3D-QSAR CoMFA study of some Heteroarylpyrroles as Possible Anticandida Agents

A three dimensional quantitative structure-activity relationship study using the comparative molecular field analysis method was performed on a series of 3-aryl-4-[alpha-(1H-imidazol-1-yl) aryl methyl] pyrroles for their anticandida activity. This study was performed using 40 compounds, for which co...

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Bibliographic Details
Published in:Indian journal of pharmaceutical sciences 2008-03, Vol.70 (2), p.154-158
Main Authors: Sharma, P C, Sharma, S V, Sharma, Archana, Suresh, B
Format: Article
Language:English
Subjects:
Antifungal agents
Candidiasis
Dosage and administration
Drug therapy
Fungal infections
Health aspects
Polyhedra
Pyrrole
Research Paper
Standard deviation
Studies
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Summary:A three dimensional quantitative structure-activity relationship study using the comparative molecular field analysis method was performed on a series of 3-aryl-4-[alpha-(1H-imidazol-1-yl) aryl methyl] pyrroles for their anticandida activity. This study was performed using 40 compounds, for which comparative molecular field analysis models were developed using a training set of 33 compounds. Database alignment of all 33 compounds was carried out by root-mean-square fit of atoms and field fit of the steric and electrostatic molecular fields. The resulting database was analyzed by partial least squares analysis with cross-validation; leave one out and no validation to extract optimum number of components. The analysis was then repeated with bootstrapping to generate the quantitative structure-activity relationship models. The predictive ability of comparative molecular field analysis model was evaluated by using a test set of 7 compounds. The 3D- quantitative structure-activity relationship model demonstrated a good fit, having r(2) value of 0.964 and a cross validated coefficient r(2) value as 0.598. Further comparison of the coefficient contour maps with the steric and electrostatic properties of the receptor has shown a high level of compatibility and good predictive capability.
ISSN:0250-474X
1998-3743
DOI:10.4103/0250-474X.41447