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.     

酵母表面展示体系的构建及在纤维素降解中的应用*

纤维素是来源广泛且储量较大的低成本可再生资源,但其结构致密难以利用。目前降解纤维素需要多种纤维素酶协作,而游离纤维素酶成本高、难以重复利用等问题限制了其广泛应用。利用酵母表面展示技术,可以将多个纤维素酶分别与锚定蛋白融合后共展示在细胞表面,从而构建酵母表面展示纤维素酶体系。这一体系可高效降解纤维素,一方面可以充分发挥表面展示的优点,如易回收、稳定性好、操作简单、成本低;另一方面可以将纤维素有效地降解为葡萄糖,并具有代谢产生物乙醇的潜力。阐述了酵母表面展示体系的构建原则,总结了影响展示体系效率的因素,介绍了这一技术在降解纤维素中的应用,为构建高效酵母表面展示纤维素酶体系及其他多酶体系提供参考。     

Stable self-assembly of a protein engineering scaffold on gold surfaces

The outer membrane protein OmpF from Escherichia coli is a member of a large family of beta-barrel membrane proteins. Some, like OmpF, are pore-forming proteins whilse others are active transporters or enzymes. We have previously shown that the receptor-binding domain (R-domain) of the toxin colicin N binds with high affinity to OmpF reconstituted into tethered lipid bilayers on gold electrodes. The binding can be measured by surface plasmon resonance (SPR) and ion channel blockage (impedance spectroscopy, IS). In this paper we report the use of a mutant OmpF-E183C in which a single cysteine had been introduced on a short periplasmic turn. OmpF-E183C binds directly to gold surfaces and creates high-density protein layers by self-assembly from detergent solution. When the gold surface is pretreated with beta-mercaptoethanol and thiolipids are added after the protein immobilisation step, the protein is shown, by Fourier transform infrared spectroscopy (FTIR), to retain its beta-rich structure. Furthermore, we could also measure R-domain binding by SPR and IS, confirming the functional reconstitution of a self-assembled membrane protein monolayer at the gold surface. Because these beta-barrel proteins are recognized protein engineering scaffolds, the method provides a generic method for the simple self-assembly of protein interfaces from aqueous solution.     

Inferring functional relationships of proteins from local sequence and spatial surface patterns

We describe a novel approach for inferring functional relationship of proteins by detecting sequence and spatial patterns of protein surfaces. Well-formed concave surface regions in the form of pockets and voids are examined to identify similarity relationship that might be directly related to protein function. We first exhaustively identify and measure analytically all 910,379 surface pockets and interior voids on 12,177 protein structures from the Protein Data Bank. The similarity of patterns of residues forming pockets and voids are then assessed in sequence, in spatial arrangement, and in orientational arrangement. Statistical significance in the form of E and p-values is then estimated for each of the three types of similarity measurements. Our method is fully automated without human intervention and can be used without input of query patterns. It does not assume any prior knowledge of functional residues of a protein, and can detect similarity based on surface patterns small and large. It also tolerates, to some extent, conformational flexibility of functional sites. We show with examples that this method can detect functional relationship with specificity for members of the same protein family and superfamily, as well as remotely related functional surfaces from proteins of different fold structures. We envision that this method can be used for discovering novel functional relationship of protein surfaces, for functional annotation of protein structures with unknown biological roles, and for further inquiries on evolutionary origins of structural elements important for protein function.     

Restricted mobility of side chains on concave surfaces of solenoid proteins may impart heightened potential for intermolecular interactions

Significant progress has been made in the determination of the protein structures with their number today passing over a hundred thousand structures. The next challenge is the understanding and prediction of protein–protein and protein–ligand interactions. In this work we address this problem by analyzing curved solenoid proteins. Many of these proteins are considered as “hub molecules” for their high potential to interact with many different molecules and to be a scaffold for multisubunit protein machineries. Our analysis of these structures through molecular dynamics simulations reveals that the mobility of the side‐chains on the concave surfaces of the solenoids is lower than on the convex ones. This result provides an explanation to the observed preferential binding of the ligands, including small and flexible ligands, to the concave surface of the curved solenoid proteins. The relationship between the landscapes and dynamic properties of the protein surfaces can be further generalized to the other types of protein structures and eventually used in the computer algorithms, allowing prediction of protein–ligand interactions by analysis of protein surfaces . Proteins 2015; 83:1654–1664. © 2015 Wiley Periodicals, Inc.     

