An examination of the conservation of surface patch polarity for proteins

MOTIVATION: The solubility of a protein is crucial for its function and is therefore an evolutionary constraint. As the solubility of a protein is related to the distribution of polar and hydrophobic residues on its solvent accessible surface, such a constraint should provide a valuable insight into the evolution of protein surfaces. We examine how the surfaces of proteins have evolved by considering how the average hydrophobicities of patches of surface residues vary across homologous proteins. We derive distributions for the average hydrophobicity/philicity of surface patches at a residue-based level-which we refer to as the residue hydrophobic density. This is computed for a set of 28 monomeric proteins and their homologues. The resulting distributions are compared with a set of randomized sequences, with the same residue content. RESULTS: We find that the patches, involving typically more than 10 residues, maintain a more hydrophilic surface than one would expect from a random substitution model, indicating a cooperative behaviour for these surfaces residues in terms of this single variable. SUPPLEMENTARY INFORMATION: Additional plots for all of the proteins examined in this paper can be found at: http://www.ebi.ac.uk/~shanahan/PCon/index.html     

Dissecting subunit interfaces in homodimeric proteins

The subunit interfaces of 122 homodimers of known three-dimensional structure are analyzed and dissected into sets of surface patches by clustering atoms at the interface; 70 interfaces are single-patch, the others have up to six patches, often contributed by different structural domains. The average interface buries 1,940 A2 of the surface of each monomer, contains one or two patches burying 600-1,600 A2, is 65% nonpolar and includes 18 hydrogen bonds. However, the range of size and of hydrophobicity is wide among the 122 interfaces. Each interface has a core made of residues with atoms buried in the dimer, surrounded by a rim of residues with atoms that remain accessible to solvent. The core, which constitutes 77% of the interface on average, has an amino acid composition that resembles the protein interior except for the presence of arginine residues, whereas the rim is more like the protein surface. These properties of the interfaces in homodimers, which are permanent assemblies, are compared to those of protein-protein complexes where the components associate after they have independently folded. On average, subunit interfaces in homodimers are twice larger than in complexes, and much less polar due to the large fraction belonging to the core, although the amino acid compositions of the cores are similar in the two types of interfaces.     

Accounting for protein-solvent contacts facilitates design of nonaggregating lattice proteins

The folding specificity of proteins can be simulated using simplified structural models and knowledge-based pair-potentials. However, when the same models are used to simulate systems that contain many proteins, large aggregates tend to form. In other words, these models cannot account for the fact that folded, globular proteins are soluble. Here we show that knowledge-based pair-potentials, which include explicitly calculated energy terms between the solvent and each amino acid, enable the simulation of proteins that are much less aggregation-prone in the folded state. Our analysis clarifies why including a solvent term improves the foldability. The aggregation for potentials without water is due to the unrealistically attractive interactions between polar residues, causing artificial clustering. When a water-based potential is used instead, polar residues prefer to interact with water; this leads to designed protein surfaces rich in polar residues and well-defined hydrophobic cores, as observed in real protein structures. We developed a simple knowledge-based method to calculate interactions between the solvent and amino acids. The method provides a starting point for modeling the folding and aggregation of soluble proteins. Analysis of our simple model suggests that inclusion of these solvent terms may also improve off-lattice potentials for protein simulation, design, and structure prediction.     

Dissecting protein-protein recognition sites

The recognition sites in 70 pairwise protein-protein complexes of known three-dimensional structure are dissected in a set of surface patches by clustering atoms at the interface. When the interface buries <2000 A2 of protein surface, the recognition sites usually form a single patch on the surface of each component protein. In contrast, larger interfaces are generally multipatch, with at least one pair of patches that are equivalent in size to a single-patch interface. Each recognition site, or patch within a site, contains a core made of buried interface atoms, surrounded by a rim of atoms that remain accessible to solvent in the complex. A simple geometric model reproduces the number and distribution of atoms within a patch. The rim is similar in composition to the rest of the protein surface, but the core has a distinctive amino acid composition, which may help in identifying potential protein recognition sites on single proteins of known structures.     

