A method for detecting hydrophobic patches on protein surfaces

An atomistic characterization of high-density lipoproteins and the conserved "LN" region of apoA-I

The physicochemical characteristics of the various subpopulations of high-density lipoproteins (HDLs) and, in particular, their surface properties determine their ability to scavenge lipids and interact with specific receptors and peptides. Five representative spheroidal HDL subpopulation models were mapped from a previously reported equilibrated coarse-grained (CG) description to an atomistic representation for subsequent molecular dynamics simulation. For each HDL model a range of finer-level analyses was undertaken, including the component-wise characterization of HDL surfaces, the average size and composition of hydrophobic surface patches, dynamic protein secondary structure monitoring, and the proclivity for solvent exposure of the proposed β-amyloid (Aβ) binding region of apolipoprotein A-I (apoA-I), "LN." This study reveals that previously characterized ellipsoidal HDL3a and HDL2a models revert to a more spherical geometry in an atomistic representation due to the enhanced conformational flexibility afforded to the apoA-I protein secondary structure, allowing for enhanced surface lipid packing and lower overall surface hydrophobicity. Indeed, the proportional surface hydrophobicity and apoA-I exposure reduced with increasing HDL size, consistent with previous characterizations. Furthermore, solvent exposure of the "LN" region of apoA-I was exclusively limited to the smallest HDL3c model within the timescale of the simulations, and typically corresponded to a distinct loss in secondary structure across the "LN" region to form part of a significant contiguous hydrophobic patch on the HDL surface. Taken together, these findings provide preliminary evidence for a subpopulation-specific interaction between HDL3c particles and circulating hydrophobic species such as Aβ via the exposed "LN" region of apoA-I.

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

How sticky are our proteins? Quantifying hydrophobicity of the human proteome

Summary

Proteins tend to bury hydrophobic residues inside their core during the folding process to provide stability to the protein structure and to prevent aggregation. Nevertheless, proteins do expose some 'sticky' hydrophobic residues to the solvent. These residues can play an important functional role, e.g. in protein-protein and membrane interactions. Here, we first investigate how hydrophobic protein surfaces are by providing three measures for surface hydrophobicity: the total hydrophobic surface area, the relative hydrophobic surface area and-using our MolPatch method-the largest hydrophobic patch. Secondly, we analyze how difficult it is to predict these measures from sequence: by adapting solvent accessibility predictions from NetSurfP2.0, we obtain well-performing prediction methods for the THSA and RHSA, while predicting LHP is more challenging. Finally, we analyze implications of exposed hydrophobic surfaces: we show that hydrophobic proteins typically have low expression, suggesting cells avoid an overabundance of sticky proteins.

Availability and implementation

The data underlying this article are available in GitHub at https://github.com/ibivu/hydrophobic_patches.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

De novo protein design by an energy function based on series expansion in distance and orientation dependence

MOTIVATION

Despite many successes, de novo protein design is not yet a solved problem as its success rate remains low. The low success rate is largely because we do not yet have an accurate energy function for describing the solvent-mediated interaction between amino acid residues in a protein chain. Previous studies showed that an energy function based on series expansions with its parameters optimized for side-chain and loop conformations can lead to one of the most accurate methods for side chain (OSCAR) and loop prediction (LEAP). Following the same strategy, we developed an energy function based on series expansions with the parameters optimized in four separate stages (recovering single-residue types without and with orientation dependence, selecting loop decoys and maintaining the composition of amino acids). We tested the energy function for de novo design by using Monte Carlo simulated annealing.

RESULTS

The method for protein design (OSCAR-Design) is found to be as accurate as OSCAR and LEAP for side-chain and loop prediction, respectively. In de novo design, it can recover native residue types ranging from 38% to 43% depending on test sets, conserve hydrophobic/hydrophilic residues at ∼75%, and yield the overall similarity in amino acid compositions at more than 90%. These performance measures are all statistically significantly better than several protein design programs compared. Moreover, the largest hydrophobic patch areas in designed proteins are near or smaller than those in native proteins. Thus, an energy function based on series expansion can be made useful for protein design.

AVAILABILITY AND IMPLEMENTATION

The Linux executable version is freely available for academic users at http://zhouyq-lab.szbl.ac.cn/resources/.

