SURF’s UP! — Protein classification by surface comparisons

Large-scale genome sequencing and structural genomics projects generate numerous sequences and structures for 'hypothetical' proteins without functional characterizations. Detection of homology to experimentally characterized proteins can provide functional clues, but the accuracy of homology-based predictions is limited by the paucity of tools for quantitative comparison of diverging residues responsible for the functional divergence. SURF'S UP! is a web server for analysis of functional relationships in protein families, as inferred from protein surface maps comparison according to the algorithm. It assigns a numerical score to the similarity between patterns of physicochemical features(charge, hydrophobicity) on compared protein surfaces. It allows recognizing clusters of proteins that have similar surfaces, hence presumably similar functions. The server takes as an input a set of protein coordinates and returns files with "spherical coordinates" of proteins in a PDB format and their graphical presentation, a matrix with values of mutual similarities between the surfaces, and the unrooted tree that represents the clustering of similar surfaces, calculated by the neighbor-joining method. SURF'S UP! facilitates the comparative analysis of physicochemical features of the surface, which are the key determinants of the protein function. By concentrating on coarse surface features, SURF'S UP! can work with models obtained from comparative modelling. Although it is designed to analyse the conservation among homologs, it can also be used to compare surfaces of non-homologous proteins with different three-dimensional folds, as long as a functionally meaningful structural superposition is supplied by the user. Another valuable characteristic of our method is the lack of initial assumptions about the functional features to be compared. SURF'S UP! is freely available for academic researchers at http://asia.genesilico.pl/surfs_up/.     

Assisted assignment of ligands corresponding to unknown electron density

A semi-automated computational procedure to assist in the identification of bound ligands from unknown electron density has been developed. The atomic surface surrounding the density blob is compared to a library of three-dimensional ligand binding surfaces extracted from the Protein Data Bank (PDB). Ligands corresponding to surfaces which share physicochemical texture and geometric shape similarities are considered for assignment. The method is benchmarked against a set of well represented ligands from the PDB, in which we show that we can identify the correct ligand based on the corresponding binding surface. Finally, we apply the method during model building and refinement stages from structural genomics targets in which unknown density blobs were discovered. A semi-automated computational method is described which aims to assist crystallographers with assigning the identity of a ligand corresponding to unknown electron density. Using shape and physicochemical similarity assessments between the protein surface surrounding the density and a database of known ligand binding surfaces, a plausible list of candidate ligands are identified for consideration. The method is validated against highly observed ligands from the Protein Data Bank and results are shown from its use in a high-throughput structural genomics pipeline.     

Molecular recognition: 3D surface structure comparison by gnomonic projection

This paper outlines a method for gnomonic projection of a molecular surface and a novel application of it to the problem of surface comparison. Semiregular arrays of points are generated by icosahedral tessellation. The surface may be the accessible surface or a chemical parameter surface such as the molecular electrostatic potential. Gnomonic projection retains the 3D characteristics of the inspection surface. Comparison of two surfaces can be achieved by statistical assessment of the pattern match. The method opens the gateway to an optimized search for pattern matches on the surfaces of dissimilar molecular structures.     

Single bacteriorhodopsin molecules revealed on both surfaces of freeze- dried and heavy metal-decorated purple membranes

The flat sheets of the purple membrane from Halobacterium halobium contain only a single protein (bacteriorhodopsin) arranged in a hexagonal lattice. After freeze-drying at -80 degrees C (a method that is superior to air-drying), shadowing with tantalum/tungsten, and image processing, structural details on both surfaces are portrayed in the range of 2 nm. One surface is rough and lattice lines are clearly visible, whereas the other is smooth and the hexagonal order seems to be absent. The optical diffraction patterns, however, indicate a hexagonal lattice for both surfaces. In addition, these diffraction patterns are characteristic and easily distinguished. The orientation of the two surfaces was identified by silver decoration: partial condensation of silver on purple membranes enabled the smooth surface to be identified as the plasmatic and the rough surface as the exoplasmic surface. After image processing, the exoplasmic surface shows a triplet structure which exactly fits the projected structure determined by Unwin and Henderson (1975. Nature(Lond.). 257:28-32) at molecular resolution, whereas, on the plasmatic surface, four image details per unit cell are visible. Three of them match the arrangement of bacteriorhodopsin, whereas the fourth must be located over a lipidic array. Summarizing these results, it is possible to show the part of each single bacteriorhodopsin protein that is present in the surfaces of the purple membrane. By "shadowing" the membranes perpendicularly, we prove that these components of the surfaces are mainly portrayed by a decoration effect of the tantalum/tungsten condensate.     