Occluded molecular surface: Analysis of protein packing

We describe a novel method to calculate the packing interactions in protein structural models. The method calculates the interatomic occluded surface areas for each atom in the protein model. The identification of, and degree of interaction with, neighboring atoms is accomplished by extending surface normal from a dot surface of each atom to the point of intersection with neighboring atoms. The combined occluded and non-occluded surface areas may be normalized for the amino acid composition of the protein providing a single parameter, the normalized protein surface ratio, which is diagnostic for native-like Structures. Individual residues in the model which are in infrequent occluded surface environments may be identified. The method provides a means to explicitly describe packing densities and packing environments of individual atoms in a protein model. Finally, the method allows estimation of the complementarity between any interacting molecules, for example a ligand binding to a receptor.     

Uncovering network systems within protein structures

Traditionally, proteins have been viewed as a construct based on elements of secondary structure and their arrangement in three-dimensional space. In a departure from this perspective we show that protein structures can be modelled as network systems that exhibit small-world, single-scale, and to some degree, scale-free properties. The phenomenological network concept of degrees of separation is applied to three-dimensional protein structure networks and reveals how amino acid residues can be connected to each other within six degrees of separation. This work also illuminates the unique features of protein networks in comparison to other networks currently studied. Recognising that proteins are networks provides a means of rationalising the robustness in the overall three-dimensional fold of a protein against random mutations and suggests an alternative avenue to investigate the determinants of protein structure, function and folding.     

A simple topological representation of protein structure: implications for new, fast, and robust structural classification

A topological representation of proteins is developed that makes use of two metrics: the Euclidean metric for identifying natural nearest neighboring residues via the Delaunay tessellation in Cartesian space and the distance between residues in sequence space. Using this representation, we introduce a quantitative and computationally inexpensive method for the comparison of protein structural topology. The method ultimately results in a numerical score quantifying the distance between proteins in a heuristically defined topological space. The properties of this scoring scheme are investigated and correlated with the standard Calpha distance root-mean-square deviation measure of protein similarity calculated by rigid body structural alignment. The topological comparison method is shown to have a characteristic dependence on protein conformational differences and secondary structure. This distinctive behavior is also observed in the comparison of proteins within families of structural relatives. The ability of the comparison method to successfully classify proteins into classes, superfamilies, folds, and families that are consistent with standard classification methods, both automated and human-driven, is demonstrated. Furthermore, it is shown that the scoring method allows for a fine-grained classification on the family, protein, and species level that agrees very well with currently established phylogenetic hierarchies. This fine classification is achieved without requiring visual inspection of proteins, sequence analysis, or the use of structural superimposition methods. Implications of the method for a fast, automated, topological hierarchical classification of proteins are discussed.     

基于物化性质对嗜热蛋白的预测

嗜热蛋白在高温下能保持稳定性和活性,是研究蛋白质热稳定性的理想模型,开发一个蛋白质热稳定性识别的方法将对蛋白质工程和蛋白质的设计很有帮助。目前的研究中,氨基酸的组成及其物化性质一直被认为和蛋白质的热稳定性相关。本研究筛选出可靠的数据集,包括915个嗜热蛋白和793个非嗜热蛋白。利用蛋白质氨基酸的物化性质和氨基酸的组成表征嗜热蛋白,将二肽氨基酸组成整合到9组氨基酸物化性质中使蛋白序列公式化。支持向量机5折叠交叉验证表明:当gap=0时,290个特征产生的精度最高,为92.74%。因此说明对于分析蛋白质的热稳定性,所建立的预测模型将是一个很有效的工具。     