Solvation Free Energy as a Measure of Hydrophobicity: Application to Serine Protease Binding Interfaces

Solvation and hydrophobicity play a key role in a variety of biological mechanisms. In substrate binding, but also in structure-based drug design, the thermodynamic properties of water molecules surrounding a given protein are of high interest. One of the main algorithms devised in recent years to quantify thermodynamic properties of water is the grid inhomogeneous solvation theory (GIST), which calculates these features on a grid surrounding the protein. Despite the inherent advantages of GIST, the computational demand is a major drawback, as calculations for larger systems can take days or even weeks. Here, we present a GPU accelerated version of the GIST algorithm, which facilitates efficient estimates of solvation free energy even of large biomolecular interfaces. Furthermore, we show that GIST can be used as a reliable tool to evaluate protein surface hydrophobicity. We apply the approach on a set of nine different proteases calculating localized solvation free energies on the surface of the binding interfaces as a measure of their hydrophobicity. We find a compelling agreement with the hydrophobicity of their substrates, i.e., peptides, binding into the binding cleft, and thus our approach provides a reliable description of hydrophobicity characteristics of these biological interfaces.

Design on a Rational Basis of High-Affinity Peptides Inhibiting the Histone Chaperone ASF1

Anti-silencing function 1 (ASF1) is a conserved H3-H4 histone chaperone involved in histone dynamics during replication, transcription, and DNA repair. Overexpressed in proliferating tissues including many tumors, ASF1 has emerged as a promising therapeutic target. Here, we combine structural, computational, and biochemical approaches to design peptides that inhibit the ASF1-histone interaction. Starting from the structure of the human ASF1-histone complex, we developed a rational design strategy combining epitope tethering and optimization of interface contacts to identify a potent peptide inhibitor with a dissociation constant of 3 nM. When introduced into cultured cells, the inhibitors impair cell proliferation, perturb cell-cycle progression, and reduce cell migration and invasion in a manner commensurate with their affinity for ASF1. Finally, we find that direct injection of the most potent ASF1 peptide inhibitor in mouse allografts reduces tumor growth. Our results open new avenues to use ASF1 inhibitors as promising leads for cancer therapy.

Non-invasive high throughput approach for protein hydrophobicity determination based on surface tension

The surface hydrophobicity of a protein is an important factor for its interactions in solution and thus the outcome of its production process. Yet most of the methods are not able to evaluate the influence of these hydrophobic interactions under natural conditions. In the present work we have established a high resolution stalagmometric method for surface tension determination on a liquid handling station, which can cope with accuracy as well as high throughput requirements. Surface tensions could be derived with a low sample consumption (800 μL) and a high reproducibility (<0.1‰ for water) within a reasonable time (3.5 min per sample). This method was used as a non-invasive HTP compatible approach to determine surface tensions of protein solutions dependent on protein content. The protein influence on the solutions' surface tension was correlated to the hydrophobicity of lysozyme, human lysozyme, BSA, and α-lactalbumin. Differences in proteins' hydrophobic character depending on pH and species could be resolved. Within this work we have developed a pH dependent hydrophobicity ranking, which was found to be in good agreement with literature. For the studied pH range of 3-9 lysozyme from chicken egg white was identified to be the most hydrophilic. α-lactalbumin at pH 3 exhibited the most pronounced hydrophobic character. The stalagmometric method occurred to outclass the widely used spectrophotometric method with bromophenol blue sodium salt as it gave reasonable results without restrictions on pH and protein species.

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central “hubs”. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.

Several non-native proteins require molecular chaperones for proper folding. Many unfolded proteins if not folded accurately, become causal factors in various types of misfolding or aggregation induced diseases such as Alzheimer′s, Huntington′s and several other neurodegenerative disorders. However, structural information of non-folded proteins especially chaperone-dependent proteins is difficult to probe experimentally due to their inherent aggregation propensities. In this work, we study DapA protein, which exhibits obligate requirement on GroEL chaperonin machinery for its folding. We use molecular dynamics simulations to reveal populated intermediate structures of DapA in atomic details. The most plausible intermediate was found to be in agreement with recently reported hydrogen-exchange experimental data. Significant increase in surface exposed hydrophobicity was observed in intermediates compared to native, which was further validated using ANS binding experiments. We also constructed network model of these intermediates that provides remarkable insights into stable hubs (or important residues) underlying diverse states of unfolded proteins. In summary, our work provides a molecular picture of an unfolded protein that is en route to chaperone binding, and these underlying structural properties might act as a molecular signal for their productive folding.

