A proline-rich region with a highly periodic sequence in Streptococcal beta protein adopts the polyproline II structure and is exposed on the bacterial surface

Proline-rich regions have been identified in many surface proteins of pathogenic streptococci and staphylococci. These regions have been suggested to be located in cell wall-spanning domains and/or to be required for surface expression of the protein. Because little is known about these regions, which are found in extensively studied and biologically important surface proteins, we characterized the proline-rich region in one such protein, the beta protein of group B streptococci. The proline-rich region in beta, designated the XPZ region, has a proline at every third position, and the sequence is highly periodic in other respects. Immunochemical analysis showed that the XPZ region was not associated with the cell wall but was exposed on the bacterial surface. Moreover, characterization of a beta mutant lacking the XPZ region demonstrated that this region was not required for surface expression of the beta protein. Comparison of the XPZ region in different beta proteins showed that it varied in size but always retained the typical sequence periodicity. Circular dichroism spectroscopy indicated that the XPZ region had the structure of a polyproline II helix, an extended and solvent-exposed structure with exactly three residues per turn. Because of the three-residue sequence periodicity in the XPZ region, it is expected to be amphipathic and to have distinct nonpolar and polar surfaces. This study identified a proline-rich structure with unique properties that is exposed on the surface of an important human pathogen.     

Estimation of amino acid residue substitution rates at local spatial regions and application in protein function inference: a Bayesian Monte Carlo approach

The amino acid sequences of proteins provide rich information for inferring distant phylogenetic relationships and for predicting protein functions. Estimating the rate matrix of residue substitutions from amino acid sequences is also important because the rate matrix can be used to develop scoring matrices for sequence alignment. Here we use a continuous time Markov process to model the substitution rates of residues and develop a Bayesian Markov chain Monte Carlo method for rate estimation. We validate our method using simulated artificial protein sequences. Because different local regions such as binding surfaces and the protein interior core experience different selection pressures due to functional or stability constraints, we use our method to estimate the substitution rates of local regions. Our results show that the substitution rates are very different for residues in the buried core and residues on the solvent-exposed surfaces. In addition, the rest of the proteins on the binding surfaces also have very different substitution rates from residues. Based on these findings, we further develop a method for protein function prediction by surface matching using scoring matrices derived from estimated substitution rates for residues located on the binding surfaces. We show with examples that our method is effective in identifying functionally related proteins that have overall low sequence identity, a task known to be very challenging.     

Extreme Evolutionary Conservation of Functionally Important Regions in H1N1 Influenza Proteome

The H1N1 subtype of influenza A virus has caused two of the four documented pandemics and is responsible for seasonal epidemic outbreaks, presenting a continuous threat to public health. Co-circulating antigenically divergent influenza strains significantly complicates vaccine development and use. Here, by combining evolutionary, structural, functional, and population information about the H1N1 proteome, we seek to answer two questions: (1) do residues on the protein surfaces evolve faster than the protein core residues consistently across all proteins that constitute the influenza proteome? and (2) in spite of the rapid evolution of surface residues in influenza proteins, are there any protein regions on the protein surface that do not evolve? To answer these questions, we first built phylogenetically-aware models of the patterns of surface and interior substitutions. Employing these models, we found a single coherent pattern of faster evolution on the protein surfaces that characterizes all influenza proteins. The pattern is consistent with the events of inter-species reassortment, the worldwide introduction of the flu vaccine in the early 80’s, as well as the differences caused by the geographic origins of the virus. Next, we developed an automated computational pipeline to comprehensively detect regions of the protein surface residues that were 100% conserved over multiple years and in multiple host species. We identified conserved regions on the surface of 10 influenza proteins spread across all avian, swine, and human strains; with the exception of a small group of isolated strains that affected the conservation of three proteins. Surprisingly, these regions were also unaffected by genetic variation in the pandemic 2009 H1N1 viral population data obtained from deep sequencing experiments. Finally, the conserved regions were intrinsically related to the intra-viral macromolecular interaction interfaces. Our study may provide further insights towards the identification of novel protein targets for influenza antivirals.     