Molecular dynamics simulation of solvated azurin: correlation between surface solvent accessibility and water residence times

A system containing the globular protein azurin and 3,658 water molecules has been simulated to investigate the influence on water dynamics exerted by a protein surface. Evaluation of water mean residence time for elements having different secondary structure did not show any correlation. Identically, comparison of solvent residence time for atoms having different charge and polarity did not show any clear trend. The main factor influencing water residence time in proximity to a specific site was found to be its solvent accessibility. In detail for atoms belonging to lateral chains and having solvent-accessible surface lower than approximately 16 A(2)a relation is found for which charged and polar atoms are surrounded by water molecules characterized by residence times longer than the non polar ones. The involvement of the low accessible protein atom in an intraprotein hydrogen bond further modulates the length of the water residence time. On the other hand for surfaces having high solvent accessibility, all atoms, independently of their character, are surrounded by water molecules which rapidly exchange with the bulk solvent. Proteins 2000;39:56-67.     

Mapping of protein surface cavities and prediction of enzyme class by a self-organizing neural network

An automated computer-based method for mapping of protein surface cavities was developed and applied to a set of 176 metalloproteinases containing zinc cations in their active sites. With very few exceptions, the cavity search routine detected the active site among the five largest cavities and produced reasonable active site surfaces. Cavities were described by means of solvent-accessible surface patches. For a given protein, these patches were calculated in three steps: (i) definition of cavity atoms forming surface cavities by a grid-based technique; (ii) generation of solvent accessible surfaces; (iii) assignment of an accessibility value and a generalized atom type to each surface point. Topological correlation vectors were generated from the set of surface points forming the cavities, and projected onto the plane by a self-organizing network. The resulting map of 865 enzyme cavities displays clusters of active sites that are clearly separated from the other cavities. It is demonstrated that both fully automated recognition of active sites, and prediction of enzyme class can be performed for novel protein structures at high accuracy.     

Structural and genomic correlates of hyperthermostability

While most organisms grow at temperatures ranging between 20 and 50 degrees C, many archaea and a few bacteria have been found capable of withstanding temperatures close to 100 degrees C, or beyond, such as Pyrococcus or Aquifex. Here we report the results of two independent large scale unbiased approaches to identify global protein properties correlating with an extreme thermophile lifestyle. First, we performed a comparative proteome analyses using 30 complete genome sequences from the three kingdoms. A large difference between the proportions of charged versus polar (noncharged) amino acids was found to be a signature of all hyperthermophilic organisms. Second, we analyzed the water accessible surfaces of 189 protein structures belonging to mesophiles or hyperthermophiles. We found that the surfaces of hyperthermophilic proteins exhibited the shift already observed at the genomic level, i.e. a proportion of solvent accessible charged residues strongly increased at the expense of polar residues. The biophysical requirements for the presence of charged residues at the protein surface, allowing protein stabilization through ion bonds, is therefore clearly imprinted and detectable in all genome sequences available to date.     

Computational protein design with explicit consideration of surface hydrophobic patches

De novo protein design requires the identification of amino-acid sequences that favor the target-folded conformation and are soluble in water. One strategy for promoting solubility is to disallow hydrophobic residues on the protein surface during design. However, naturally occurring proteins often have hydrophobic amino acids on their surface that contribute to protein stability via the partial burial of hydrophobic surface area or play a key role in the formation of protein-protein interactions. A less restrictive approach for surface design that is used by the modeling program Rosetta is to parameterize the energy function so that the number of hydrophobic amino acids designed on the protein surface is similar to what is observed in naturally occurring monomeric proteins. Previous studies with Rosetta have shown that this limits surface hydrophobics to the naturally occurring frequency (～28%), but that it does not prevent the formation of hydrophobic patches that are considerably larger than those observed in naturally occurring proteins. Here, we describe a new score term that explicitly detects and penalizes the formation of hydrophobic patches during computational protein design. With the new term, we are able to design protein surfaces that include hydrophobic amino acids at naturally occurring frequencies, but do not have large hydrophobic patches. By adjusting the strength of the new score term, the emphasis of surface redesigns can be switched between maintaining solubility and maximizing folding free energy.     