Molecular recognition: identification of local minima for matching in rotational 3-space by cluster analysis

This paper outlines a method for identifying discrete structural matches between molecular parameter surfaces by cluster analysis. The method is an integral part of a minimization search procedure for surface comparisons between dissimilar molecules described in the preceding paper. Priority is given in this study to the discovery of orientations having parameter matches near to the global minimum in dissimilarity.     

A photo-electroactive surface strategy for immobilizing ligands in patterns and gradients for studies of cell polarization

We report a combined photochemical and electrochemical method to pattern ligands and cells in complex geometries and gradients on inert surfaces. This work demonstrates: (1) the control of density of immobilized ligands within overlapping photopatterns, and (2) the attached cell culture patterned onto ligand defined gradients for studies of directional cell polarity. Our approach is based on the photochemical activation of benzoquinonealkanethiols. Immobilization of aminooxy terminated ligands in selected region of the quinone monolayer resulted in patterns on the surface. This approach is unique in that the extent of photochemical deprotection, as well as ligand immobilization can be monitored and quantified by cyclic voltammetry in situ. Furthermore, complex photochemical patterns of single or multiple ligands can be routinely generated using photolithographic masks. Finally, this methodology is completely compatible with attached cell culture and we show how the subtle interplay between cell-cell interactions and underlying peptide gradient influences cell polarization. The combined use of photochemistry, electrochemistry and well defined surface chemistry provides molecular level control of patterned ligands and gradients on surfaces.     

Searching for geometric molecular shape complementarity using bidimensional surface profiles

The study presented herein is a bidimensional approach to the complementarity of two molecular surfaces. From two chosen sections we have established a methodology of generating the optimal matching of two shapes. Our approach consists in describing two molecular surface sections by a shape vector (the angular profile), in finding their matching patterns by comparison of the two profiles, and in optimizing the relative locations of the two sections in two-dimensional space, using rotations and translations defined by geometric characteristics. The set of optimal configurations are successively displayed on a screen. Satisfying results have been obtained for the matching of the complex kallikreine Atrypsin pancreatic bovin 2. This efficient method could be used as a preprocessing for a tridimensional shape complementarity approach between two molecular surfaces.     

Evaluating molecular similarity using reduced representations of the electron density

A model system of four benzodiazepine-like ligands for the central benzodiazepine receptors (CBRs) and peripheral benzodiazepine receptors (PBRs)is examined using a genetic algorithm procedure (GAGS) designed for evaluating molecular similarity. The method is based on the alignment of reduced representations generated from the critical points of the electron density computed at medium crystallographic resolution. The results are further characterized by a comparison with alignments produced by MIMIC, a field-based superimposition method that matches both steric and electrostatic molecular fields. The alignments produced by the two methods are generally seen to be consistent. The relationships of the compounds' binding affinities for both CBRs and PBRs to the alignments determined by GAGS yield a set of structural features required for significant binding to benzodiazepine receptors. Benefits of using reduced representations for evaluating molecular similarities and for constructing pharmacophore models are discussed.     

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.     

Proteomic characterization of isolated retinal pigment epithelium microvilli

Polarized epithelial cells are characterized by displaying compartmentalized functions associated with differential distribution of transporters, structural proteins, and signaling molecules on their apical and basolateral surfaces. Their apical surfaces frequently elaborate microvilli, which vary in structure according to the specific type and function of each epithelium. The molecular basis of this heterogeneity is poorly understood. However, differences in function will undoubtedly be reflected in the specific molecular composition of the apical surface in each epithelial subtype. We have exploited a method for isolating microvilli from the mouse eye using wheat germ agglutinin (WGA)-agarose beads to begin to understand the specific molecular composition of apical microvilli of the retinal pigment epithelium (RPE) and expand our knowledge of the potential function of this interface. Initially, apical RPE plasma membranes bound to WGA beads were processed for morphological analysis using known apical and basolateral surface markers. The protein composition of the apical microvilli was then established using proteomic analysis. Over 200 proteins were identified, including a number of proteins previously known to be localized to RPE microvilli, as well as others not known to be present at this surface. Localization of novel proteins identified with proteomics was confirmed by immunohistochemistry in both mouse and rat eye tissue. The data generated provides new information on the protein composition of the RPE apical microvilli. The isolation technique used should be amenable for isolating microvilli in other epithelia as well, allowing new insights into additional functions of this important epithelial compartment.     

