Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity

Intra-host diversities of the receptor-binding domain of stork faeces-derived avian H5N1 viruses and its significance as predicted by molecular dynamic simulation

Virus evolution facilitates the emergence of viruses with unpredictable impacts on human health. This study investigated intra-host variations of the receptor-binding domain (RBD) of the haemagglutinin (HA) gene of the avian H5N1 viruses obtained from the 2004 and 2005 epidemics. The results showed that the mutation frequency of the RBD ranged from 0.3 to 0.6 %. The mutations generated one consensus and several minor populations. The consensus population of the 2004 epidemic was transmitted to the 2005 outbreak with increased frequency (39 and 45 %, respectively). Molecular dynamics simulation was applied to predict the significance of the variants. The results revealed that the consensus sequence (E218K/V248I) interacted unstably with sialic acid (SA) with an α2,6 linkage (SAα2,6Gal). Although the mutated K140R/E218K/V248I and Y191C/E218K/V248I sequences decreased the HA binding capacity to α2,3-linked SA, they were shown to bind α2,6-linked SA with increased affinity. Moreover, the substitutions at aa 140 and 191 were positive-selection sites. These data suggest that the K140R and Y191C mutations may represent a step towards human adaptation of the avian H5N1 virus.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Using a mutual information-based site transition network to map the genetic evolution of influenza A/H3N2 virus

MOTIVATION

Mapping the antigenic and genetic evolution pathways of influenza A is of critical importance in the vaccine development and drug design of influenza virus. In this article, we have analyzed more than 4000 A/H3N2 hemagglutinin (HA) sequences from 1968 to 2008 to model the evolutionary path of the influenza virus, which allows us to predict its future potential drifts with specific mutations.

RESULTS

The mutual information (MI) method was used to design a site transition network (STN) for each amino acid site in the A/H3N2 HA sequence. The STN network indicates that most of the dynamic interactions are positioned around the epitopes and the receptor binding domain regions, with strong preferences in both the mutation sites and amino acid types being mutated to. The network also shows that antigenic changes accumulate over time, with occasional large changes due to multiple co-occurring mutations at antigenic sites. Furthermore, the cluster analysis by subdividing the STN into several subnetworks reveals a more detailed view about the features of the antigenic change: the characteristic inner sites and the connecting inter-subnetwork sites are both responsible for the drifts. A novel five-step prediction algorithm based on the STN shows a reasonable accuracy in reproducing historical HA mutations. For example, our method can reproduce the 2003-2004 A/H3N2 mutations with approximately 70% accuracy. The method also predicts seven possible mutations for the next antigenic drift in the coming 2009-2010 season. The STN approach also agrees well with the phylogenetic tree and antigenic maps based on HA inhibition assays.

AVAILABILITY

All code and data are available at http://ibi.zju.edu.cn/birdflu/.