The role of MukE in assembling a functional MukBEF complex

The MukB-MukE-MukF protein complex is essential for chromosome condensation and segregation in Escherichia coli. The central component of this complex, the MukB protein, is related functionally and structurally to the ubiquitous SMC (structural maintenance of chromosomes) proteins. In a manner similar to SMC, MukB requires the association of two accessory proteins (MukE and MukF) for its function. MukF is a constitutive dimer that bridges the interaction between MukB and MukE. While MukB can condense DNA on its own, it requires MukF and MukE to ensure proper chromosome segregation. Here, we present a novel structure of the E. coli MukE-MukF complex, in which the intricate crystal packing interactions reveal an alternative MukE dimerization interface spanning both N- and C-terminal winged-helix domains of the protein. The structure also unveils additional cross-linking interactions between adjacent MukE-MukF complexes mediated by MukE. A variant of MukE encompassing point mutations on one of these surfaces does not affect assembly of the MukB-MukE-MukF complex and yet cannot restore the temperature sensitivity of the mukE∷kan strain, suggesting that this surface may mediate critical protein-protein interactions between MukB-MukE-MukF complexes. Since the dimerization interface of MukE overlaps with the region of the protein that interacts with MukB in the MukB-MukE-MukF complex, we suggest that competing MukB-MukE and MukE-MukE interactions may regulate the formation of higher-order structures of bacterial condensin.     

The surface of β-sheet proteins contains amphiphilic regions which may provide clues about protein folding

A major bottleneck in the field of biochemistry is our limited understanding of the processes by which a protein folds into its native conformation. Much of the work on this issue has focused on the conserved core of the folded protein. However, one might imagine that a ubiquitous motif for unaided folding or for the recognition of chaperones may involve regions on the surface of the native structure. We explore this possibility by an analysis of the spatial distribution of regions with amphiphilic α-helical potential on the surface of β-sheet proteins. All proteins, Including β-sheet proteins, contain regions with amphiphilic α-helical potential. That is, any α-helix formed by that region would be amphiphilic, having both hydrophobic and hydrophilic surfaces. In the three-dimensional structure of all β-sheet proteins analyzed, we have found a distinct pattern in the spatial distribution of sequences with amphiphilic α-helical potential. The amphiphilic regions occur in ring shaped clusters approximately 20 to 30 Å in diameter on the surface of the protein. In addition, these regions have a strong preference for positively charged amino acids and a lower preference for residues not favorable to α-helix formation. Although the purpose of these amphiphilic regions which are not associated with naturally occurring α-helix is unknown, they may play a critical role in highly conserved processes such as protein folding. © 1996 Wiley-Liss, Inc.     

Predicting Protein Function and Binding Profile via Matching of Local Evolutionary and Geometric Surface Patterns

Inferring protein functions from structures is a challenging task, as a large number of orphan protein structures from structural genomics project are now solved without their biochemical functions characterized. For proteins binding to similar substrates or ligands and carrying out similar functions, their binding surfaces are under similar physicochemical constraints, and hence the sets of allowed and forbidden residue substitutions are similar. However, it is difficult to isolate such selection pressure due to protein function from selection pressure due to protein folding, and evolutionary relationship reflected by global sequence and structure similarities between proteins is often unreliable for inferring protein function. We have developed a method, called pevoSOAR (pocket-based evolutionary search of amino acid residues), for predicting protein functions by solving the problem of uncovering amino acids residue substitution pattern due to protein function and separating it from amino acids substitution pattern due to protein folding. We incorporate evolutionary information specific to an individual binding region and match local surfaces on a large scale with millions of precomputed protein surfaces to identify those with similar functions. Our pevoSOAR method also generates a probablistic model called the computed binding a profile that characterizes protein-binding activities that may involve multiple substrates or ligands. We show that our method can be used to predict enzyme functions with accuracy. Our method can also assess enzyme binding specificity and promiscuity. In an objective large-scale test of 100 enzyme families with thousands of structures, our predictions are found to be sensitive and specific: At the stringent specificity level of 99.98%, we can correctly predict enzyme functions for 80.55% of the proteins. The overall area under the receiver operating characteristic curve measuring the performance of our prediction is 0.955, close to the perfect value of 1.00. The best Matthews coefficient is 86.6%. Our method also works well in predicting the biochemical functions of orphan proteins from structural genomics projects.     

Identification of protein biochemical functions by similarity search using the molecular surface database eF-site

The identification of protein biochemical functions based on their three-dimensional structures is strongly required in the post-genome-sequencing era. We have developed a new method to identify and predict protein biochemical functions using the similarity information of molecular surface geometries and electrostatic potentials on the surfaces. Our prediction system consists of a similarity search method based on a clique search algorithm and the molecular surface database eF-site (electrostatic surface of functional-site in proteins). Using this system, functional sites similar to those of phosphoenoylpyruvate carboxy kinase were detected in several mononucleotide-binding proteins, which have different folds. We also applied our method to a hypothetical protein, MJ0226 from Methanococcus jannaschii, and detected the mononucleotide binding site from the similarity to other proteins having different folds.     

