LAMPA, LArge Multidomain Protein Annotator, and its application to RNA virus polyproteins.

MOTIVATION: To facilitate accurate estimation of statistical significance of sequence similarity in profile-profile searches, queries should ideally correspond to protein domains. For multidomain proteins, using domains as queries depends on delineation of domain borders, which may be unknown. Thus, proteins are commonly used as queries that complicate establishing homology for similarities close to cutoff levels of statistical significance. RESULTS: In this article, we describe an iterative approach, called LAMPA, LArge Multidomain Protein Annotator, that resolves the above conundrum by gradual expansion of hit coverage of multidomain proteins through re-evaluating statistical significance of hit similarity using ever smaller queries defined at each iteration. LAMPA employs TMHMM and HHsearch for recognition of transmembrane regions and homology, respectively. We used Pfam database for annotating 2985 multidomain proteins (polyproteins) composed of >1000 amino acid residues, which dominate proteomes of RNA viruses. Under strict cutoffs, LAMPA outperformed HHsearch-mediated runs using intact polyproteins as queries by three measures: number of and coverage by identified homologous regions, and number of hit Pfam profiles. Compared to HHsearch, LAMPA identified 507 extra homologous regions in 14.4% of polyproteins. This Pfam-based annotation of RNA virus polyproteins by LAMPA was also superior to RefSeq expert annotation by two measures, region number and annotated length, for 69.3% of RNA virus polyprotein entries. We rationalized the obtained results based on dependencies of HHsearch hit statistical significance for local alignment similarity score from lengths and diversities of query-target pairs in computational experiments. AVAILABILITY AND IMPLEMENTATION: LAMPA 1.0.0 R package is placed at github (https://github.com/Gorbalenya-Lab/LAMPA). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Discovery of an essential nucleotidylating activity associated with a newly delineated conserved domain in the RNA polymerase-containing protein of all nidoviruses.

RNA viruses encode an RNA-dependent RNA polymerase (RdRp) that catalyzes the synthesis of their RNA(s). In the case of positive-stranded RNA viruses belonging to the order Nidovirales, the RdRp resides in a replicase subunit that is unusually large. Bioinformatics analysis of this non-structural protein has now revealed a nidoviral signature domain (genetic marker) that is N-terminally adjacent to the RdRp and has no apparent homologs elsewhere. Based on its conservation profile, this domain is proposed to have nucleotidylation activity. We used recombinant non-structural protein 9 of the arterivirus equine arteritis virus (EAV) and different biochemical assays, including irreversible labeling with a GTP analog followed by a proteomics analysis, to demonstrate the manganese-dependent covalent binding of guanosine and uridine phosphates to a lysine/histidine residue. Most likely this was the invariant lysine of the newly identified domain, named nidovirus RdRp-associated nucleotidyltransferase (NiRAN), whose substitution with alanine severely diminished the described binding. Furthermore, this mutation crippled EAV and prevented the replication of severe acute respiratory syndrome coronavirus (SARS-CoV) in cell culture, indicating that NiRAN is essential for nidoviruses. Potential functions supported by NiRAN may include nucleic acid ligation, mRNA capping and protein-primed RNA synthesis, possibilities that remain to be explored in future studies.

Arterivirus nsp12 versus the coronavirus nsp16 2'-O-methyltransferase: comparison of the C-terminal cleavage products of two nidovirus pp1ab polyproteins.

The 3'-terminal domain of the most conserved ORF1b in three of the four families of the order Nidovirales (except for the family Arteriviridae) encodes a (putative) 2'-O-methyltransferase (2'-O-MTase), known as non structural protein (nsp) 16 in the family Coronaviridae and implicated in methylation of the 5' cap structure of nidoviral mRNAs. As with coronavirus transcripts, arterivirus mRNAs are assumed to possess a 5' cap although no candidate MTases have been identified thus far. To address this knowledge gap, we analysed the uncharacterized nsp12 of arteriviruses, which occupies the ORF1b position equivalent to that of the nidovirus 2'-O-MTase (coronavirus nsp16). In our in-depth bioinformatics analysis of nsp12, the protein was confirmed to be family specific whilst having diverged much further than other nidovirus ORF1b-encoded proteins, including those of the family Coronaviridae. Only one invariant and several partially conserved, predominantly aromatic residues were identified in nsp12, which may adopt a structure with alternating α-helices and ß-strands, an organization also found in known MTases. However, no statistically significant similarity was found between nsp12 and the twofold larger coronavirus nsp16, nor could we detect MTase activity in biochemical assays using recombinant equine arteritis virus (EAV) nsp12. Our further analysis established that this subunit is essential for replication of this prototypic arterivirus. Using reverse genetics, we assessed the impact of 25 substitutions at 14 positions, yielding virus phenotypes ranging from WT-like to non-viable. Notably, replacement of the invariant phenylalanine 109 with tyrosine was lethal. We concluded that nsp12 plays an essential role during EAV replication, possibly by acting as a co-factor for another enzyme.

Practical application of bioinformatics by the multidisciplinary VIZIER consortium.

This review focuses on bioinformatics technologies employed by the EU-sponsored multidisciplinary VIZIER consortium (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 PROJECT: 2004-511960, active from 1 November 2004 to 30 April 2009), to achieve its goals. From the management of the information flow of the project, to bioinformatics-mediated selection of RNA viruses and prediction of protein targets, to the analysis of 3D protein structures and antiviral compounds, these technologies provided a communication framework and integrated solutions for steady and timely advancement of the project. RNA viruses form a large class of major pathogens that affect humans and domestic animals. Such RNA viruses as HIV, Influenza virus and Hepatitis C virus are of prime medical concern today, but the identities of viruses that will threaten human population tomorrow are far from certain. To contain outbreaks of common or newly emerging infections, prototype drugs against viruses representing the Virus Universe must be developed. This concept was championed by the VIZIER project which brought together experts in diverse fields to produce a concerted and sustained effort for identifying and validating targets for antivirus therapy in dozens of RNA virus lineages.