QSAR analysis for heterocyclic antifungals.
We perform linear regression analyses on 1202 numerical descriptors that encode the various aspects of the topological, geometrical and electronic molecular structure with the aim of achieving the best QSAR relationship between the antifungal potencies against the Candida albicans strain and the structure of 96 heterocyclic ring derivatives. As a realistic application we employ the model found to predict the biological activity for 60 non-yet measured compounds.
Duchowicz
Pablo R
PR
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), División Química Teórica, Departamento de Química, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 1900 La Plata, Argentina. prduchowicz@yahoo.com.ar
Vitale
Martín G
MG
Castro
Eduardo A
EA
Fernández
Michael
M
Caballero
Julio
J
D000465:Algorithms; D000935:Antifungal Agents / Q000138:chemical synthesis* / Q000494:pharmacology*; D002176:Candida albicans / Q000187:drug effects; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D006571:Heterocyclic Compounds / Q000138:chemical synthesis* / Q000494:pharmacology*; D008826:Microbial Sensitivity Tests; D008958:Models, Molecular; D015233:Models, Statistical; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
D000935:Antifungal Agents; D006571:Heterocyclic Compounds