Algorithmic approaches to protein-protein interaction site prediction

Interaction sites on protein surfaces mediate virtually all biological activities, and their identification holds promise for disease treatment and drug design. Novel algorithmic approaches for the prediction of these sites have been produced at a rapid rate, and the field has seen significant advancement over the past decade. However, the most current methods have not yet been reviewed in a systematic and comprehensive fashion. Herein, we describe the intricacies of the biological theory, datasets, and features required for modern protein-protein interaction site (PPIS) prediction, and present an integrative analysis of the state-of-the-art algorithms and their performance. First, the major sources of data used by predictors are reviewed, including training sets, evaluation sets, and methods for their procurement. Then, the features employed and their importance in the biological characterization of PPISs are explored. This is followed by a discussion of the methodologies adopted in contemporary prediction programs, as well as their relative performance on the datasets most recently used for evaluation. In addition, the potential utility that PPIS identification holds for rational drug design, hotspot prediction, and computational molecular docking is described. Finally, an analysis of the most promising areas for future development of the field is presented.

Predicting enzyme adsorption to lignin films by calculating enzyme surface hydrophobicity

The inhibitory action of lignin on cellulase cocktails is a major challenge to the biological saccharification of plant cell wall polysaccharides. Although the mechanism remains unclear, hydrophobic interactions between enzymes and lignin are hypothesized to drive adsorption. Here we evaluate the role of hydrophobic interactions in enzyme-lignin binding. The hydrophobicity of the enzyme surface was quantified using an estimation of the clustering of nonpolar atoms, identifying potential interaction sites. The adsorption of enzymes to lignin surfaces, measured using the quartz crystal microbalance, correlates to the hydrophobic cluster scores. Further, these results suggest a minimum hydrophobic cluster size for a protein to preferentially adsorb to lignin. The impact of electrostatic contribution was ruled out by comparing the isoelectric point (pI) values to the adsorption of proteins to lignin surfaces. These results demonstrate the ability to predict enzyme-lignin adsorption and could potentially be used to design improved cellulase cocktails, thus lowering the overall cost of biofuel production.

Energy functions in de novo protein design: current challenges and future prospects

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.

Versatility and invariance in the evolution of homologous heteromeric interfaces

Evolutionary pressures act on protein complex interfaces so that they preserve their complementarity. Nonetheless, the elementary interactions which compose the interface are highly versatile throughout evolution. Understanding and characterizing interface plasticity across evolution is a fundamental issue which could provide new insights into protein-protein interaction prediction. Using a database of 1,024 couples of close and remote heteromeric structural interologs, we studied protein-protein interactions from a structural and evolutionary point of view. We systematically and quantitatively analyzed the conservation of different types of interface contacts. Our study highlights astonishing plasticity regarding polar contacts at complex interfaces. It also reveals that up to a quarter of the residues switch out of the interface when comparing two homologous complexes. Despite such versatility, we identify two important interface descriptors which correlate with an increased conservation in the evolution of interfaces: apolar patches and contacts surrounding anchor residues. These observations hold true even when restricting the dataset to transiently formed complexes. We show that a combination of six features related either to sequence or to geometric properties of interfaces can be used to rank positions likely to share similar contacts between two interologs. Altogether, our analysis provides important tracks for extracting meaningful information from multiple sequence alignments of conserved binding partners and for discriminating near-native interfaces using evolutionary information.

