Volume 2, Issue 5, October 2017, Page: 36-46
Insilico Predictive Model for Anti-Microbial Properties of Ni (II)-Schiff Bases’ Complexes Against Staphylococcus aureus and Candida albicans
Ameji John Philip, Department of Chemistry, Ahmadu Bello University Zaria, Zaria, Nigeria
Haruna Idris Muhammad, Department of Chemistry, Audu Bako College of Agriculture Dambatta, Kano, Nigeria
Raji Saheed Akinleye, Chemical Engineering Department, Ladoke Akintola University of Technology, Ogbomosho, Nigeria
Awor George Okorn, Department of Chemistry, Ahmadu Bello University Zaria, Zaria, Nigeria
Ibraheem Wasiu Aderemi, Department of Chemistry, Ahmadu Bello University Zaria, Zaria, Nigeria
Received: Sep. 10, 2017;       Accepted: Sep. 20, 2017;       Published: Oct. 17, 2017
DOI: 10.11648/j.ijbbmb.20170205.11      View  1234      Downloads  85
The emergence of multi-drug resistant strain of Staphylococcus aureus and Candida albicans has necessitated the exploration and development of newer structural moiety of Nickel-Schiff bases’ complexes as potential drug candidates against the aforementioned pathogens owing to their enormous inhibitory activity against these microbes. In this study, a Quantitative Structure Activity Relationship analysis was performed on some selected complexes by correlating their experimentally validated bioactivities against the pathogenic microbes with the OD, 1D, 2D and 3D descriptors of the molecules through linear regression resulting in the generation of three statistically significant models from which a hexa-parametric model was selected as the most robust model with R2 = 0.909, R2 adj = 0.890, Q2 = 0.844, R2ext = 0.609. The optimization model hinted the predominance of the size descriptors (WD. volume and nT6Ring), descriptors of hydrogen bond acceptor ability of the complexes (nHBAcc2 and nHBAcc3) and a descriptor of molecular polarity (Weta 3. polar) in influencing the observed anti-microbial activites of the complexes. The wealth of information in this study could provide a blueprint in the design of novel bioactive complexes that could curb the alarming trend of multi-drug resistant strain of Staphylococcus aureus and Candida albicans.
Staphylococcus aureus, Candida albicans, Descriptors, QSAR, Drug
To cite this article
Ameji John Philip, Haruna Idris Muhammad, Raji Saheed Akinleye, Awor George Okorn, Ibraheem Wasiu Aderemi, Insilico Predictive Model for Anti-Microbial Properties of Ni (II)-Schiff Bases’ Complexes Against Staphylococcus aureus and Candida albicans, International Journal of Biochemistry, Biophysics & Molecular Biology. Vol. 2, No. 5, 2017, pp. 36-46. doi: 10.11648/j.ijbbmb.20170205.11
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