A quantitative analysis of interfacial amino acid conservation in protein-protein hetero complexes

A long-standing question in molecular biology is whether interfaces of protein-protein complexes are more conserved than the rest of the protein surfaces. Although it has been reported that conservation can be used as an indicator for predicting interaction sites on proteins, there are recent reports stating that the interface regions are only slightly more conserved than the rest of the protein surfaces, with conservation signals not being statistically significant enough for predicting protein-protein binding sites. In order to properly address these controversial reports we have studied a set of 28 well resolved hetero complex structures of proteins that consists of transient and non-transient complexes. The surface positions were classified into four conservation classes and the conservation index of the surface positions was quantitatively analyzed. The results indicate that the surface density of highly conserved positions is significantly higher in the protein-protein interface regions compared with the other regions of the protein surface. However, the average conservation index of the patches in the interface region is not significantly higher compared with other surface regions of the protein structures. This finding demonstrates that the number of conserved residue positions is a more appropriate indicator for predicting protein-protein binding sites than the average conservation index in the interacting region. We have further validated our findings on a set of 59 benchmark complex structures. Furthermore, an analysis of 19 complexes of antigen-antibody interactions shows that there is no conservation of amino acid positions in the interacting regions of these complexes, as expected, with the variable region of the immunoglobulins interacting mostly with the antigens. Interestingly, antigen interacting regions also have a higher number of non-conserved residue positions in the interacting region than the rest of the protein surface.     

Analysis of lateral diffusion from a spherical cell surface to a tubular projection.

Cell surfaces are often heterogeneous with respect to the lateral distribution and mobility of membrane components. Because lateral mobility is related to membrane structure, measurement of a particular component's local diffusion coefficient within a distinct surface region provides useful information about the formation and maintenance of that region. Many structurally interesting cell surface features can be described as narrow tubular projections from the body of the cell. In a companion paper, we consider the thin "tethers" that can be mechanically drawn from the red blood cell membrane, and we measure the transport of fluorescent integral proteins from the surface of the cell body onto the tether. In this paper we present an analysis to describe the surface diffusion of membrane particles from a spherical shell onto a thin cylindrical process. Provision is made for different rates of diffusion within the two morphologically distinct regions. The relative role of each region in controlling the diffusive flux between regions is determined primarily by a single dimensionless parameter. This parameter incorporates the ratio of the two diffusion coefficients as well as the dimensions of each region. The analysis can be applied to a fluorescence photobleaching experiment in which the extended process is bleached. If the dimensions of the spherical cell body and the cylindrical extension are known, then the diffusion coefficients of both regions can be determined from the experimental fluorescence recovery curve.     

Matching nucleotide sequences of human antibodies with other known sequences

From an evolutionary point of view, the complementarity-determining regions of antibodies are distinct from other proteins including the framework regions of antibodies. A search for identical nucleotide sequences of eighty-four 15 consecutive bp in the complementary-determining regions of human antibody heavy chains with other known sequences yielded four matches: two sequential 15-bp matches, or one 16-bp match, with the coding region of a sea-urchin testis histone H2b-2, one 15-bp match with the promotor region of a cauliflower mosaic virus inclusion body protein, and a 15-bp match with an intron between exons 1 and 2 of human factor IX. As a control, an identical search of eighty-four 15 consecutive bp in the framework regions of human antibody heavy chains yielded no matches with other sequences except those from other antibody framework regions. Since the currently available nucleotide sequence database used in the search consisted of about 1 x 10(7) bp, finding such matches in the complementarity-determining regions might not be random.     

Incorporation of evolutionary information into Rosetta comparative modeling

Prediction of protein structures from sequences is a fundamental problem in computational biology. Algorithms that attempt to predict a structure from sequence primarily use two sources of information. The first source is physical in nature: proteins fold into their lowest energy state. Given an energy function that describes the interactions governing folding, a method for constructing models of protein structures, and the amino acid sequence of a protein of interest, the structure prediction problem becomes a search for the lowest energy structure. Evolution provides an orthogonal source of information: proteins of similar sequences have similar structure, and therefore proteins of known structure can guide modeling. The relatively successful Rosetta approach takes advantage of the first, but not the second source of information during model optimization. Following the classic work by Andrej Sali and colleagues, we develop a probabilistic approach to derive spatial restraints from proteins of known structure using advances in alignment technology and the growth in the number of structures in the Protein Data Bank. These restraints define a region of conformational space that is high-probability, given the template information, and we incorporate them into Rosetta's comparative modeling protocol. The combined approach performs considerably better on a benchmark based on previous CASP experiments. Incorporating evolutionary information into Rosetta is analogous to incorporating sparse experimental data: in both cases, the additional information eliminates large regions of conformational space and increases the probability that energy-based refinement will hone in on the deep energy minimum at the native state.     