Unraveling how interfaces of protein complexes coevolved is of major importance to improve our ability to predict their structures and design novel binders. Proteins whose interaction was maintained throughout evolution generally have their homologs binding in a similar manner while their sequences can have significantly diverged. Constraints holding proteins together should be captured from the growing body of available multiple sequence alignments. However, it remains unclear which features of the interfaces provide most tolerance to mutations and it is unknown whether any invariant properties may help to extract meaningful signals from sequence alignments. To solve this issue, we tackled an unprecedented large scale analysis of more than 1000 non-redundant couples of structural interologs. Structural interologs are pairs of complexes of known structure whose chains are homologs. We quantitatively measured how the networks of contacts varied between two interfaces. Although highly versatile, we found that contact networks were more conserved for residues acting as anchors and for apolar contacts when they are clustered into surface patches. Altogether, our results provide major guidelines for exploiting the wealth of evolutionary information contained in the sequences of binding partners. On those bases we developed a method to predict which residues most likely conserve their contacts.

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.

Effect of PEG end-group hydrophobicity on lysozyme interactions in solution characterized by light scattering

We compare protein-protein and protein-polymer osmotic virial coefficients measured by static light scattering for aqueous solutions of lysozyme with low-molecular-weight, hydroxy-terminated (hPEG) and methyl-terminated (mPEG) poly(ethylene glycol) at two solution conditions: pH 7.0 and 0.01 M ionic strength, and pH 6.2 and 0.8 M ionic strength. We find that adding PEG to aqueous lysozyme solutions makes a net repulsive contribution to lysozyme-lysozyme interactions, independent of ionic strength and PEG end-group hydrophobicity. PEG end-group hydrophobicity has a profound effect on the magnitude of this contribution, however, at low ionic strength where mPEG-lysozyme attractive interactions become significant. The enhanced attractions promote mPEG-lysozyme preferential interactions at the expense of lysozyme self-interactions, which leads to lysozyme-lysozyme interactions that are more repulsive in the presence of mPEG. These preferential interactions also lead to the preferential exclusion of diffusable ions locally around the protein, which results in a pronounced ionic strength dependence of mPEG-mediated lysozyme-lysozyme interactions.

In vitro evolved non-aggregating and thermostable lipase: structural and thermodynamic investigation

Rational and in vitro evolutionary approaches to improve either protein stability or aggregation resistance were successful, but empirical rules for simultaneous improvement of both stability and aggregation resistance under denaturing conditions are still to be ascertained. We have created a robust variant of a lipase from Bacillus subtilis named "6B" using multiple rounds of in vitro evolution. T(m) and optimum activity temperature of 6B is 78 °C and 65 °C, respectively, which is ~22 °C and 30 °C higher than that of wild-type lipase. Most significantly, 6B does not aggregate upon heating. Physical basis of remarkable thermostability and non-aggregating behavior of 6B was explored using X-ray crystallography, NMR and differential scanning calorimetry. Our structural investigations highlight the importance of tightening of mobile regions of the molecule such as loops and helix termini to attain higher thermostability. Accordingly, NMR studies suggest a very rigid structure of 6B lipase. Further investigation suggested that reduction/perturbation of the large hydrophobic patches present in the wild-type protein structure, decreased propensity of amino acid sequence for aggregation and absence of aggregation-prone intermediate during thermal unfolding of 6B can account for its resistance to aggregation. Overall, our study suggest that better anchoring of the loops with the rest of the protein molecule through mutations particularly on the sites that perturb/disturb the exposed hydrophobic patches can simultaneously increase protein stability and aggregation resistance.

Structural analysis of protein folding by the long-chain archaeal chaperone FKBP26

In the cell, protein folding is mediated by folding catalysts and chaperones. The two functions are often linked, especially when the catalytic module forms part of a multidomain protein, as in Methanococcus jannaschii peptidyl-prolyl cis/trans isomerase FKBP26. Here, we show that FKBP26 chaperone activity requires both a 50-residue insertion in the catalytic FKBP domain, also called 'Insert-in-Flap' or IF domain, and an 80-residue C-terminal domain. We determined FKBP26 structures from four crystal forms and analyzed chaperone domains in light of their ability to mediate protein-protein interactions. FKBP26 is a crescent-shaped homodimer. We reason that folding proteins are bound inside the large crescent cleft, thus enabling their access to inward-facing peptidyl-prolyl cis/trans isomerase catalytic sites and ipsilateral chaperone domain surfaces. As these chaperone surfaces participate extensively in crystal lattice contacts, we speculate that the observed lattice contacts reflect a proclivity for protein associations and represent substrate interactions by FKBP26 chaperone domains. Finally, we find that FKBP26 is an exceptionally flexible molecule, suggesting a mechanism for nonspecific substrate recognition.