Within the twilight zone: a sensitive profile-profile comparison tool based on information theory

This paper presents a novel approach to profile-profile comparison. The method compares two input profiles (like those that are generated by PSI-BLAST) and assigns a similarity score to assess their statistical similarity. Our profile-profile comparison tool, which allows for gaps, can be used to detect weak similarities between protein families. It has also been optimized to produce alignments that are in very good agreement with structural alignments. Tests show that the profile-profile alignments are indeed highly correlated with similarities between secondary structure elements and tertiary structure. Exhaustive evaluations show that our method is significantly more sensitive in detecting distant homologies than the popular profile-based search programs PSI-BLAST and IMPALA. The relative improvement is the same order of magnitude as the improvement of PSI-BLAST relative to BLAST. Our new tool often detects similarities that fall within the twilight zone of sequence similarity.     

Molecular dynamics effects on protein electrostatics

Electrostatic calculations have been carried out on a number of structural conformers of tuna cytochrome c. Conformers were generated using molecular dynamics simulations with a range of solvent simulating, macroscopic dielectric formalisms, and one solvent model that explicitly included solvent water molecules. Structures generated using the lowest dielectric models were relatively tight, with side chains collapsed on the surface, while those from the higher dielectric models had more internal and external fluidity, with surface side chains exploring a fuller range of conformational space. The average structure generated with the explicitly solvated model corresponded most closely with the crystal structure. Individual pK values, overall titration curves, and electrostatic potential surfaces were calculated for average structures and structures along each simulation. Differences between structural conformers within each simulation give rise to substantial changes in calculated local electrostatic interactions, resulting in pK value fluctuations for individual sites in the protein that vary by 0.3-2.0 pK units from the calculated time average. These variations are due to the thermal side chain reorientations that produce fluctuations in charge site separations. Properties like overall titration curves and pH dependent stability are not as sensitive to side chain fluctuations within a simulation, but there are substantial effects between simulations due to marked differences in average side chain behavior. These findings underscore the importance of proper dielectric formalism in molecular dynamics simulations when used to generate alternate solution structures from a crystal structure, and suggest that conformers significantly removed from the average structure have altered electrostatic properties that may prove important in episodic protein properties such as catalysis.     

Shape group studies of molecular similarity: relative shapes of Van der Waals and electrostatic potential surfaces of nicotinic agonists

In drug design, the usual strategy involves characterizing and comparing the shapes of molecules. We apply a simple method to accomplish this goal: determining the symmetry-independent shape groups (homology groups of algebraic topology) of a molecular surface.In this paper, we have adapted the method to describing the interrelation between Van der Waals and electrostatic potential surfaces. We describe rigorously the shape features in a series of molecules by using specific ranges of electrostatic potential over a Van der Waals surface. We consider a series of four nicotinic agonists as an example and discuss their expected activities as potential drugs on the basis of the shape similarities found.     

SEM observations on petals and fruits of some Turkish endemic Bupleurum L. (Umbelliferae) species

Petal and fruit surface sculpturing are reported for seven endemic Bupleurum species in Turkey. Considerable differences in the dorsal surface of petals were observed, but major structural similarities were found in the ventral surface of petals. Significant taxonomic differences between species were determined on the surfaces of the fruits. These microstructural surface features are evaluated as possible consistent parameters in the delimitation of species of Bupleurum. © 2002 The Linnean Society of London, Botanical Journal of the Linnean Society , 2002, 138 , 441–449.     

HOLLOW: Generating Accurate Representations of Channel and Interior Surfaces in Molecular Structures

Background  

An accurate rendering of interior surfaces can facilitate the analysis of mechanisms at atomic-level detail, such as the transport of substrates in the ammonia channel. In molecular viewers, one must remove the exterior surface that obscures the channel surface by clipping the viewing plane or manually selecting the channel residues in order to display a partial surface. Neither method is entirely satisfactory, as unwanted additional pieces of surfaces are always generated.     

Three-dimensional, sequence order-independent structural comparison of a serine protease against the crystallographic database reveals active site similarities: potential implications to evolution and to protein folding.

We have recently developed a fast approach to comparisons of 3-dimensional structures. Our method is unique, treating protein structures as collections of unconnected points (atoms) in space. It is completely independent of the amino acid sequence order. It is unconstrained by insertions, deletions, and chain directionality. It matches single, isolated amino acids between 2 different structures strictly by their spatial positioning regardless of their relative sequential position in the amino acid chain. It automatically detects a recurring 3D motif in protein molecules. No predefinition of the motif is required. The motif can be either in the interior of the proteins or on their surfaces. In this work, we describe an enhancement over our previously developed technique, which considerably reduces the complexity of the algorithm. This results in an extremely fast technique. A typical pairwise comparison of 2 protein molecules requires less than 3 s on a workstation. We have scanned the structural database with dozens of probes, successfully detecting structures that are similar to the probe. To illustrate the power of this method, we compare the structure of a trypsin-like serine protease against the structural database. Besides detecting homologous trypsin-like proteases, we automatically obtain 3D, sequence order-independent, active-site similarities with subtilisin-like and sulfhydryl proteases. These similarities equivalence isolated residues, not conserving the linear order of the amino acids in the chains. The active-site similarities are well known and have been detected by manually inspecting the structures in a time-consuming, laborious procedure. This is the first time such equivalences are obtained automatically from the comparison of full structures. The far-reaching advantages and the implications of our novel algorithm to studies of protein folding, to evolution, and to searches for pharmacophoric patterns are discussed.     