Potential folding-function interrelationship in proteins

The possibility is addressed that protein folding and function may be related via regions that are critical for both folding and function. This approach is based on the building blocks folding model that describes protein folding as binding events of conformationally fluctuating building blocks. Within these, we identify building block fragments that are critical for achieving the native fold. A library of such critical building blocks (CBBs) is constructed. Then, it is asked whether the functionally important residues fall in these CBB fragments. We find that for over two-thirds of the proteins in our library with available functional information, the catalytic or binding site residues lie within the CBB regions. From the evolutionary standpoint, a folding-function relationship is advantageous, since the need to guard against mutations is limited to one region. Furthermore, conformationally similar CBBs are found in globally unrelated proteins with different functions. Hence, substituting CBBs may lead to designed proteins with altered functions. We further find that the CBBs in our library are conformationally unstable.     

Patterning of proteins and cells on functionalized surfaces prepared by polyelectrolyte multilayers and micromolding in capillaries

A method for protein and cell patterning on polyelectrolyte-coated surfaces using simple micromolding in capillaries (MIMIC) is described. MIMIC produced two distinctive regions. One contained polyethylene glycol (PEG) microstructures fabricated using photopolymerization that provided physical, chemical, and biological barriers to the nonspecific binding of proteins, bacteria, and fibroblast cells. The second region was the polyelectrolyte (PEL) coated surface that promoted protein and cell immobilization.

The difference in surface functionality between the PEL region and background PEG microstructures resulted in simple patterning of biomolecules. Fluorescein isothiocyanate-tagged bovine serum albumin, E. coli expressing green fluorescence protein (GFP), and fibroblast cells were successfully bound to the exposed PEL surfaces at micron scale. Compared with the simple adsorption of protein, fluorescence intensity was dramatically improved (by about six-fold) on the PEL-modified surfaces. Although animal cell patterning is prerequisite for adhesive protein layer to survive on desired area, the PEL surface without adhesive proteins provides affordable microenvironment for cells.

The simple preparation of functionalized surface but universal platform can be applied to various biomolecules such as proteins, bacteria, and cells.     

Measurement of protein surface shape by solid angles

A method for measuring the gross shape of local regions of protein surface is presented and applied to an examination of three proteins. Any point on the protein surface can be assigned a number that measures the degree of convexity or concavity of the surface in the vicinity of the point. This number is computed by centring a sphere at that point and measuring how much of the sphere lies inside the protein. The sphere radius is a parameter chosen according to the scale of the features that are being analysed. The amount of sphere intersecting the protein is interpreted as a solid angle, denoted omega. Three proteins are analysed by this method: lysozyme, Superoxide dismutase and chymotrypsin. The resulting omega values are used to colour code the protein surfaces displayed on a colour raster graphics terminal. The method can be seen to reliably identify protrusions and depressions. The difficulty of developing a generally useful method for measuring protein surface shape is discussed. Possible applications of the solid-angle method include the analysis of shape complementarity at protein interfaces, the development of computer algorithms for predicting complexes between proteins, or between proteins and ligands, the identification of homologous epitopes on different proteins that might be immunologically crossreactive, and the determination of correlations between surface geometry and chemical properties.     

C-terminal WxL domain mediates cell wall binding in Enterococcus faecalis and other gram-positive bacteria

Analysis of the genome sequence of Enterococcus faecalis clinical isolate V583 revealed novel genes encoding surface proteins. Twenty-seven of these proteins, annotated as having unknown functions, possess a putative N-terminal signal peptide and a conserved C-terminal region characterized by a novel conserved domain designated WxL. Proteins having similar characteristics were also detected in other low-G+C-content gram-positive bacteria. We hypothesized that the WxL region might be a determinant of bacterial cell location. This hypothesis was tested by generating protein fusions between the C-terminal regions of two WxL proteins in E. faecalis and a nuclease reporter protein. We demonstrated that the C-terminal regions of both proteins conferred a cell surface localization to the reporter fusions in E. faecalis. This localization was eliminated by introducing specific deletions into the domains. Interestingly, exogenously added protein fusions displayed binding to whole cells of various gram-positive bacteria. We also showed that the peptidoglycan was a binding ligand for WxL domain attachment to the cell surface and that neither proteins nor carbohydrates were necessary for binding. Based on our findings, we propose that the WxL region is a novel cell wall binding domain in E. faecalis and other gram-positive bacteria.     