Nanoscale dewetting transition in protein complex folding

In a previous study, a surprising drying transition was observed to take place inside the nanoscale hydrophobic channel in the tetramer of the protein melittin. The goal of this paper is to determine if there are other protein complexes capable of displaying a dewetting transition during their final stage of folding. We searched the entire protein data bank (PDB) for all possible candidates, including protein tetramers, dimers, and two-domain proteins, and then performed the molecular dynamics (MD) simulations on the top candidates identified by a simple hydrophobic scoring function based on aligned hydrophobic surface areas. Our large scale MD simulations found several more proteins, including three tetramers, six dimers, and two two-domain proteins, which display a nanoscale dewetting transition in their final stage of folding. Even though the scoring function alone is not sufficient (i.e., a high score is necessary but not sufficient) in identifying the dewetting candidates, it does provide useful insights into the features of complex interfaces needed for dewetting. All top candidates have two features in common: (1) large aligned (matched) hydrophobic areas between two corresponding surfaces, and (2) large connected hydrophobic areas on the same surface. We have also studied the effect on dewetting of different water models and different treatments of the long-range electrostatic interactions (cutoff vs PME), and found the dewetting phenomena is fairly robust. This work presents a few proteins other than melittin tetramer for further experimental studies of the role of dewetting in the end stages of protein folding.

Structure and Dynamics of Hydrogen Bonds in the Interface of a C12E6 Spherical Micelle in Water Solution: A MD Study at Various Temperatures

The temperature dehydration of a C(12)E(6) spherical micelle is characterized through the study of the structure and dynamics of the hydrogen bonds formed by water within the micellar interface. Water molecules in proximity of the hydrophilic fragment of the C(12)E(6) surfactants form strong H-bonds with the oxyethilene units E and with the polar alcoholic heads. The activation energies of such H-bonds fall in the range 2-3 Kcal mol(-1). On the exposed oil core, the number of water-water H-bonds decreases as an effect of dehydration. The dynamics of such bonds exhibits a slow relaxation with respect to the bulk, and two time scales can be discerned: the first one, tau approximately 3-6 ps, is typical of water-water H-bonds around small hydrophobic molecules, whereas the second one, tau approximately 40-80 ps, is probably due to the confining effect of the long hydrophilic fragments which reduces the probability of a water molecule to leave the hydration layer of the exposed oil core. Water molecules around the core form H-bond clusters whose size and distribution change with temperature. From a cluster analysis, the system appears to be below the percolation threshold, suggesting that the exposed oily surface is formed by disconnected patches of size around 1 nm(2), close to the estimate of the solvated hydrophobic patches on protein surfaces. The network connectivity is also considered for concentric hydration shells along the interface: it turns out that near the oil core, the cluster size is larger than elsewhere in the interface demonstrating a strong structural effect induced by the exposed hydrocarbon tails. Temperature affects the cluster size only in the innermost shell.

Optimal docking area: a new method for predicting protein-protein interaction sites

Understanding energetics and mechanism of protein-protein association remains one of the biggest theoretical problems in structural biology. It is assumed that desolvation must play an essential role during the association process, and indeed protein-protein interfaces in obligate complexes have been found to be highly hydrophobic. However, the identification of protein interaction sites from surface analysis of proteins involved in non-obligate protein-protein complexes is more challenging. Here we present Optimal Docking Area (ODA), a new fast and accurate method of analyzing a protein surface in search of areas with favorable energy change when buried upon protein-protein association. The method identifies continuous surface patches with optimal docking desolvation energy based on atomic solvation parameters adjusted for protein-protein docking. The procedure has been validated on the unbound structures of a total of 66 non-homologous proteins involved in non-obligate protein-protein hetero-complexes of known structure. Optimal docking areas with significant low-docking surface energy were found in around half of the proteins. The 'ODA hot spots' detected in X-ray unbound structures were correctly located in the known protein-protein binding sites in 80% of the cases. The role of these low-surface-energy areas during complex formation is discussed. Burial of these regions during protein-protein association may favor the complexed configurations with near-native interfaces but otherwise arbitrary orientations, thus driving the formation of an encounter complex. The patch prediction procedure is freely accessible at http://www.molsoft.com/oda and can be easily scaled up for predictions in structural proteomics.

