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https://hdl.handle.net/1959.11/56010
Title: | Computational insights into the binding of pimodivir to the mutated PB2 subunit of the influenza A virus |
Contributor(s): | Arba, Muhammad (author); Ningsih, Aprilia Surya (author); Bande, La Ode Santiaji (author); Wahyudi, Setyanto Tri (author); Bui-Linh, Candice (author); Wu, Chun (author); Karton, Amir (author) |
Publication Date: | 2023-07-14 |
Early Online Version: | 2023-05-14 |
DOI: | 10.1080/08927022.2023.2210690 |
Handle Link: | https://hdl.handle.net/1959.11/56010 |
Abstract: | | Influenza A virus (IAV) is reported to develop Pimodivir resistance because of multiple mutations within the Polymerase basic 2 protein (PB2) of IAV. The lack of a high-resolution structure of these PB2 mutants complexed with Pimodivir hinders efforts to understand the drug resistance. Here we decipher the binding differences of Pimodivir in the wild-type and mutant systems Q306H, S324I, S324N, S324R, F404Y, and N510 T of IVA PB2 using homology modelling, molecular dynamics, molecular docking, and density functional theory simulations. The key residues responsible for Pimodivir binding were identified as Glu361, Arg355, Arg332, His357, and Phe323. Those mutations, mainly N510 T, result in significant conformational changes of Pimodivir in the PB2 active site. As a result, the affinity of Pimodivir is significantly reduced in the N510 T system. The mutation effects are less pronounced in the other mutant systems. Dynamic cross-correlation matrix (DCCM) analyses suggest that the singlepoint mutation N510 T produces an allosteric effect on the ligand-binding domain, thus reducing ligand-binding affinity. The present study reveals how a single-point mutation modulates the Pimodivir binding in IAV PB2, which provides important insights into designing new Pimodivir analogues with better binding affinities.
Publication Type: | Journal Article |
Source of Publication: | Molecular Simulation, 49(10), p. 1031-1043 |
Publisher: | Taylor & Francis |
Place of Publication: | United Kingdom |
ISSN: | 1029-0435 0892-7022 |
Fields of Research (FoR) 2020: | 340701 Computational chemistry |
Socio-Economic Objective (SEO) 2020: | 280120 Expanding knowledge in the physical sciences |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Science and Technology
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