Surface motifs by a computer vision technique: Searches,detection, and implications for protein–ligand recognition

We describe the application of a method geared toward structural and surface comparison of proteins. The method is based on the Geometric Hashing Paradigm adapted from Computer Vision. It allows for comparison of any two sets of 3-D coordinates, such as protein backbones, protein core or protein surface motifs, and small molecules such as drugs. Here we apply our method to 4 types of comparisons between pairs of molecules: (1) comparison of the backbones of two protein domains; (2) search for a predefined 3-D C_α motif within the full backbone of a domain; and in particular, (3) comparison of the surfaces of two receptor proteins; and (4) comparison of the surface of a receptor to the surface of a ligand. These aspects complement each other and can contribute toward a better understandingof protein structure and biomolecular recognition. Searches for 3-D surface motifs can be carried out on either receptors or on ligands. The latter may result in the detection of pharmacophoric patterns. If the surfaces of the binding sites of either the receptors or of the ligands are relatively similar, surface superpositioning may aid significantly in the docking problem. Currently, only distance invariants are used in the matching, although additional geometric surface invariants are considered. The speed of our Geometric Hashing algorithm is encouraging, with a typical surface comparison taking only seconds or minutes of CPU time on a SUN 4 SPARC workstation. The direct application of this method to the docking problem is also discussed. We demonstrate the success of this methodin its application to two members of the globin family and to two dehydrogenases. © 1993 Wiley-Liss, Inc.     

Characterization of local geometry of protein surfaces with the visibility criterion

Experimentally determined protein tertiary structures are rapidly accumulating in a database, partly due to the structural genomics projects. Included are proteins of unknown function, whose function has not been investigated by experiments and was not able to be predicted by conventional sequence-based search. Those uncharacterized protein structures highlight the urgent need of computational methods for annotating proteins from tertiary structures, which include function annotation methods through characterizing protein local surfaces. Toward structure-based protein annotation, we have developed VisGrid algorithm that uses the visibility criterion to characterize local geometric features of protein surfaces. Unlike existing methods, which only concerns identifying pockets that could be potential ligand-binding sites in proteins, VisGrid is also aimed to identify large protrusions, hollows, and flat regions, which can characterize geometric features of a protein structure. The visibility used in VisGrid is defined as the fraction of visible directions from a target position on a protein surface. A pocket or a hollow is recognized as a cluster of positions with a small visibility. A large protrusion in a protein structure is recognized as a pocket in the negative image of the structure. VisGrid correctly identified 95.0% of ligand-binding sites as one of the three largest pockets in 5616 benchmark proteins. To examine how natural flexibility of proteins affects pocket identification, VisGrid was tested on distorted structures by molecular dynamics simulation. Sensitivity decreased approximately 20% for structures of a root mean square deviation of 2.0 A to the original crystal structure, but specificity was not much affected. Because of its intuitiveness and simplicity, the visibility criterion will lay the foundation for characterization and function annotation of local shape of proteins.     

Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces.     

The human IgA-Fc alpha receptor interaction and its blockade by streptococcal IgA-binding proteins

IgA plays a key role in immune defence of the mucosal surfaces. IgA can trigger elimination mechanisms against pathogens through the interaction of its Fc region with Fc alpha Rs (receptors specific for the Fc region of IgA) present on neutrophils, macrophages, monocytes and eosinophils. The human Fc alpha R (CD89) shares homology with receptors specific for the Fc region of IgG (Fc gamma Rs) and IgE (Fc epsilon RIs), but is a more distantly related member of the receptor family. CD89 interacts with residues lying at the interface of the two domains of IgA Fc, a site quite distinct from the homologous regions at the top of IgG and IgE Fc recognized by Fc gamma R and Fc epsilon RI respectively. Certain pathogenic bacteria express surface proteins that bind to human IgA Fc. Experiments with domain-swap antibodies and mutant IgAs indicate that binding of three such proteins (Sir22 and Arp4 of Streptococcus pyogenes and beta protein of group B streptococci) depend on sites in the Fc interdomain region of IgA, the binding region also used by CD89. Further, we have found that the streptococcal proteins can inhibit interaction of IgA with CD89, and have thereby identified a mechanism by which a bacterial IgA-binding protein may modulate IgA effector function.