Geometric and potential driving formation and evolution of biomolecular surfaces

This paper presents new geometrical flow equations for the theoretical modeling of biomolecular surfaces in the context of multiscale implicit solvent models. To account for the local variations near the biomolecular surfaces due to interactions between solvent molecules, and between solvent and solute molecules, we propose potential driven geometric flows, which balance the intrinsic geometric forces that would occur for a surface separating two homogeneous materials with the potential forces induced by the atomic interactions. Stochastic geometric flows are introduced to account for the random fluctuation and dissipation in density and pressure near the solvent–solute interface. Physical properties, such as free energy minimization (area decreasing) and incompressibility (volume preserving), are realized by some of our geometric flow equations. The proposed approach for geometric and potential forces driving the formation and evolution of biological surfaces is illustrated by extensive numerical experiments and compared with established minimal molecular surfaces and molecular surfaces. Local modification of biomolecular surfaces is demonstrated with potential driven geometric flows. High order geometric flows are also considered and tested in the present work for surface generation. Biomolecular surfaces generated by these approaches are typically free of geometric singularities. As the speed of surface generation is crucial to implicit solvent model based molecular dynamics, four numerical algorithms, a semi-implicit scheme, a Crank–Nicolson scheme, and two alternating direction implicit (ADI) schemes, are constructed and tested. Being either stable or conditionally stable but admitting a large critical time step size, these schemes overcome the stability constraint of the earlier forward Euler scheme. Aided with the Thomas algorithm, one of the ADI schemes is found to be very efficient as it balances the speed and accuracy.      

Mutualism versus pathogenesis: the give-and-take in plant–bacteria interactions

Pathogenic bacteria and mutualistic rhizobia are able to invade and establish chronic infections within their host plants. The success of these plant–bacteria interactions requires evasion of the plant innate immunity by either avoiding recognition or by suppressing host defences. The primary plant innate immunity is triggered upon recognition of common microbe-associated molecular patterns. Different studies reveal striking similarities between the molecular bases underlying the perception of rhizobial nodulation factors and microbe-associated molecular patterns from plant pathogens. However, in contrast to general elicitors, nodulation factors can control plant defences when recognized by their cognate legumes. Nevertheless, in response to rhizobial infection, legumes show transient or local defence-like responses suggesting that Rhizobium is perceived as an intruder although the plant immunity is controlled. Whether these responses are involved in limiting the number of infections or whether they are required for the progression of the interaction is not yet clear. Further similarities in both plant–pathogen and Rhizobium –legume associations are factors such as surface polysaccharides, quorum sensing signals and secreted proteins, which play important roles in modulating plant defence responses and determining the outcome of the interactions.     

Extracting Hydrogen-Bond Signature Patterns from Protein Structure Data

Classification of protein sequences and structures into families is a fundamental task in biology, and it is often used as a basis for designing experiments for gaining further knowledge. Some relationships between proteins are detected by the similarities in their sequences, and many more by the similarities in their structures. Despite this, there are a number of examples of functionally similar molecules without any recognisable sequence or structure similarities, and there are also a number of protein molecules that share common structural scaffolds but exhibit different functions. Newer methods of comparing molecules are required in order to detect similarities and dissimilarities in protein molecules. In this article, it is proposed that the precise 3-dimensional disposition of key residues in a protein molecule is what matters for its function, or what conveys the "meaning" for a biological system, but not what means it uses to achieve this. The concept of comparing two molecules through their intramolecular interaction networks is explored, since these networks dictate the disposition of amino acids in a protein structure. First, signature patterns, or fingerprints, of interaction networks in pre-classified protein structural families are computed using an approach to find structural equivalences and consensus hydrogen bonds. Five examples from different structural classes are illustrated. These patterns are then used to search the entire Protein Data Bank, an approach through which new, unexpected similarities have been found. The potential for finding relationships through this approach is highlighted. The use of hydrogen-bond fingerprints as a new metric for measuring similarities in protein structures is also described.