Abstract

The objective of this research was to create a 3D-QSAR CoMFA model for a set of twenty-five neuraminidase inhibitors containing thiazolidine-4-carboxylic acid derivatives and to identify a new potent neuraminidase inhibitor for the treatment of influenza. The statistical parameters of the generated model are excellent: Q2 = 0.708, R2 = 0.997. The external validation results were (r2 0 = 0.922, K= 1.016, R2 pred = 0.674, r2 m= 0.778) indicating that the constructed model has good predictive power. Based on the contour map of the CoMFA model, we were able to propose six novel compounds with higher neuraminidase inhibitory activity than the most active compound. The six proposed molecules were submitted to molecular docking to analyse the bindings formed between the newly designed molecules and the neuraminidase. All of the proposed molecules were found to be more stable on the active site of neuraminidase than the reference molecule (1SJ). SwissADME was used to estimate the pharmacokinetic properties of each proposed molecule, while ProToxII and VEGA QSAR were used to investigate any potential toxicity. Finally, a reaction mechanism for synthesizing the six proposed compounds was described, which could potentially be explored further in the search for novel neuraminidase inhibitors. In conclusion, this study has identified potential candidates for the development of more effective neuraminidase inhibitors for the treatment of influenza.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call