Achieving stability and conformational specificity in designed proteins via binary patterning

We have developed a method to determine the optimal binary pattern (arrangement of hydrophobic and polar amino acids) of a target protein fold prior to amino acid sequence selection in protein design studies. A solvent accessible surface is generated for a target fold using its backbone coordinates and "generic" side-chains, which are constructs whose size and shape are similar to an average amino acid. Each position is classified as hydrophobic or polar according to the solvent exposure of its generic side-chain. The method was tested by analyzing a set of proteins in the Protein Data Bank and by experimentally constructing and analyzing a set of engrailed homeodomain variants whose binary patterns were systematically varied. Selection of the optimal binary pattern results in a designed protein that is monomeric, well-folded, and hyperthermophilic. Homeodomain variants with fewer hydrophobic residues are destabilized, while additional hydrophobic residues induce aggregation. Binary patterning, in conjunction with a force field that models folded state energies, appears sufficient to satisfy two basic goals of protein design: stability and conformational specificity.     

Charge-Rich Regions Modulate the Anti-Aggregation Activity of Hsp90

Protein aggregation can have dramatic effects on cellular function and plays a causative role in many human diseases. In all cells, molecular chaperones bind to aggregation-prone proteins and hinder aggregation. The ability of a protein to resist aggregation and remain soluble in aqueous solution is linked to the physical properties of the protein. Numerous physical studies demonstrate that charged atoms favor solubility. We note that many molecular chaperones possess a substantial negative charge that may allow them to impart solubility on aggregation-prone proteins. Hsp90 is one such negatively charged molecular chaperone. The charge on Hsp90 is largely concentrated in two highly acidic regions. To investigate the relationship between chaperone charge and protein solubility, we deleted these charge-rich regions and analyzed the resulting Hsp90 constructs for anti-aggregation activity. We found that deletion of both charge-rich regions dramatically impaired Hsp90 anti-aggregation activity. The anti-aggregation role of the deleted charge-rich regions could be due to net charge or sequence-specific features. To distinguish these possibilities, we attached an acid-rich region with a distinct amino acid sequence to our double-deleted Hsp90 construct. This charge rescue construct displayed effective anti-aggregation activity indicating that the net charge of Hsp90 contributes to its anti-aggregation activity.     

Prediction of protein-protein interactions based on surface patch comparison

A method to predict if two proteins interact, based on their three-dimensional structures, is presented. It consists of five steps: (i) the surface of each protein, represented by the solvent accessible atoms, is divided into small patches; (ii) the shape of each patch is described by the atom distributions along its principal axes; (iii) the shape complementarity between two patches is estimated by comparing, through contingency table analysis, their atom distributions along their principal axes; (iv) given protein A, with nA surface patches, and protein B, with nB surface patches, nA x nB shape complementarity values are obtained; and (v) the distribution of the latter allows one to discriminate pairs of interacting and of noninteracting proteins. Only a few seconds are necessary to predict if two proteins interact, with accuracy close to 80%, sensitivity over 70% and specificity close to 50%.     