Protein structure prediction using a docking-based hierarchical folding scheme

The pathways by which proteins fold into their specific native structure are still an unsolved mystery. Currently, many methods for protein structure prediction are available, and most of them tackle the problem by relying on the vast amounts of data collected from known protein structures. These methods are often not concerned with the route the protein follows to reach its final fold. This work is based on the premise that proteins fold in a hierarchical manner. We present FOBIA, an automated method for predicting a protein structure. FOBIA consists of two main stages: the first finds matches between parts of the target sequence and independently folding structural units using profile-profile comparison. The second assembles these units into a 3D structure by searching and ranking their possible orientations toward each other using a docking-based approach. We have previously reported an application of an initial version of this strategy to homology based targets. Since then we have considerably enhanced our method's abilities to allow it to address the more difficult template-based target category. This allows us to now apply FOBIA to the template-based targets of CASP8 and to show that it is both very efficient and promising. Our method can provide an alternative for template-based structure prediction, and in particular, the docking-basedranking technique presented here can be incorporated into any profile-profile comparison based method.     

Amino acid architecture and the distribution of polar atoms on the surfaces of proteins

We propose that a necessary condition for a protein to be soluble is the absence of large hydrophobic patches on its solvent-accessible surface, which can cause aggregation to occur. We note that the polar nature of the backbone of all amino acids guarantees a minimum polar content and hence can interrupt such patches. As a result, a carefully conserved detailed atomic placement of residues on the protein surface is not necessary for solubility. In order to demonstrate this, we construct a measure based on the average hydrophobicity of a simply defined patch. We use this measurement to compare surfaces that exhibit a clear difference in their solubility properties, namely, a) the solvent accessible surfaces for a set of homo-dimers and the surfaces buried in their interfaces and b) for a set of monomers the surfaces of fragments of secondary structure which are solvent accessible/inaccessible. Having demonstrated a difference in the first set of distributions, we characterize the solvent accessible surfaces of monomeric proteins. To test if cooperative behavior occurs between the atoms for these surfaces, we construct a set of randomized surfaces, which obey a very simple stereochemical constraint. We find that the observed and randomized distributions are much more similar than the previous sets we examined. This implies that while surfaces of soluble proteins must have sufficient polar content, the relative placement of atoms of one amino acid with respect to the atoms of neighboring amino acid need not be finely tuned, which provides an innate robustness for protein design and folding.     

A novel method for isolation of membrane proteins: a baculovirus surface display system

We have developed a novel baculovirus surface display (BVSD) system for the isolation of membrane proteins. We expressed a reporter gene that encoded hemagglutinin gene fused in frame with the signal peptide and transmembrane domain of the baculovirus gp64 protein, which is displayed on the surface of BmNPV virions. The expression of this fusion protein on the virion envelope allowed us to develop two methods for isolating membrane proteins. In the first method, we isolated proteins directly from the envelope of budding BmNPV virions. In the second method, we isolated proteins from cellular membranes that had disintegrated due to viral egress. We isolated 6756 proteins. Of these, 1883 have sequence similarities to membrane proteins and 1550 proteins are homologous to known membrane proteins. This study indicates that membrane proteins can be effectively isolated using our BVSD system. Using an analogous method, membrane proteins can be isolated from other eukaryotic organisms, including human beings, by employing a host cell-specific budding virus.     

