Abstract

Objective: Neuraminidase is an enzyme aspartic protease that is essential for the life cycle of H1N1. Methods: Constructed a model of Neuraminidase enzyme the 3D structure as template using with Modeller software. The Neuraminidase enzyme model was predicted and validated by Procheck, What check, Errat, Verify-3D and AutoDock web server for reliability. Results: The Modeller homology-modeling algorithm was demonstrated excellent accuracy in blind predictions. The Neuraminidase enzyme model built with little, 35% identity could be accurate enough to be successfully used in receptor based rational drug design. The closest homologue with the highest sequence identity 100% was selected. Zanamivir drug and analogues were retrieved from PubChem database, as well as subjected to docking interaction with Neuraminidase enzyme used AutoDock programme. Based on the root mean square deviation and lowest binding energy values the best docking orientation was selected. The better lowest binding energy value -6.91 was selected of CID_25209232. Conclusions: This study will be used in broad screening of inhibitors of the protein. However, further implemented experimental and clinical verification is needed to establishment these analogues as drug

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