CRK: An evolutionary approach for distinguishing biologically relevant interfaces from crystal contacts

Protein crystals contain two different types of interfaces: biologically relevant ones, observed in protein–protein complexes and oligomeric proteins, and nonspecific ones, corresponding to crystal lattice contacts. Because of the increasing complexity of the objects being tackled in structural biology, distinguishing biological contacts from crystal contacts is not always a trivial task and can lead to wrong interpretation of macromolecular structures. We devised an approach (CRK, core‐rim K_a/K_s ratio) for distinguishing biologically relevant interfaces from nonspecific ones. Given a protein–protein interface, CRK finds a set of homologs to the sequences of the proteins involved in the interface, retrieves and aligns the corresponding coding sequences, on which it carries out a residue‐by‐residue K_a/K_s ratio (ω) calculation. It divides interface residues into a “rim” and a “core” set and analyzes the selection pressure on the residues belonging to the two sets. We developed and tested CRK on different datasets and test cases, consisting of biologically relevant contacts, nonspecific ones or of both types. The method proves very effective in distinguishing the two categories of interfaces, with an overall accuracy rate of 84%. As it relies on different principles when compared with existing tools, CRK is optimally suited to be used in combination with them. In addition, CRK has potential applications in the validation of structures of oligomeric proteins and protein complexes. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Characterizing conserved structural contacts by pair-wise relative contacts and relative packing groups

To adequately deal with the inherent complexity of interactions between protein side-chains, we develop and describe here a novel method for characterizing protein packing within a fold family. Instead of approaching side-chain interactions absolutely from one residue to another, we instead consider the relative interactions of contacting residue pairs. The basic element, the pair-wise relative contact, is constructed from a sequence alignment and contact analysis of a set of structures and consists of a cluster of similarly oriented, interacting, side-chain pairs. To demonstrate this construct's usefulness in analyzing protein structure, we used the pair-wise relative contacts to analyze two sets of protein structures as defined by SCOP: the diverse globin-like superfamily (126 structures) and the more uniform heme binding globin family (a 94 structure subset of the globin-like superfamily). The superfamily structure set produced 1266 unique pair-wise relative contacts, whereas the family structure subset gave 1001 unique pair-wise relative contacts. For both sets, we show that these constructs can be used to accurately and automatically differentiate between fold classes. Furthermore, these pair-wise relative contacts correlate well with sequence identity and thus provide a direct relationship between changes in sequence and changes in structure. To capture the complexity of protein packing, these pair-wise relative contacts can be superimposed around a single residue to create a multi-body construct called a relative packing group. Construction of convex hulls around the individual packing groups provides a measure of the variation in packing around a residue and defines an approximate volume of space occupied by the groups interacting with a residue. We find that these relative packing groups are useful in understanding the structural quality of sequence or structure alignments. Moreover, they provide context to calculate a value for structural randomness, which is important in properly assessing the quality of a structural alignment. The results of this study provide the framework for future analysis for correlating sequence changes to specific structure changes.     

1D2DSimScore: A novel method for comparing contacts in biomacromolecules and their complexes

The biologically relevant structures of proteins and nucleic acids and their complexes are dynamic. They include a combination of regions ranging from rigid structural segments to structural switches to regions that are almost always disordered, which interact with each other in various ways. Comparing conformational changes and variation in contacts between different conformational states is essential to understand the biological functions of proteins, nucleic acids, and their complexes. Here, we describe a new computational tool, 1D2DSimScore, for comparing contacts and contact interfaces in all kinds of macromolecules and macromolecular complexes, including proteins, nucleic acids, and other molecules. 1D2DSimScore can be used to compare structural features of macromolecular models between alternative structures obtained in a particular experiment or to score various predictions against a defined “ideal” reference structure. Comparisons at the level of contacts are particularly useful for flexible molecules, for which comparisons in 3D that require rigid-body superpositions are difficult, and in biological systems where the formation of specific inter-residue contacts is more relevant for the biological function than the maintenance of a specific global 3D structure. Similarity/dissimilarity scores calculated by 1D2DSimScore can be used to complement scores describing 3D structural similarity measures calculated by the existing tools.     

Protein-protein crystal-packing contacts.

