As enzymes evolve and diverge from common ancestor sequences, they often keep their overall reaction chemistry but specialise in the binding of different cognate ligands. This study borrows methods for the computational assessment of 2D similarity of small molecules from the field of chemoinformatics, to examine the extent of structure conservation of cognate ligands binding to similar proteins. Proteins from 87 structural superfamilies from Escherichia coli form the core dataset, which is extended using homologues with functional assignments from any organism. We find that correlation of the substrate similarity with protein similarity (measured by either sequence-based or structure-based scores) can only be clearly established for very similar proteins. At low sequence identities, the superfamily to which a protein belongs can give helpful clues to its function, and more importantly, the confidence attached to such clues is superfamily-dependent. Our data indicate that only a few superfamilies show great substrate diversity, and that most exhibit conservation of at least part of the structural scaffold of the substrate.

Comparing the structures of H3, H5 and H9 subtype haemagglutinins, we deduced a structural basis for including all 15 influenza subtypes in four clades. H3, H5 and H9 represent three of these clades; we now report the structure of an H7 HA as a representative of the fourth clade. We confirm the structure of the turn at the N-terminus of the conserved central alpha-helix of HA2, and the combination of ionisable residues near the "fusion peptide" as clade-specific features. We compare the structures of three H1 HAs with H5 HA in the same clade, to refine our previous classification and we confirm the division of the clades into two groups of two. We also show the roles of carbohydrate side chains in the esterase-fusion domain boundaries in the formation of clade-specific structural markers.

There are 15 subtypes of influenza A virus (H1-H15), all of which are found in avian species. Three caused pandemics in the last century: H1 in 1918 (and 1977), H2 in 1957 and H3 in 1968. In 1997, an H5 avian virus and in 1999 an H9 virus caused outbreaks of respiratory disease in Hong Kong. We have determined the three-dimensional structures of the haemagglutinins (HAs) from H5 avian and H9 swine viruses closely related to the viruses isolated from humans in Hong Kong. We have compared them with known structures of the H3 HA from the virus that caused the 1968 H3 pandemic and of the HA?esterase?fusion (HEF) glycoprotein from an influenza C virus. Structure and sequence comparisons suggest that HA subtypes may have originated by diversification of properties that affected the metastability of HAs required for their membrane fusion activities in viral infection.

We present a statistical graphical model to infer specific molecular function for unannotated protein sequences using homology. Based on phylogenomic principles, SIFTER (Statistical Inference of Function Through Evolutionary Relationships) accurately predicts molecular function for members of a protein family given a reconciled phylogeny and available function annotations, even when the data are sparse or noisy. Our method produced specific and consistent molecular function predictions across 100 Pfam families in comparison to the Gene Ontology annotation database, BLAST, GOtcha, and Orthostrapper. We performed a more detailed exploration of functional predictions on the adenosine-5′-monophosphate/adenosine deaminase family and the lactate/malate dehydrogenase family, in the former case comparing the predictions against a gold standard set of published functional characterizations. Given function annotations for 3% of the proteins in the deaminase family, SIFTER achieves 96% accuracy in predicting molecular function for experimentally characterized proteins as reported in the literature. The accuracy of SIFTER on this dataset is a significant improvement over other currently available methods such as BLAST (75%), GeneQuiz (64%), GOtcha (89%), and Orthostrapper (11%). We also experimentally characterized the adenosine deaminase from Plasmodium falciparum, confirming SIFTER?s prediction. The results illustrate the predictive power of exploiting a statistical model of function evolution in phylogenomic problems. A software implementation of SIFTER is available from the authors.

We have determined the structure of the HA of an avian influenza virus, A/duck/Ukraine/63, a member of the same antigenic subtype, H3, as the virus that caused the 1968 Hong Kong influenza pandemic, and a possible progenitor of the pandemic virus. We find that structurally significant differences between the avian and the human HAs are restricted to the receptor-binding site particularly the substitutions Q226L and G228S that cause the site to open and residues within it to rearrange, including the conserved residues Y98, W153, and H183. We have also analyzed complexes formed by the HA with sialopentasaccharides in which the terminal sialic acid is in either alpha2,3- or alpha2,6-linkage to galactose. Comparing the structures of complexes in which an alpha2,3-linked receptor analog is bound to the H3 avian HA or to an H5 avian HA leads to the suggestion that all avian influenza HAs bind to their preferred alpha2,3-linked receptors similarly, with the analog in a trans conformation about the glycosidic linkage. We find that alpha2,6-linked analogs are bound by both human and avian HAs in a cis conformation, and that the incompatibility of an alpha2,6-linked receptor with the alpha2,3-linkage-specific H3 avian HA-binding site is partially resolved by a small change in the position and orientation of the sialic acid. We discuss our results in relation to the mechanism of transfer of influenza viruses between species.

The observed distribution of protein structures can give us important clues about the underlying evolutionary process, imposing important constraints on possible models. The availability of results from an increasing number of genome projects has made the development of these models an active area of research. Models explaining the observed distribution of structures have focused on the inherent functional capabilities and structural properties of different folds and on the evolutionary dynamics. Increasingly, these elements are being combined.