Fast accurate evaluation of protein solvent exposure

Protein solvation energies are often taken to be proportional to solvent-accessible surface areas. Computation of these areas is numerically demanding and may become a bottleneck for folding and design applications. Fast graph-based methods, such as dead-end elimination (DEE), become possible if all energies, including solvation energies, are expressed as single-residue and pair-residue terms. To this end, Street and Mayo originated a pair-residue approximation for solvent-accessible surface areas (Street AG, Mayo SL. Pairwise calculation of protein solvent accessible surface areas. Fold Des 1998;3:253-258). The dominant source of error in this method is the overlapping burial of side-chain surfaces in the protein core. Here we report a new pair-residue approximation, which greatly reduces this overlap error by the use of optimized generic side-chains. We have tested the generic-side-chain method for the ten proteins studied by Street and Mayo and for 377 single-domain proteins from the CATH database (Orengo CA, Michie AD, Jones S, Jones DT, Swindells MB, Thornton JM. CATH-A hierarchic classification of protein domain structures. Structure 1997;5:1093-1108). With little additional cost in computation, the new method consistently reduces error for total areas and residue-by-residue areas by more than a factor of two. For example, the residue-by-residue error (for buried area) is reduced from 7.42 A(2) to 3.70 A(2). This difference translates into a solvation energy difference of approximately 0.2 kcal/mol per residue, amounting to a reduction in root-mean-square energy error of 2 kcal/mol for a 100 residue chain, a potentially critical difference for both protein folding and design applications.     

Establishment of cell surface engineering and its development

Cell surface display of proteins/peptides has been established based on mechanisms of localizing proteins to the cell surface. In contrast to conventional intracellular and extracellular (secretion) expression systems, this method, generally called an arming technology, is particularly effective when using yeasts as a host, because the control of protein folding that is often required for the preparation of proteins can be natural. This technology can be employed for basic and applied research purposes. In this review, I describe various strategies for the construction of engineered yeasts and provide an outline of the diverse applications of this technology to industrial processes such as the production of biofuels and chemicals, as well as bioremediation and health-related processes. Furthermore, this technology is suitable for novel protein engineering and directed evolution through high-throughput screening, because proteins/peptides displayed on the cell surface can be directly analyzed using intact cells without concentration and purification. Functional proteins/peptides with improved or novel functions can be created using this beneficial, powerful, and promising technique.     

Searching for protein signatures using a multilevel alphabet

Short motifs are known to play diverse roles in proteins, such as in mediating the interactions with other molecules, binding to membranes, or conducting a specific biological function. Standard approaches currently employed to detect short motifs in proteins search for enrichment of amino acid motifs considering mostly the sequence information. Here, we presented a new approach to search for common motifs (protein signatures) which share both physicochemical and structural properties, looking simultaneously at different features. Our method takes as an input an amino acid sequence and translates it to a new alphabet that reflects its intrinsic structural and chemical properties. Using the MEME search algorithm, we identified the proteins signatures within subsets of protein which encompass common sequence and structural information. We demonstrated that we can detect enriched structural motifs, such as the amphipathic helix, from large datasets of linear sequences, as well as predicting common structural properties (such as disorder, surface accessibility, or secondary structures) of known functional‐motifs. Finally, we applied the method to the yeast protein interactome and identified novel putative interacting motifs. We propose that our approach can be applied for de novo protein function prediction given either sequence or structural information. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Identification of protein functional surfaces by the concept of a split pocket

The function of a protein is often fulfilled via molecular interactions on its surfaces, so identifying the functional surface(s) of a protein is helpful for understanding its function. Here, we introduce the concept of a split pocket, which is a pocket that is split by a cognate ligand. We use a geometric approach that is site‐specific. Specifically, we first compute a set of all pockets in the protein with its ligand(s) and a set of all pockets with the ligand(s) removed and then compare the two sets of pockets to identify the split pocket(s) of the protein. To reduce the search space and expedite the process of surface partitioning, we design probe radii according to the physicochemical textures of molecules. Our method achieves a success rate of 96% on a benchmark test set. We conduct a large‐scale computation to identify ～19,000 split pockets from 11,328 structures (1.16 million potential pockets); for each pocket, we obtain residue composition, solvent‐accessible area, and molecular volume. With this database of split pockets, our method can be used to predict the functional surfaces of unbound structures. Indeed, the functional surface of an unbound protein may often be found from its similarity to remotely related bound forms that belong to distinct folds. Finally, we apply our method to identify glucose‐binding proteins, including unbound structures. Our study demonstrates the power of geometric and evolutionary matching for studying protein functional evolution and provides a framework for classifying protein functions by local spatial patterns of functional surfaces. Proteins 2009. © 2009 Wiley‐Liss, Inc.