Abstract
The molecular orbital semi-empirical method PM3 is employed to calculate a set of molecular properties (variables) of 21 flavonoid compounds with anti-HIV activity. Pattern recognition techniques, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed in order to reduce dimensionality, and investigate which subset of variables would be more effective in classifying the flavonoid compounds according to their degree of anti-HIV activity. The principal component and hierarchical cluster studies showed that the variables LUMO (the energy of the lowest unoccupied molecular orbital), χ (electronegativity), and Q2, Q3 and Q7 (charges on atoms 2, 3 and 7) are related to the compounds with higher anti-HIV activity. These variables keep the more active flavonoids clustered together and separate them from those less active when principal component analysis and hierarchical cluster analysis are employed.
Published Version
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