Protein-protein contacts in monomeric protein crystal structures have been analyzed and compared to the physiological protein-protein contacts in oligomerization. A number of features differentiate the crystal-packing contacts from the natural contacts occurring in multimeric proteins. The area of the protein surface patches involved in packing contacts is generally smaller and its amino acid composition is indistinguishable from that of the protein surface accessible to the solvent. The fraction of protein surface in crystal contacts is very variable and independent of the number of packing contacts. The thermal motion at the crystal packing interface and that of the protein core, even for large packing interfaces, though the tendency is to be closer to that of the core. These results suggest that protein crystallization depends on random protein-protein interactions, which have little in common with physiological protein-protein recognition processes, and that the possibility of engineering macromolecular crystallization to improve crystal quality could be widened.     

The limit of accuracy of protein modeling: influence of crystal packing on protein structure

The size of the protein database (PDB) makes it now feasible to arrive at statistical conclusions regarding structural effects of crystal packing. These effects are relevant for setting upper practical limits of accuracy on protein modeling. Proteins whose crystals have more than one molecule in the asymmetric unit or whose structures were determined at least twice by X-ray crystallography were paired and their differences analyzed. We demonstrate a clear influence of crystal environment on protein structure, including backbone conformations, hinge-like motions and side-chain conformations. The positions of surface water molecules tend to be variable in different crystal environments while those of ligands are not. Structures determined by independent groups vary more than structures determined by the same authors. The use of different refinement methods is a major source for this effect. Our pair-wise analysis derives a practical limit to the accuracy of protein modeling. For different crystal forms, the limit of accuracy (C(alpha), root-mean-square deviation (RMSD)) is approximately 0.8A for the entire protein, which includes approximately 0.3A due to crystal packing. For organized secondary elements, the upper limit of C(alpha) RMSD is 0.5-0.6A while for loops or protein surface it reaches 1.0A. Twenty percent of exposed side- chains exhibit different chi(1+2) conformations with approximately half of the effect also resulting from crystal packing. A web based tool for analysis and graphic presentation of surface areas of crystal contacts is available (http://ligin.weizmann.ac.il/cryco).     

Predicted residue–residue contacts can help the scoring of 3D models

During the 7th Critical Assessment of Protein Structure Prediction (CASP7) experiment, it was suggested that the real value of predicted residue–residue contacts might lie in the scoring of 3D model structures. Here, we have carried out a detailed reassessment of the contact predictions made during the recent CASP8 experiment to determine whether predicted contacts might aid in the selection of close‐to‐native structures or be a useful tool for scoring 3D structural models. We used the contacts predicted by the CASP8 residue–residue contact prediction groups to select models for each target domain submitted to the experiment. We found that the information contained in the predicted residue–residue contacts would probably have helped in the selection of 3D models in the free modeling regime and over the harder comparative modeling targets. Indeed, in many cases, the models selected using just the predicted contacts had better GDT‐TS scores than all but the best 3D prediction groups. Despite the well‐known low accuracy of residue–residue contact predictions, it is clear that the predictive power of contacts can be useful in 3D model prediction strategies. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Protein-RNA contacts at crystal packing surfaces

The crystal packing surfaces comprising protein-RNA interactions were analyzed for 50 RNA-protein crystal structures in the Protein Data Bank database. Protein-RNA crystal contacts, which represent nonspecific protein-RNA interfaces, were investigated for their amino acid propensities, hydrogen bond patterns, and backbone and side chain interactions. When compared to biologically relevant interactions, the protein-RNA crystal contacts exhibit similarities as well as differences with respect to the principles of protein-RNA interactions. Similar to what was observed at cognate protein-RNA interfaces, positively charged amino acids have high propensities at noncognate protein-RNA interfaces and preferentially form hydrogen bonds with RNA phosphate groups. In contrast, nonpolar residues are less frequently associated with noncognate interactions. These results highlight the important roles of both electrostatic and hydrogen bonding interactions, facilitated by positively charged amino acids, in mediating both specific and nonspecific protein-RNA interactions.     

Effects of protein engineering and rational mutagenesis on crystal lattice of single chain antibody fragments

Protein crystallization is dependent upon, and sensitive to, the intermolecular contacts that assist in ordering proteins into a three‐dimensional lattice. Here we used protein engineering and mutagenesis to affect the crystallization of single chain antibody fragments (scFvs) that recognize the EE epitope (EYMPME) with high affinity. These hypercrystallizable scFvs are under development to assist difficult proteins, such as membrane proteins, in forming crystals, by acting as crystallization chaperones. Guided by analyses of intermolecular crystal lattice contacts, two second‐generation anti‐EE scFvs were produced, which bind to proteins with installed EE tags. Surprisingly, although noncomplementarity determining region (CDR) lattice residues from the parent scFv framework remained unchanged through the processes of protein engineering and rational design, crystal lattices of the derivative scFvs differ. Comparison of energy calculations and the experimentally‐determined lattice interactions for this basis set provides insight into the complexity of the forces driving crystal lattice choice and demonstrates the availability of multiple well‐ordered surface features in our scFvs capable of forming versatile crystal contacts. Proteins 2014; 82:1884–1895. © 2014 Wiley Periodicals, Inc.     

