A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity.
The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA) and K-nearest neighbor (KNN), were employed in order to reduce dimensionality and investigate which subset of variables could be more effective for classifying the flavones according to their degree of anti-HIV-1 activity. The PCA, HCA, SDA and KNN studies showed that the variables log P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1.
Souza
Jaime
J
Departamento de Química e Física Molecular, Instituto de Química de São Carlos, Universidade de São Paulo, CP 780, 13560-970 São Carlos, SP, Brazil.
Santos
Regina Helena de Almeida
RH
Ferreira
Márcia Miguel Castro
MM
Molfetta
Fábio Alberto
FA
Camargo
Ademir João
AJ
Honório
Káthia Maria
KM
da Silva
Albérico Borges Ferreira
AB
D019380:Anti-HIV Agents / Q000737:chemistry*; D016000:Cluster Analysis; D005419:Flavonoids / Q000737:chemistry*; D025341:Principal Component Analysis / Q000379:methods*; D013329:Structure-Activity Relationship
D019380:Anti-HIV Agents; D005419:Flavonoids