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QSAR Study of Nickel-Schiff Base Complexes as Anti-bacterial Agents against Staphylococcus aureus

Domain:

healthcare

Record type:

paper
Creator:
AmeUzaIdr
Editor:
Dep
Publisher:
CCSDSci
Host:avatar
International audience Aim: To develop good and rational Quantitative Structure Activity Relationship (QSAR) mathematical models that can predict to a significant accuracy the anti-Staphylococcus aureus Minimum inhibitory concentration (MIC) of Ni-Schiff base complexes.Place and Duration of Study: Department of Chemistry (Physical Chemistry unit), Ahmadu Bello University, Zaria, Nigeria, between January and June 2015.Methodology: A set of 36 nickel-Schiff base complexes with their antibacterial activities in terms of minimum inhibitory concentration (MIC) against the gram-positive bacteria, Staphylococcus aureus were selected for 0D, 1D, 2D and 3D quantitative structure activity relationship (QSAR) analysis by means of Density Functional Theory (DFT) using the Becke’s three-parameter hybrid functional (B3LYP) and 6-31G* basis set. The computed descriptors were correlated with their experimental MIC. Genetic function approximation (GFA) method and Multi-linear regression analysis (MLR) was used to derive the most statistically significant QSAR model.Results: Among the obtained QSAR models, the most statistically significant one was a tri- parametric linear equation with the squared correlation coefficient R2 value of 0.9399, adjusted squared correlation coefficient R 2adj value of 0.9313 and Leave one out (LOO) cross validation coefficient (Q2) value of 0.9074. An external set was used for confirming the predictive power of the model, its R2pred = 0.9725.Conclusion: The QSAR results reveal that molecular size and polarity predominantly influence the anti-Staphylococcus aureus activity of the complexes. The wealth of information in this study will provide an insight to designing novel bioactive nickel-schiff base complexes that will curb the emerging trend of multi-drug resistant strain of Staphylococcus aureus.

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hal.science

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[INFO.INFO-IM]Computer Science [cs]/Medical Imaging

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