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Protein structures contain highly complex systems of voids, making up specific features such as surface clefts or grooves, pockets, protrusions, cavities, pores or channels, and tunnels. Many of them are essential for the migration of solvents, ions and small molecules through proteins, and their binding to the functional sites. Analysis of these structural features is very important for understanding of structure-function relationships, for the design of potential inhibitors or proteins with improved functional properties. Here we critically review existing software tools specialized in rapid identification, visualization, analysis and design of protein tunnels and channels. The strengths and weaknesses of individual tools are reported together with examples of their applications for the analysis and engineering of various biological systems. This review can assist users with selecting a proper software tool for study of their biological problem as well as highlighting possible avenues for further development of existing tools. Development of novel descriptors representing not only geometry, but also electrostatics, hydrophobicity or dynamics, is needed for reliable identification of biologically relevant tunnels and channels., (Copyright © 2012 Elsevier Inc. All rights reserved.)

FTH_0069 is a previously uncharacterized strongly immunoreactive protein that has been proposed to be a novel virulence factor in Francisella tularensis. Here, the glycan structure modifying two C-terminal peptides of FTH_0069 was identified utilizing high resolution, high mass accuracy mass spectrometry, combined with in-source CID tandem MS experiments. The glycan observed at m/z 1156 was determined to be a hexasaccharide, consisting of two hexoses, three N-acetylhexosamines, and an unknown monosaccharide containing a phosphate group. The monosaccharide sequence of the glycan is tentatively proposed as X-P-HexNAc-HexNAc-Hex-Hex-HexNAc, where X denotes the unknown monosaccharide. The glycan is identical to that of DsbA glycoprotein, as well as to one of the multiple glycan structures modifying the type IV pilin PilA, suggesting a common biosynthetic pathway for the protein modification. Here, we demonstrate that the glycosylation of FTH_0069, DsbA, and PilA was affected in an isogenic mutant with a disrupted wbtDEF gene cluster encoding O-antigen synthesis and in a mutant with a deleted pglA gene encoding pilin oligosaccharyltransferase PglA. Based on our findings, we propose that PglA is involved in both pilin and general F. tularensis protein glycosylation, and we further suggest an inter-relationship between the O-antigen and the glycan synthesis in the early steps in their biosynthetic pathways.

A haloalkane dehalogenase, DpcA, from Psychrobacter cryohalolentis K5, representing a novel psychrophilic member of the haloalkane dehalogenase family, was identified and biochemically characterized. DpcA exhibited a unique temperature profile with exceptionally high activities at low temperatures. The psychrophilic properties of DpcA make this enzyme promising for various environmental applications.

Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

An enzyme's substrate specificity is one of its most important characteristics. The quantitative comparison of broad-specificity enzymes requires the selection of a homogenous set of substrates for experimental testing, determination of substrate-specificity data and analysis using multivariate statistics. We describe a systematic analysis of the substrate specificities of nine wild-type and four engineered haloalkane dehalogenases. The enzymes were characterized experimentally using a set of 30 substrates selected using statistical experimental design from a set of nearly 200 halogenated compounds. Analysis of the activity data showed that the most universally useful substrates in the assessment of haloalkane dehalogenase activity are 1-bromobutane, 1-iodopropane, 1-iodobutane, 1,2-dibromoethane and 4-bromobutanenitrile. Functional relationships among the enzymes were explored using principal component analysis. Analysis of the untransformed specific activity data revealed that the overall activity of wild-type haloalkane dehalogenases decreases in the following order: LinB~DbjA>DhlA~DhaA~DbeA~DmbA>DatA~DmbC~DrbA. After transforming the data, we were able to classify haloalkane dehalogenases into four SSGs (substrate-specificity groups). These functional groups are clearly distinct from the evolutionary subfamilies, suggesting that phylogenetic analysis cannot be used to predict the substrate specificity of individual haloalkane dehalogenases. Structural and functional comparisons of wild-type and mutant enzymes revealed that the architecture of the active site and the main access tunnel significantly influences the substrate specificity of these enzymes, but is not its only determinant. The identification of other structural determinants of the substrate specificity remains a challenge for further research on haloalkane dehalogenases.