QSE: A new 3-D solvent exposure measure for the analysis of protein structure

Solvent exposure of amino acids measures how deep residues are buried in tertiary structure of proteins, and hence it provides important information for analyzing and predicting protein structure and functions. Existing methods of calculating solvent exposure such as accessible surface area, relative accessible surface area, residue depth, contact number, and half-sphere exposure still have some limitations. In this article, we propose a novel solvent exposure measure named quadrant-sphere exposure (QSE) based on eight quadrants derived from spherical neighborhood. The proposed measure forms a microenvironment around Cα atom as a sphere with a radius of 13??, and subdivides it into eight quadrants according to a rectangular coordinate system constructed based on geometric relationships of backbone atoms. The number of neighboring Cα atoms whose labels are the same is given as the QSE value of the center Cα atom at hand. As evidenced by histograms that show very different distributions for different structure configurations, the proposed measure captures local properties that are characteristic for a residue's eight-directional neighborhood within a sphere. Compared with other measures, QSE provides a different view of solvent exposure, and provides information that is specific for different tertiary structure. As the experimental results show, QSE measure can potentially be used in protein structure analysis and predictions.     

Interior and surface of monomeric proteins

The solvent-accessible surface area (As) of 46 monomeric proteins is calculated using atomic co-ordinates from high-resolution and well-refined crystal structures. The As of these proteins can be determined to within 1 to 2% and that of their individual residues to within 10 to 20%. The As values of proteins are correlated with their molecular weight (Mr) in the range 4000 to 35,000: the power law As = 6.3 M0.73 predicts protein As values to within 4% on average. The average water-accessible surface is found to be 57% non-polar, 24% polar and 19% charged, with 5% root-mean-square variations. The molecular surface buried inside the protein is 58% non-polar, 39% polar and 4% charged. The buried surface contains more uncharged polar groups (mostly peptides) than the surface that remains accessible, but many fewer charged groups. On average, 15% of residues in small proteins and 32% in larger ones may be classed as "buried residues", having less than 5% of their surface accessible to the solvent. The accessibilities of most other residues are evenly distributed in the range 5 to 50%. Although the fraction of buried residues increases with molecular weight, the amino acid compositions of the protein interior and surface show no systematic variation with molecular weight, except for small proteins that are often very rich in buried cysteines. From amino acid compositions of protein surfaces and interiors we calculate an effective coefficient of partition for each type of residue, and derive an implied set of transfer free energy values. This is compared with other sets of partition coefficients derived directly from experimental data. The extent to which groups of residues (charged, polar and non-polar) are buried within proteins correlates well with their hydrophobicity derived from amino acid transfer experiments. Within these three groups, the correlation is low.     

Amino acid side-chain partition energies and distribution of residues in soluble proteins

Energies required to transfer amino acid side chains from water to less polar environments were calculated from results of several studies and compared with several statistical analyses of residue distributions in soluble proteins. An analysis that divides proteins into layers parallel with their surfaces is more informative than those that simply classify residues as exposed or buried. Most residues appear to be distributed as a function of the distance from the protein-water interface in a manner consistent with partition energies calculated from partitioning of amino acids between water and octanol phases and from solubilities of amino acids in water, ethanol, and methanol. Lys, Arg, Tyr, and Trp residues tend to concentrate near the water-protein interface where their apolar side-chain components are more buried than their polar side-chain components. Residue distributions calculated in this manner do not correlate well with side-chain solvation energies calculated from vapor pressures of side-chain analogs over a water phase. Results of statistical studies that classify residues as exposed to solvent or buried inside the protein interior appear to depend on the method used to classify residues. Data from some of these studies correlate better with solvation energies, but other data correlate better with partition energies. Most other statistical methods that have been used to evaluate effects of water on residue distributions yield results that correlate better with partition energies than with solvation energies.     