Polymorphism of the epidermal growth factor receptor extracellular ligand binding domain: the dimer interface depends on domain stabilization

Epidermal growth factor receptors (EGFRs) and their cytoplasmic tyrosine kinases play important roles in cell proliferation and signaling. The EGFR extracellular domain (sEGFR) forms a dimer upon the binding of ligands, such as epidermal growth factor (EGF) and transforming growth factor α (TGFα). In this study, multiple molecular dynamics (MD) simulations of the 2:2 EGF·sEGFR3-512 dimer and the 2:2 TGFα·sEGFR3-512 dimer were performed in solvent and crystal environments. The simulations of systems comprising up to half a million atoms reveal part of the structural dynamics of which sEGFR dimers are capable. The solvent simulations consistently exhibited a prominent conformational relaxation from the initial crystal structures on the nanosecond time scale, leading to symmetry breaking and more extensive contacts between the two sEGFR monomers. In the crystal control simulation, this symmetry breaking and compaction was largely suppressed by crystal packing contacts. The simulations also provided evidence that the disordered domain IV of sEGFR may act as a stabilizing spacer in the dimer. Thus, the simulations suggest that the sEGFR dimer can take diverse configurations in solvent environments. These biologically relevant conformations of the EGFR signal transduction network can be controlled by contacts among the structural domains of sEGFR and its ligands.     

NOXclass: prediction of protein-protein interaction types

Background  

Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available.     

Comparison of the structures and the crystal contacts of trypanosomal triosephosphate isomerase in four different crystal forms.

Triosephosphate isomerase (TIM) is a dimeric enzyme consisting of 2 identical subunits. Trypanosomal TIM can be crystallized in 4 different spacegroups: P2(1)2(1)2(1), C2(big cell), C2(small cell), and P1. The P1 crystal form only grows in the presence of 1.4 M DMSO; there are 2 DMSO binding sites per subunit. The structures have been refined at a resolution of 1.83 A, 2.10 A, 2.13 A, and 1.80 A, respectively. In the 4 different spacegroups the TIM subunit can be observed in the context of 7 different crystallographic environments. In the C2 cells, the dimer 2-fold axis coincides with a crystallographic 2-fold axis. The similarities and differences of the 7 subunits are discussed. In 6 subunits the flexible loop (loop 6) is open, whereas in the P2(1)2(1)2(1) cell, the flexible loop of subunit 2 is in an almost closed conformation. The crystal contacts in the 4 different crystal forms are predominantly generated by polar residues in loops. A statistical analysis of the residues involved in crystal contacts shows that, in particular, serines are frequently involved in these interactions; 19% of the exposed serines are involved in crystal contacts.     

RosettaHoles2: A volumetric packing measure for protein structure refinement and validation

We present an improved version of RosettaHoles, a methodology for quantitative and visual characterization of protein core packing. RosettaHoles2 features a packing measure more rapidly computable, accurate and physically transparent, as well as a new validation score intended for structures submitted to the Protein Data Bank. The differential packing measure is parameterized to maximize the gap between computationally generated and experimentally determined X‐ray structures, and can be used in refinement of protein structure models. The parameters of the model provide insight into components missing in current force fields, and the validation score gives an upper bound on the X‐ray resolution of Protein Data Bank structures; a crystal structure should have a validation score as good as or better than its resolution.     

Conservation helps to identify biologically relevant crystal contacts.