Morphological aspects of oligomeric protein structures

Features of multimeric proteins are reviewed to shed light on the formation of protein assemblies from a structural perspective. The features comprise biochemical and geometric properties. They are compiled on new low-redundancy sets of crystal structures of homomeric proteins with different symmetry and subunit multiplicity, as well as on a set of heteromeric proteins. Crystal structures of likely monomers provide a control group.

Crystal structure of the mosquito-larvicidal toxin Cry4Ba and its biological implications

Cry4Ba, isolated from Bacillus thuringiensis subsp. israelensis, is specifically toxic to the larvae of Aedes and Anopheles mosquitoes. The structure of activated Cry4Ba toxin has been determined by multiple isomorphous replacement with anomalous scattering and refined to R(cryst) = 20.5% and R(free)= 21.8% at 1.75 Angstroms resolution. It resembles previously reported Cry toxin structures but shows the following distinctions. In domain I the helix bundle contains only the long and amphipathic helices alpha3-alpha7. The N-terminal helices alpha1-alpha2b, absent due to proteolysis during crystallisation, appear inessential to toxicity. In domain II the beta-sheet prism presents short apical loops without the beta-ribbon extension of inner strands, thus placing the receptor combining sites close to the sheets. In domain III the beta-sandwich contains a helical extension from the C-terminal strand beta23, which interacts with a beta-hairpin excursion from the edge of the outer sheet. The structure provides a rational explanation of recent mutagenesis and biophysical data on this toxin. Furthermore, added to earlier structures from the Cry toxin family, Cry4Ba completes a minimal structural database covering the Coleoptera, Lepidoptera, Diptera and Lepidoptera/Diptera specificity classes. A multiple structure alignment found that the Diptera-specific Cry4Ba is structurally more closely similar to the Lepidoptera-specific Cry1Aa than the Coleoptera-specific Cry3Aa, but most distantly related to Lepidoptera/Diptera-specific Cry2Aa. The structures are most divergent in domain II, supporting the suggestion that this domain has a major role in specificity determination. They are most similar in the alpha3-alpha7 major fragment of domain I, which contains the alpha4-alpha5 hairpin crucial to pore formation. The collective knowledge of Cry toxin structure and mutagenesis data will lead to a more critical understanding of the structural basis for receptor binding and pore formation, as well as allowing the scope of diversity to be better appreciated.

ProMate: a structure based prediction program to identify the location of protein-protein binding sites

Is the whole protein surface available for interaction with other proteins, or are specific sites pre-assigned according to their biophysical and structural character? And if so, is it possible to predict the location of the binding site from the surface properties? These questions are answered quantitatively by probing the surfaces of proteins using spheres of radius of 10 A on a database (DB) of 57 unique, non-homologous proteins involved in heteromeric, transient protein-protein interactions for which the structures of both the unbound and bound states were determined. In structural terms, we found the binding site to have a preference for beta-sheets and for relatively long non-structured chains, but not for alpha-helices. Chemically, aromatic side-chains show a clear preference for binding sites. While the hydrophobic and polar content of the interface is similar to the rest of the surface, hydrophobic and polar residues tend to cluster in interfaces. In the crystal, the binding site has more bound water molecules surrounding it, and a lower B-factor already in the unbound protein. The same biophysical properties were found to hold for the unbound and bound DBs. All the significant interface properties were combined into ProMate, an interface prediction program. This was followed by an optimization step to choose the best combination of properties, as many of them are correlated. During optimization and prediction, the tested proteins were not used for data collection, to avoid over-fitting. The prediction algorithm is fully automated, and is used to predict the location of potential binding sites on unbound proteins with known structures. The algorithm is able to successfully predict the location of the interface for about 70% of the proteins. The success rate of the predictor was equal whether applied on the unbound DB or on the disjoint bound DB. A prediction is assumed correct if over half of the predicted continuous interface patch is indeed interface. The ability to predict the location of protein-protein interfaces has far reaching implications both towards our understanding of specificity and kinetics of binding, as well as in assisting in the analysis of the proteome.

