QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS OF NOVEL PYRAZOLINE DERIVATIVES USING K NEAREST NEIGHBOUR MOLECULAR FIELD ANALYSIS METHOD
DOI:
https://doi.org/10.22159/ijpps.2017v9i12.19401Keywords:
3D-QSAR, MCD inhibitors, kNN-MFA model, Stepwise variable selection methodAbstract
Objective: Malonyl CoA decarboxylase (MCD) enzyme plays important role in fatty acid and glucose oxidation. Inhibition of MCD might turn to a novel approach to treat ischemia. The main objective of this research article was to develop a novel pharmacophore for enhanced activity.
Methods: Three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed for pyrazoline derivatives as MCD inhibitors using VLife MDS 4.6 software. The QSAR model was developed using the stepwise 3D-QSAR kNN-MFA method.
Results: The statistical results generated from kNN-MFA method indicated the significance and requirements for better MCD inhibitory activity. The information rendered by 3D-QSAR model may render to better understanding and designing of novel MCD inhibitors.
Conclusion: 3D-QSAR is an important tool in understanding the structural requirements for the design of novel and potent MCD inhibitors. It can be employed to design new drug discovery.
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References
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