Author(s): Anil K. Srivastava et al
Journal: International Journal of Pharmaceutical Sciences and Research
ISSN 0975-8232
Volume: 3;
Issue: 9;
Start page: 3249;
Date: 2012;
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Keywords: Anti-amoebic activity | PM5 | MLR | QSAR models
ABSTRACT
In quest of better anti-amoebic agents, quantitative structure-activity relationship (QSAR) studies were performed on a series of pyrazoline & dioxazoles derivatives with the help of PM5 calculations and geometry optimizations using CAChe software. Multiple Linear Regression (MLR) analysis was performed to derive QSAR models using the descriptors, molecular weight (MW), conformation minimum energy (ɛ), HOMO energy (HOMO), shape index, basic kappa second order (k2), absolute hardness (h), electronegativity (c), electrophilicity index (ω), molar volume (MV), molar refractivity (MR), LogP (LP), parachor (Pc) and solvent accessibility surface area (SASA). The QSAR models equations of anti-amoebic agents have been developed by using maximum of seven descriptors, in which conformation minimum energy, shape index, molar volume and parchor were present have good predictive powers of correlation coefficients. These models can successfully predict the anti-amoebic activity of any newly discovered pyrazoline and dioxazole derivatives which can later be tested in laboratory.
Journal: International Journal of Pharmaceutical Sciences and Research
ISSN 0975-8232
Volume: 3;
Issue: 9;
Start page: 3249;
Date: 2012;
VIEW PDF


Keywords: Anti-amoebic activity | PM5 | MLR | QSAR models
ABSTRACT
In quest of better anti-amoebic agents, quantitative structure-activity relationship (QSAR) studies were performed on a series of pyrazoline & dioxazoles derivatives with the help of PM5 calculations and geometry optimizations using CAChe software. Multiple Linear Regression (MLR) analysis was performed to derive QSAR models using the descriptors, molecular weight (MW), conformation minimum energy (ɛ), HOMO energy (HOMO), shape index, basic kappa second order (k2), absolute hardness (h), electronegativity (c), electrophilicity index (ω), molar volume (MV), molar refractivity (MR), LogP (LP), parachor (Pc) and solvent accessibility surface area (SASA). The QSAR models equations of anti-amoebic agents have been developed by using maximum of seven descriptors, in which conformation minimum energy, shape index, molar volume and parchor were present have good predictive powers of correlation coefficients. These models can successfully predict the anti-amoebic activity of any newly discovered pyrazoline and dioxazole derivatives which can later be tested in laboratory.