gloria Castellano. "Molecular Classification of 5-Amino-2-Aroylquinolines and 4-Aroyl-6,7,8-Trimethoxyquinolines as Highly Potent Tubulin Polymerization Inhibitors," International Journal of Chemoinformatics and Chemical Engineering (IJCCE) 3, no.2: 1-26. http://doi.org/10.4018/ijcce.2013070101

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Abstract

Algorithms for classification and taxonomy are proposed based on criteria as information entropy and its production. It is classified a series of 5-amino-2-aroylquinolines (AAQs) and 4-aroyl-6,7,8-trimethoxyquinolines (TMQs) combretastatin analogues for anti-cancer activity. 5-Amino-6-methoxy-2-aroylquinoline AAQ showed anti-proliferative activity more potent as compared to combretastatin A-4 (CA4), against various human cancer cell lines and a multidrug resistance (MDR) cancer cell line. On the basis of AAQ/TMQ structure–activity relationship new derivatives are designed. The AAQs/TMQs are classified using nine characteristic chemical properties in molecules. Many classification algorithms are based on information entropy. When applying the procedures to sets of moderate size, an excessive number of results appear compatible with data and suffer a combinatorial explosion. However, after equipartition conjecture, one has a selection criterion between different variants resulting from classification between hierarchical trees. A classification of anti-cancer agents is obtained. The features denote positions R2–8 on the quinoline bicycle.

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