ArticleJournal of the American Chemical Society2009
Combining molecular dynamics with bayesian analysis to predict and evaluate ligand-binding mutations in influenza hemagglutinin.
Article in Journal of the American Chemical Society, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 35 citations in OpenAlex.
- Random forest algorithm reveals novel sites in HA protein that shift receptor binding preference of the H9N2 avian influenza virus.Virologica Sinica · 2025Article
- Friends and relatives: insight into conformational regulation from orthologues and evolutionary lineages using KIF and KIN.Faraday discussions · 2024Article
- Characterizing Receptor Flexibility to Predict Mutations That Lead to Human Adaptation of Influenza Hemagglutinin.Journal of chemical theory and computation · 2022Article
- Influenza hemagglutinin drives viral entry via two sequential intramembrane mechanisms.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness.PloS one · 2020Article
- Predicting allostery and microbial drug resistance with molecular simulations.Current opinion in structural biology · 2018Review
- All-atom virus simulations.Current opinion in virology · 2018Review
- Closely related, yet unique: Distinct homo- and heterodimerization patterns of G protein coupled chemokine receptors and their fine-tuning by cholesterol.PLoS computational biology · 2018Article
- Cholesterol enhances influenza binding avidity by controlling nanoscale receptor clustering.Chemical science · 2018Article
- Excess positional mutual information predicts both local and allosteric mutations affecting beta lactamase drug resistance.Bioinformatics (Oxford, England) · 2016Article
- Article
- Improving pandemic influenza risk assessment.eLife · 2014Article
- Molecular mechanisms of inhibition of influenza by surfactant protein D revealed by large-scale molecular dynamics simulation.Biochemistry · 2013Article
- Impact of mutations on the allosteric conformational equilibrium.Journal of molecular biology · 2013Article
- Carbohydrate force fields.Wiley interdisciplinary reviews. Computational molecular science · 2012Article
- Article
- Bringing molecules back into molecular evolution.PLoS computational biology · 2012Review
- Molecular-level simulation of pandemic influenza glycoproteins.Methods in molecular biology (Clifton, N.J.) · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Influenza virus attaches to and infects target cells via binding of cell-surface glycans by the viral hemagglutinin. This binding specificity is considered a major reason why avian influenza is typically poorly transmitted between humans, while swine influenza is better transmitted due to glycan similarity between the human and swine upper respiratory tract. Predicting mutations that control glycan binding is thus important to continued surveillance against new pandemic influenza strains. We have designed a molecular-dynamics approach for scoring potential mutants with predictive power for both receptor-binding-domain and allosteric mutations similar to those identified from clinical isolates of avian influenza. We have performed thousands of simulations of 17 different hemagglutinin mutants totaling >1 ms in length and employ a bayesian model to rank mutations that disrupt the stability of the hemagglutinin-ligand complex. Based on our simulations, we predict a significantly increased k(off) for seven of these mutants. This means of using molecular dynamics analysis to make experimentally verifiable predictions offers a potentially general method to identify ligand-binding mutants, particularly allosteric ones. Our analysis of ligand dissociation provides a means to evaluate mutants prior to experimental mutagenesis and testing and constitutes an important step toward understanding the determinants of ligand binding by H5N1 influenza.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.