Some crystal contacts are biologically relevant, most are not. We assess the utility of combining measures of size and conservation to discriminate between biological and non-biological contacts. Conservation and size information is calculated for crystal contacts in 53 families of homodimers and 65 families of monomers. Biological contacts are shown to be usually conserved and typically the largest contact in the crystal. A range of neural networks accepting different combinations and encodings of this information is used to answer the following questions: (1) is a given crystal contact biological, and (2) given all crystal contacts in a homodimer, which is the biological one? Predictions for (1) are performed on both homodimer and monomer datasets. The best performing neural network combined size and conservation inputs. For the homodimers, it correctly classified 48 out of 53 biological contacts and 364 out of 366 non-biological contacts, giving a combined accuracy of 98.3 %. A more robust performance statistic, the phi-coefficient, which accounts for imbalances in the dataset, gave a value of 0.92. Taking all 535 non-biological contacts from the 65 monomers, this predictor made erroneous classifications only 4.3 % of the time. Predictions for (2) were performed on homodimers only. The best performing network achieved a prediction accuracy of 98.1 % using size information alone. We conclude that in answering question (1) size and conservation combined discriminate biological from non-biological contacts better than either measure alone. For answering question (2), we conclude that in our dataset size is so powerful a discriminant that conservation adds little predictive benefit.     

CONFOLD: Residue‐residue contact‐guided ab initio protein folding

Predicted protein residue–residue contacts can be used to build three‐dimensional models and consequently to predict protein folds from scratch. A considerable amount of effort is currently being spent to improve contact prediction accuracy, whereas few methods are available to construct protein tertiary structures from predicted contacts. Here, we present an ab initio protein folding method to build three‐dimensional models using predicted contacts and secondary structures. Our method first translates contacts and secondary structures into distance, dihedral angle, and hydrogen bond restraints according to a set of new conversion rules, and then provides these restraints as input for a distance geometry algorithm to build tertiary structure models. The initially reconstructed models are used to regenerate a set of physically realistic contact restraints and detect secondary structure patterns, which are then used to reconstruct final structural models. This unique two‐stage modeling approach of integrating contacts and secondary structures improves the quality and accuracy of structural models and in particular generates better β‐sheets than other algorithms. We validate our method on two standard benchmark datasets using true contacts and secondary structures. Our method improves TM‐score of reconstructed protein models by 45% and 42% over the existing method on the two datasets, respectively. On the dataset for benchmarking reconstructions methods with predicted contacts and secondary structures, the average TM‐score of best models reconstructed by our method is 0.59, 5.5% higher than the existing method. The CONFOLD web server is available at http://protein.rnet.missouri.edu/confold/ . Proteins 2015; 83:1436–1449. © 2015 Wiley Periodicals, Inc.     

Participation of protein sequence termini in crystal contacts

The analysis of the crystal packing interactions, in a nonredundant set of high resolution and monomeric globular protein crystal structures, shows that the residues located at the N- and C-termini of the sequence tend to participate in packing interaction more often than expected and that often they interact with each other. Since the sequence termini are, in general, conformationally very flexible and since they host electrical charges of opposite sign, it can be hypothesized that they play a crucial role in the early formation of the nonphysiological contacts that bring to protein crystallization. It is thus not surprising that modest lengthening/shortening of the sequence termini have often a dramatic effect on protein crystallogenesis.     

Packing forces in nine crystal forms of cutinase

During the characterization of mutants and covalently inhibited complexes of Fusarium solani cutinase, nine different crystal forms have been obtained so far. Protein mutants with a different surface charge distribution form new intermolecular salt bridges or long-range electrostatic interactions that are accompanied by a change in the crystal packing. The whole protein surface is involved in the packing contacts and the hydrophobicities of the protein surfaces in mutual contact turned out to be noncorrelated, which indicates that the packing interactions are nonspecific. In the case of the hydrophobic variants, the packing contacts showed some specificity, as the protein in the crystal tends to form either crystallographic or noncrystallographic dimers, which shield the hydrophobic surface from the solvent. The likelihood of surface atoms to be involved in a crystal contact is the same for both polar and nonpolar atoms. However, when taking areas in the 200–600 Ų range, instead of individual atoms, the either highly hydrophobic or highly polar surface regions were found to have an increased probability of establishing crystal lattice contacts. The protein surface surrounding the active-site crevice of cutinase constitutes a large hydrophobic area that is involved in packing contacts in all the various crystalline contexts. Proteins 31:320–333, 1998. © 1998 Wiley-Liss, Inc.     

