Open AccessIn silico molecular modeling of neuraminidase enzyme H1N1 avian influenza virus and docking with zanamivir ligands
Author(s) -
Ramachandran Muthiyan,
Balwyn Nambikkairaj,
Manly bakyavathy
Publication year - 2012
Publication title -
asian pacific journal of tropical disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 33
ISSN - 2222-1808
DOI - 10.1016/s2222-1808(12)60094-2
Subject(s) - zanamivir , autodock , modeller , neuraminidase , docking (animal) , in silico , pubchem , homology modeling , enzyme , computational biology , chemistry , biochemistry , biology , medicine , nursing , disease , pathology , covid-19 , infectious disease (medical specialty) , gene
Objective: Neuraminidase is an enzyme aspartic protease that is essential for the life cycle of\udH1N1. Methods: Constructed a model of Neuraminidase enzyme the 3D structure as template\udusing with Modeller software. The Neuraminidase enzyme model was predicted and validated\udby Procheck, What check, Errat, Verify-3D and AutoDock web server for reliability. Results:\udThe Modeller homology-modeling algorithm was demonstrated excellent accuracy in blind\udpredictions. The Neuraminidase enzyme model built with little, 35% identity could be accurate\udenough to be successfully used in receptor based rational drug design. The closest homologue\udwith the highest sequence identity 100% was selected. Zanamivir drug and analogues were\udretrieved from PubChem database, as well as subjected to docking interaction with Neuraminidase\udenzyme used AutoDock programme. Based on the root mean square deviation and lowest binding\udenergy values the best docking orientation was selected. The better lowest binding energy value\ud-6.91 was selected of CID_25209232. Conclusions: This study will be used in broad screening of\udinhibitors of the protein. However, further implemented experimental and clinical verification is\udneeded to establishment these analogues as drug