Convergence in peptide folding simulation: Multiple trajectories of a potential AIDS pharmacophore

To examine the conformational properties in aqueous solution of a 15-residue peptide that is a potential pharmacophore for AIDS vaccine development, molecular dynamics simulations were performed in water starting from structures determined experimentally in three different organic solvents. Convergence characteristics of the simulation are examined in Cartesian and conformational spaces. In addition, novel analysis tools are employed including a multidimensional scaling method to represent the distance between trajectory frames. As these methods are based on a variety of physical parameters, they provide a useful cross-check on the structural convergence. Theoretical two-dimensional (2D) 1H-NMR spectra are also generated. These are superficially quite different in appearance, demonstrating that backbone similarities difficult to identify by visual inspection of 2D NMR data can be revealed using the methods described here.

Structure of the Epstein-Barr virus gp42 protein bound to the MHC class II receptor HLA-DR1

Epstein-Barr virus (EBV) causes infectious mononucleosis, establishes long-term latent infections, and is associated with a variety of human tumors. The EBV gp42 glycoprotein binds MHC class II molecules, playing a critical role in infection of B lymphocytes. EBV gp42 belongs to the C-type lectin superfamily, with homology to NK receptors of the immune system. We report the crystal structure of gp42 bound to the human MHC class II molecule HLA-DR1. The gp42 binds HLA-DR1 using a surface site that is distinct from the canonical lectin and NK receptor ligand binding sites. At the canonical ligand binding site, gp42 forms a large hydrophobic groove, which could interact with other ligands necessary for EBV entry, providing a mechanism for coupling MHC recognition and membrane fusion.

Prediction of protein surface accessibility with information theory

A new, simple method based on information theory is introduced to predict the solvent accessibility of amino acid residues in various states defined by their different thresholds. Prediction is achieved by the application of information obtained from a single amino acid position or pair-information for a window of seventeen amino acids around the desired residue. Results obtained by pairwise information values are better than results from single amino acids. This reinforces the effect of the local environment on the accessibility of amino acid residues. The prediction accuracy of this method in a jackknife test system for two and three states is better than 70 and 60 %, respectively. A comparison of the results with those reported by others involving the same data set also testifies to a better prediction accuracy in our case.

New structural and functional aspects of the type I interferon-receptor interaction revealed by comprehensive mutational analysis of the binding interface

Type I interferons bind to two cell surface receptors, ifnar1 and ifnar2, as the first step in the activation of several signal transduction pathways that elicit an anti-viral state and an anti-proliferative response. Here, we quantitatively mapped the complete binding region of ifnar2 on interferon (IFN)alpha2 by 35 individual mutations to alanine and isosteric residues. Of the six "hot-spot" residues identified (Leu-30, Arg-33, Arg-144, Ala-145, Met-148, and Arg-149), four are located on the E-helix, which is located at the center of the binding site flanked by residues on the A-helix and the AB-loop. The contribution of residues of the D-helix, which have been previously implicated in binding, proved to be marginal for the interaction with the extracellular domain of ifnar2. Interestingly, the ifnar2 binding site overlaps the largest continuous hydrophobic patch on IFNalpha2. Thus, hydrophobic interactions seem to play a significant role stabilizing this interaction, with the charged residues contributing toward the rapid association of the complex. Relating the anti-viral and anti-proliferative activity of the various interferon mutants with their affinity toward ifnar2 results in linear function over the whole range of affinities investigated, suggesting that ifnar2 binding is the rate-determining step in cellular activation. Dose-time analysis of the anti-viral response revealed that shortening the incubation time of low-level activation cannot be compensated by higher IFN doses. Considering the strict dependence of the cellular response on affinity, these results suggest that for maintaining transcription of IFN-responsive genes over a longer time period, low but continuous signaling through the IFN receptor is essential.

