A molecular modelling approach to understand the effect of co-evolutionary mutations (V344M, I354L) identified in the PB2 subunit of influenza A 2009 pandemic H1N1 virus on m7GTP ligand binding

Bhoye, Dipali; Behera, Abhisek K.; Cherian, Sarah

doi:10.1099/jgv.0.000500

Cited by 5 publications

(3 citation statements)

References 58 publications

(56 reference statements)

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“…The largest of the polymerases, PB2, possessed nine fixed variants: R54K, M66I, D195N, R293K, R299K, V344M, I354L, S453T, and V731I. Of these, I354 and S453 lie in the cap-binding domain that is essential for the cap-snatching mechanism during the viral RNA transcription process [50] (Figure 1). Most of the sporadically detected variants in polymerases clustered in one patient suffering from enhanced respiratory symptoms including peribronchial markings and mucus accumulation in lungs.…”

Section: Mutation Analysismentioning

confidence: 99%

Inter-Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

et al. 2020

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The diversity of RNA viruses dictates their evolution in a particular host, community or environment. Here, we reported within- and between-host pH1N1virus diversity at consensus and sub-consensus levels over a three-year period (2015–2017) and its implications on disease severity. A total of 90 nasal samples positive for the pH1N1 virus were deep-sequenced and analyzed to detect low-frequency variants (LFVs) and haplotypes. Parallel evolution of LFVs was seen in the hemagglutinin (HA) gene across three scales: among patients (33%), across years (22%), and at global scale. Remarkably, investigating the emergence of LFVs at the consensus level demonstrated that within-host virus evolution recapitulates evolutionary dynamics seen at the global scale. Analysis of virus diversity at the HA haplotype level revealed the clustering of low-frequency haplotypes from early 2015 with dominant strains of 2016, indicating rapid haplotype evolution. Haplotype sharing was also noticed in all years, strongly suggesting haplotype transmission among patients infected during a specific influenza season. Finally, more than half of patients with severe symptoms harbored a larger number of haplotypes, mostly in patients under the age of five. Therefore, patient age, haplotype diversity, and the presence of certain LFVs should be considered when interpreting illness severity. In addition to its importance in understanding virus evolution, sub-consensus virus diversity together with whole genome sequencing is essential to explain variabilities in clinical outcomes that cannot be explained by either analysis alone.

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Section: Mutation Analysismentioning

confidence: 99%

Inter-Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

et al. 2020

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“…Given the essential and multi-functional roles of influenza A proteins, there are many options when it comes to selecting an antiviral drug target(s), with almost all major proteins having been the subject of extensive investigation. Furthermore, molecular dynamics, docking and virtual screening protocols have also been combined as integrative strategies to identify influenza A inhibitors, and identify binding pockets [25][26][27][28] as shown in figure 2. These methods have also been applied after initial experimental work to analyse molecular interactions.…”

Section: Discovery Of Influenza a Inhibitors And Drug Targetsmentioning

confidence: 99%

Integrating molecular modelling methods to advance influenza A virus drug discovery

Patel

Kukol

2021

Drug Discovery Today

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“…The NA of H5N1 and pH1N1 with H274Y mutation significantly weakened the binding affinity for the anti-viral drug oseltamivir, which resulted from the loss of H-bond interactions between the oseltamivir and two residues of NA (178W and 152R) 14 . Moreover, co-mutations V344M and I354L in the PB2 subunit of pH1N1 enhanced binding affinity by creating additional H-bond contacts between PB2 cap binding domain and the pre-mRNA cap analogue m7GTP 15 . However, these researches, as stated, were specific to a few influenza subtypes and only covered a few of proteins.…”

Section: Introductionmentioning

confidence: 99%

Hydrogen Bond Variations of Influenza A Viruses During Adaptation in Human

Luo

Deng

Ding

et al. 2017

Sci Rep

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Many host specific mutations have been detected in influenza A viruses (IAVs). However, their effects on hydrogen bond (H-bond) variations have rarely been investigated. In this study, 60 host specific sites were identified in the internal proteins of avian and human IAVs, 27 of which contained mutations with effects on H-bonds. Besides, 30 group specific sites were detected in HA and NA. Twenty-six of 36 mutations existing at these group specific sites caused H-bond loss or formation in at least one subtype. The number of mutations in isolations of 2009 pandemic H1N1, human-infecting H5N1 and H7N9 varied. The combinations of mutations and H-bond changes in these three subtypes of IAVs were also different. In addition, the mutations in isolations of H5N1 distributed more scattered than those in 2009 pandemic H1N1 and H7N9. Eight wave specific mutations in isolations of the fifth H7N9 wave were also identified. Three of them, R140K in HA, Y170H in NA, and R340K in PB2, were capable of resulting in H-bond loss. As mentioned above, these host or group or wave specific H-bond variations provide us with a new field of vision for understanding the changes of structural features in the human adaptation of IAVs.

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A molecular modelling approach to understand the effect of co-evolutionary mutations (V344M, I354L) identified in the PB2 subunit of influenza A 2009 pandemic H1N1 virus on m7GTP ligand binding

Cited by 5 publications

References 58 publications

Inter-Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

Inter-Versus Intra-Host Sequence Diversity of pH1N1 and Associated Clinical Outcomes

Integrating molecular modelling methods to advance influenza A virus drug discovery

Hydrogen Bond Variations of Influenza A Viruses During Adaptation in Human

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