Describing Partially Unfolded States of Proteins from Sparse NMR Ddata

Proteins involved in signal transduction can usually be present in two states: an inactive and an active (signaling) state. In the case of photoreceptors such as PYP, it has been shown that the signaling state has a large degree of structural and dynamic disorder. Conventional structural NMR approaches present difficulties in describing such partially unfolded states. Owing to the disordered dynamical and transient nature of such states classical NOE-based information, when present, is sparse. Chemical shift changes upon partial unfolding can, however, be easily monitored from HSQC spectra. We show here that such states can be modeled by defining native-like inter-residue contacts for those residues that do not shift significantly upon partial unfolding. The feasibility of this approach is demonstrated using lysozyme as a test case and applied to model the partially unfolded signaling state (pB) of a truncated form of the photoactive yellow protein for which a “classical” NOE-based structure is available for validation. This approach should be generally applicable to systems in which part of the structure remains in a well-defined native-like conformation.     

Carbohydrate binding module recognition of xyloglucan defined by polar contacts with branching xyloses and CH‐Π interactions

Engineering of novel carbohydrate‐binding proteins that can be utilized in various biochemical and biotechnical applications would benefit from a deeper understanding of the biochemical interactions that determine protein‐carbohydrate specificity. In an effort to understand further the basis for specificity we present the crystal structure of the multi‐specific carbohydrate‐binding module (CBM) X‐2 L110F bound to a branched oligomer of xyloglucan (XXXG). X‐2 L110F is an engineered CBM that can recognize xyloglucan, xylans and β‐glucans. The structural observations of the present study compared with previously reported structures of X‐2 L110F in complex with linear oligomers, show that the π‐surface of a phenylalanine, F110, allows for interactions with hydrogen atoms on both linear (xylopentaose and cellopentaose) and branched ligands (XXXG). Furthermore, X‐2 L110F is shown to have a relatively flexible binding cleft, as illustrated in binding to XXXG. This branched ligand requires a set of reorientations of protein side chains Q72, N31, and R142, although these residues have previously been determined as important for binding to xylose oligomers by mediating polar contacts. The loss of these polar contacts is compensated for in binding to XXXG by polar interactions mediated by other protein residues, T74, R115, and Y149, which interact mainly with the branching xyloses of the xyloglucan oligomer. Taken together, the present study illustrates in structural detail how CH‐π interactions can influence binding specificity and that flexibility is a key feature for the multi‐specificity displayed by X‐2 L110F, allowing for the accommodation of branched ligands. Proteins 2014; 82:3466–3475. © 2014 Wiley Periodicals, Inc.     

Crystal packing effects on protein loops

The effects of crystal packing on protein loop structures are examined by (1) a comparison of loops in proteins that have been crystallized in alternate packing arrangements, and (2) theoretical prediction of loops both with and without the inclusion of the crystal environment. Results show that in a minority of cases, loop geometries are dependent on crystal packing effects. Explicit representation of the crystal environment in a loop prediction algorithm can be used to model these effects and to reconstruct the structures, and relative energies, of a loop in alternative packing environments. By comparing prediction results with and without the inclusion of the crystal environment, the loop prediction algorithm can further be used to identify cases in which a crystal structure does not represent the most stable state of a loop in solution. We anticipate that this capability has implications for structural biology.     

An amino acid code for β‐sheet packing structure

To understand the relationship between protein sequence and structure, this work extends the knob‐socket model in an investigation of β‐sheet packing. Over a comprehensive set of β‐sheet folds, the contacts between residues were used to identify packing cliques: sets of residues that all contact each other. These packing cliques were then classified based on size and contact order. From this analysis, the two types of four‐residue packing cliques necessary to describe β‐sheet packing were characterized. Both occur between two adjacent hydrogen bonded β‐strands. First, defining the secondary structure packing within β‐sheets, the combined socket or XY:HG pocket consists of four residues i, i+2 on one strand and j, j+2 on the other. Second, characterizing the tertiary packing between β‐sheets, the knob‐socket XY:H+B consists of a three‐residue XY:H socket (i, i+2 on one strand and j on the other) packed against a knob B residue (residue k distant in sequence). Depending on the packing depth of the knob B residue, two types of knob‐sockets are found: side‐chain and main‐chain sockets. The amino acid composition of the pockets and knob‐sockets reveal the sequence specificity of β‐sheet packing. For β‐sheet formation, the XY:HG pocket clearly shows sequence specificity of amino acids. For tertiary packing, the XY:H+B side‐chain and main‐chain sockets exhibit distinct amino acid preferences at each position. These relationships define an amino acid code for β‐sheet structure and provide an intuitive topological mapping of β‐sheet packing. Proteins 2014; 82:2128–2140. © 2014 Wiley Periodicals, Inc.