Analysis of amino acid contributions to protein solubility using short peptide tags fused to a simplified BPTI variant

Protein solubility is usually characterized in terms of a hydrophobicity scale, which refers to the free energy of transfer of a molecule from an aqueous to a nonpolar solution and is not a "solubility propensity scale" per se. Using a "host-guest" approach, we measured the effects of short poly-amino-acid tags (guests) on the solubility of a host protein, a simplified bovine pancreatic trypsin inhibitor (BPTI), to which they were fused at the C-terminus. We analyzed 10 amino acid types, representing the full range of biophysical properties (acidic, basic, polar, and hydrophobic). As anticipated, positively charged residues significantly increased the solubility of the model protein, at both pH 4.7 and 7.7, whereas very hydrophobic poly-Ile markedly reduced the solubility of BPTI. Poly-Asp and poly-Glu barely affected BPTI solubility at pH 4.7, but induced an eight to ten-fold increase at pH 7.7, attributable to the ionization of their side chains. Although Pro is the most soluble amino acid, poly-Pro did not affect the protein's solubility. The effects of the other tags on BPTI solubility ranged from none to an eight-fold increase. To ensure that the measured solubility values were context independent and could provide a "solubility propensity scale", we confirmed that the tags remained independent of the structure, thermal stability, and biochemical activity of the host protein. These observations suggest that this approach is valuable for measuring the solubility propensities of amino acids, which could eventually allow the calculation of a polypeptide's relative solubility from its amino acid sequence.     

Quantification of protein surfaces,volumes and atom-atom contacts using a constrained Voronoi procedure

MOTIVATION: Geometric representations of proteins and ligands, including atom volumes, atom-atom contacts and solvent accessible surfaces, can be used to characterize interactions between and within proteins, ligands and solvent. Voronoi algorithms permit quantification of these properties by dividing structures into cells with a one-to-one correspondence with constituent atoms. As there is no generally accepted measure of atom-atom contacts, a continuous analytical representation of inter-atomic contacts will be useful. Improved geometric algorithms will also be helpful in increasing the speed and accuracy of iterative modeling algorithms. RESULTS: We present computational methods based on the Voronoi procedure that provide rapid and exact solutions to solvent accessible surfaces, volumes, and atom contacts within macromolecules. Furthermore, we define a measure of atom-atom contact that is consistent with the calculation of solvent accessible surfaces, allowing the integration of solvent accessibility and inter-atomic contacts into a continuous measure. The speed and accuracy of the algorithm is compared to existing methods for calculating solvent accessible surfaces and volumes. The presented algorithm has a reduced execution time and greater accuracy compared to numerical and approximate analytical surface calculation algorithms, and a reduced execution time and similar accuracy to existing Voronoi procedures for calculating atomic surfaces and volumes.     

Exploring the environmental preference of weak interactions in (alpha/beta)8 barrel proteins

The environmental preference for the occurrence of noncanonical hydrogen bonding and cation-pi interactions, in a data set containing 71 nonredundant (alpha/beta)(8) barrel proteins, with respect to amino acid type, secondary structure, solvent accessibility, and stabilizing residues has been performed. Our analysis reveals some important findings, which include (a) higher contribution of weak interactions mediated by main-chain atoms irrespective of the amino acids involved; (b) domination of the aromatic amino acids among interactions involving side-chain atoms; (c) involvement of strands as the principal secondary structural unit, accommodating cross strand ion pair interaction and clustering of aromatic amino acid residues; (d) significant contribution to weak interactions occur in the solvent exposed areas of the protein; (e) majority of the interactions involve long-range contacts; (f) the preference of Arg is higher than Lys to form cation-pi interaction; and (g) probability of theoretically predicted stabilizing amino acid residues involved in weak interaction is higher for polar amino acids such as Trp, Glu, and Gln. On the whole, the present study reveals that the weak interactions contribute to the global stability of (alpha/beta)(8) TIM-barrel proteins in an environment-specific manner, which can possibly be exploited for protein engineering applications.     

Modelling of solvent positions around polar groups in proteins

Previous analysis of the distribution of experimental solvent molecule positions around amino acid side chains showed that distinct clustering occurred close to polar or charged atoms in proteins. We have used those data to predict likely solvent positions around proteins not used in our initial analysis. We envisage that this algorithm, AQUARIUS, will be useful for finding solvent positions in electron density maps generated by protein crystallography and as useful starting positions for solvent molecules in computer simulation studies of macromolecules.