Molecular dynamics studies of human receptor molecule in hemagglutinin of 1918 and 2009 H1N1 influenza viruses

Lee, Angelina Noviani; Hartono, Yossa Dwi; Sun, Tiedong; Leow, Min Li; Liu, Xuewei; Huang, Xuri; Zhang, Dawei

doi:10.1007/s00894-010-0867-5

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…This was demonstrated by studies which show that amino acid substitutions increasing or decreasing charge respectively enhance or reduce receptor binding affinity and avidity [ 45 , 46 ]. Another study looking into molecular dynamics between HA and human receptor have found that mutations in HA affects the binding free energy involving electrostatic and non-polar interactions [ 47 ]. Polarizability, which concerns a molecule's ability to be polarized, would therefore play a part in determining the binding interaction of HA and human receptor.…”

Section: Discussionmentioning

confidence: 99%

Predicting host tropism of influenza A virus proteins using random forest

2014

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BackgroundMajority of influenza A viruses reside and circulate among animal populations, seldom infecting humans due to host range restriction. Yet when some avian strains do acquire the ability to overcome species barrier, they might become adapted to humans, replicating efficiently and causing diseases, leading to potential pandemic. With the huge influenza A virus reservoir in wild birds, it is a cause for concern when a new influenza strain emerges with the ability to cross host species barrier, as shown in light of the recent H7N9 outbreak in China. Several influenza proteins have been shown to be major determinants in host tropism. Further understanding and determining host tropism would be important in identifying zoonotic influenza virus strains capable of crossing species barrier and infecting humans.ResultsIn this study, computational models for 11 influenza proteins have been constructed using the machine learning algorithm random forest for prediction of host tropism. The prediction models were trained on influenza protein sequences isolated from both avian and human samples, which were transformed into amino acid physicochemical properties feature vectors. The results were highly accurate prediction models (ACC>96.57; AUC>0.980; MCC>0.916) capable of determining host tropism of individual influenza proteins. In addition, features from all 11 proteins were used to construct a combined model to predict host tropism of influenza virus strains. This would help assess a novel influenza strain's host range capability.ConclusionsFrom the prediction models constructed, all achieved high prediction performance, indicating clear distinctions in both avian and human proteins. When used together as a host tropism prediction system, zoonotic strains could potentially be identified based on different protein prediction results. Understanding and predicting host tropism of influenza proteins lay an important foundation for future work in constructing computation models capable of directly predicting interspecies transmission of influenza viruses. The models are available for prediction at http://fluleap.bic.nus.edu.sg.

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Section: Discussionmentioning

confidence: 99%

Predicting host tropism of influenza A virus proteins using random forest

2014

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“…The behavior of a human receptor bound to HA of the 1918 and a novel 2009 H1N1 influenza viruses was also studied by Lee and coworker [33]. Both 1918 and 2009 complexes were predicted to have a similar binding free energy (-7.30 and -8.04 kcal•mol -1 for 1918 and 2009, respectively).…”

Section: Ha-receptor Binding Specificitymentioning

confidence: 95%

Computational Studies of Influenza A Virus at Three Important Targets: Hemagglutinin, Neuraminidase and M2 Protein

Rungrotmongkol¹,

Yotmanee²,

Nunthaboot³

et al. 2011

CPD

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While the seasonal influenza viruses spreading around the world cause the annual epidemics, the recent outbreaks of influenza A virus subtype H5N1 and pandemic H1N1 have raised a global human health concerns. In this review, the applicability of computational techniques focused on three important targets in the viral life cycle: hemagglutinin, neuraminidase and M2 proton channel are summarized. Protein mechanism of action, substrate binding specificity and drug resistance, ligand-target interactions of substrate/inhibitor binding to these three proteins either wild-type or mutant strains are discussed and compared. Advances on the novel anti-influenza agents designed specifically to combat the avian H5N1 and pandemic H1N1 viruses are introduced. A better understanding of molecular inhibition and source of drug resistance as well as a set of newly designed compounds is greatly useful as a rotational guide for synthetic and medicinal chemists to develop a new generation of anti-influenza drugs.

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“…A novel combination of V135S and A138S was predicted to significantly increase the human receptor binding preference due to its high contribution of electrostatic interaction. Substitutions of serine at both positions 135 and 138 resulted in a conformational rearrangement in the HA-glycan binding area, therefore accommodating the stable hydrogen bonds between HA and SA-α-2,6-Gal receptor [24] . Further research showed that the tert-butyl hydroquinone (TBHQ) showed potent activity with IC50 values of 5 to 10 µM against the conformational rearrangement of H3N2 [25] .…”

Section: Computational Studiesmentioning

confidence: 99%

Computational analysis in Influenza virus

Chavan

Bapat²,

Patil³

et al. 2017

Receptor Clin Invest

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Influenza viruses are major human pathogens accountable for respiratory diseases affecting millions of people worldwide and characterized by high morbidity and significant mortality. Influenza infections can be controlled by vaccination and antiviral drugs. However, vaccines need yearly updating and give limited protection. In addition, the currently available drugs suffer from the rapid and extensive emergence of drug resistance. All this highlights the urgent need for developing new antiviral strategies with novel mechanisms of action and with reduced drug resistance potential. Recent advances in the understanding of Influenza virus replication have discovered a number of cellular drug targets that counteract viral drug resistance. With expanded bioinformatics' knowledge on computational modeling and molecular dynamic stimulations, novel small molecule inhibitors of herbal/ayurvedic origin are being explored due to their non-toxicity and affordability. Using in-silico techniques the structural details and information of influenza protein have been studied to identify the potential drugs for inhibition. Further, we have discussed the various computational studies carried out on major protein/targets of Influenza which could provide new clues for a newer class of antiviral (ayurvedic) drugs. In the years to come ahead, the influenza treatment will go through major changes, with advancing our knowledge of pathogenesis as new methods becoming clinically validated.

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Molecular dynamics studies of human receptor molecule in hemagglutinin of 1918 and 2009 H1N1 influenza viruses

Cited by 4 publications

References 19 publications

Predicting host tropism of influenza A virus proteins using random forest

Predicting host tropism of influenza A virus proteins using random forest

Computational Studies of Influenza A Virus at Three Important Targets: Hemagglutinin, Neuraminidase and M2 Protein

Computational analysis in Influenza virus

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