WEBnm@ v2.0: Web server and services for comparing protein flexibility.

BACKGROUND: Normal mode analysis (NMA) using elastic network models is a reliable and cost-effective computational method to characterise protein flexibility and by extension, their dynamics. Further insight into the dynamics-function relationship can be gained by comparing protein motions between protein homologs and functional classifications. This can be achieved by comparing normal modes obtained from sets of evolutionary related proteins. RESULTS: We have developed an automated tool for comparative NMA of a set of pre-aligned protein structures. The user can submit a sequence alignment in the FASTA format and the corresponding coordinate files in the Protein Data Bank (PDB) format. The computed normalised squared atomic fluctuations and atomic deformation energies of the submitted structures can be easily compared on graphs provided by the web user interface. The web server provides pairwise comparison of the dynamics of all proteins included in the submitted set using two measures: the Root Mean Squared Inner Product and the Bhattacharyya Coefficient. The Comparative Analysis has been implemented on our web server for NMA, WEBnm@, which also provides recently upgraded functionality for NMA of single protein structures. This includes new visualisations of protein motion, visualisation of inter-residue correlations and the analysis of conformational change using the overlap analysis. In addition, programmatic access to WEBnm@ is now available through a SOAP-based web service. Webnm@ is available at http://apps.cbu.uib.no/webnma . CONCLUSION: WEBnm@ v2.0 is an online tool offering unique capability for comparative NMA on multiple protein structures. Along with a convenient web interface, powerful computing resources, and several methods for mode analyses, WEBnm@ facilitates the assessment of protein flexibility within protein families and superfamilies. These analyses can give a good view of how the structures move and how the flexibility is conserved over the different structures.

Genomic insights into methanotrophy: the complete genome sequence of Methylococcus capsulatus (Bath).

Methanotrophs are ubiquitous bacteria that can use the greenhouse gas methane as a sole carbon and energy source for growth, thus playing major roles in global carbon cycles, and in particular, substantially reducing emissions of biologically generated methane to the atmosphere. Despite their importance, and in contrast to organisms that play roles in other major parts of the carbon cycle such as photosynthesis, no genome-level studies have been published on the biology of methanotrophs. We report the first complete genome sequence to our knowledge from an obligate methanotroph, Methylococcus capsulatus (Bath), obtained by the shotgun sequencing approach. Analysis revealed a 3.3-Mb genome highly specialized for a methanotrophic lifestyle, including redundant pathways predicted to be involved in methanotrophy and duplicated genes for essential enzymes such as the methane monooxygenases. We used phylogenomic analysis, gene order information, and comparative analysis with the partially sequenced methylotroph Methylobacterium extorquens to detect genes of unknown function likely to be involved in methanotrophy and methylotrophy. Genome analysis suggests the ability of M. capsulatus to scavenge copper (including a previously unreported nonribosomal peptide synthetase) and to use copper in regulation of methanotrophy, but the exact regulatory mechanisms remain unclear. One of the most surprising outcomes of the project is evidence suggesting the existence of previously unsuspected metabolic flexibility in M. capsulatus, including an ability to grow on sugars, oxidize chemolithotrophic hydrogen and sulfur, and live under reduced oxygen tension, all of which have implications for methanotroph ecology. The availability of the complete genome of M. capsulatus (Bath) deepens our understanding of methanotroph biology and its relationship to global carbon cycles. We have gained evidence for greater metabolic flexibility than was previously known, and for genetic components that may have biotechnological potential.