Sequencing and model structure of a Naja naja atra protein fragment

We report the amino acid sequence of a basic protein isolated from the snake venom of Naja naja atra. An automated Edman sequencer was used to determine the 65-residue sequence, aided by electrospray ionization/mass spectrometry. Online reduction and pyridylethylation of the peptide was performed to identify the cysteine residues. Trypsin, chymotrypsin and aspartic digestions were carried out to derive peptide fragments for further sequencing. Fragmented peptides were overlapped to obtain the complete sequence. Molecular mass measurements of the whole protein and its fragments were used as a countercheck for sequence assignment. Further confirmation of the sequence was indicated by sequence homology to other snake venom neurotoxins. A molecular model of the tertiary structure was constructed based on sequence homology, and was refined by global minimization and extensive quality control algorithms. Electrostatic and hydrophobic surface calculations and molecular dynamics simulations were carried out to determine the functional properties of the molecule.

The effect of vicinal polar and charged groups on hydrophobic hydration

The use of a linear relationship between free energy of hydrophobic hydration and solvent-accessible apolar surface area has been helpful in interpreting the thermodynamics of biological macromolecules. However, a recent study (Y.-K. Cheng, P. J. Rossky, Nature 1998, Vol. 392, pp. 696-699) has established a substantial enthalpic dependence on biomolecular surface topography, originating from solvent hydrogen-bonding loss in a restrictive geometry. In this study, we use molecular dynamics simulations of 2-Zn insulin in water solvent to explore the further effect of vicinal polar or charged groups on hydrophobic hydration at a biomolecular surface. In contrast to the case for solvent more isolated from such polar solute influences, the binding energies of the water that is proximal to the hydrophobic dimeric interface of insulin and vicinal to polar and charged groups are comparable to the bulk solvent value, a result of compensating interaction primarily with the solute counterions. The results suggest a special importance for such polar/charged groups in biological processes involving hydrophobic surface regions of restricted geometry and also suggest a general route for tuning the hydrophobicity of interfaces.

Modularity and homology: modelling of the type II module family from titin

We report the homology modelling of the structures of the 162 type II modules from the giant multi-domain protein titin (also known as connectin). The package MODELLER was used and implemented in an automated fashion using four experimentally determined structures as templates. Validation of the models was assessed in terms of divergence from the templates and consensus of the alignments. The homology within the whole family of type II modules as well as with the templates is relatively high (20-35% identity and ca 50% similarity). Comparison between the models of domains for which an NMR structure has been solved and the experimental solution gives an estimate of the quality of the modelling. Our results allow us to distinguish between a set of structurally relevant residues, which are conserved throughout the whole family and buried in the hydrophobic core, from the residues that are conserved and exposed. These latter residues are potentially functionally important. Comparison of exposed conserved patches for modules in different regions of the titin molecule suggests potential interaction surfaces. Our results may be tested directly for those modules whose binding partner is known.

Morphology of protein-protein interfaces

BACKGROUND

Most soluble proteins are active as low-number oligomers. Statistical surveys of oligomeric proteins have defined the roles of hydrophobicity and complementarity in the stability of protein interfaces, but tend to average structural features over a diverse set of protein-protein interfaces, blurring information on how individual interfaces are stabilized.

RESULTS

We report a visual survey of 136 homodimeric proteins from the Brookhaven Protein Data Bank, with images that highlight the major structural features of each protein-protein interaction surface. Nearly all of these proteins have interfaces formed between two globular subunits. Surprisingly, the pattern of hydrophilicity over the surface of these interfaces is quite variable. Approximately one-third of the interfaces show a recognizable hydrophobic core, with a single large, contiguous, hydrophobic patch surrounded by a ring of intersubunit polar interactions. The remaining two-thirds of the proteins show a varied mixture of small hydrophobic patches, polar interactions and water molecules scattered over the entire interfacial area. Ten proteins in the survey have intertwined interfaces formed by extensive interdigitation of the two subunit chains. These interfaces are very hydrophobic and are associated with proteins that require both stability and internal symmetry.

CONCLUSIONS

The archetypal protein interface, with a defined hydrophobic core, is present in only a minority of the surveyed homodimeric proteins. Most homodimeric proteins are stabilized by a combination of small hydrophobic patches, polar interactions and a considerable number of bridging water molecules. The presence or absence of a hydrophobic core within these interfaces does not correlate with specific protein functions.