Verification of protein structures: patterns of nonbonded atomic interactions.

A novel method for differentiating between correctly and incorrectly determined regions of protein structures based on characteristic atomic interaction is described. Different types of atoms are distributed nonrandomly with respect to each other in proteins. Errors in model building lead to more randomized distributions of the different atom types, which can be distinguished from correct distributions by statistical methods. Atoms are classified in one of three categories: carbon (C), nitrogen (N), and oxygen (O). This leads to six different combinations of pairwise noncovalently bonded interactions (CC, CN, CO, NN, NO, and OO). A quadratic error function is used to characterize the set of pairwise interactions from nine-residue sliding windows in a database of 96 reliable protein structures. Regions of candidate protein structures that are mistraced or misregistered can then be identified by analysis of the pattern of nonbonded interactions from each window.     

A dissection of specific and non-specific protein-protein interfaces

We compare the geometric and physical-chemical properties of interfaces involved in specific and non-specific protein-protein interactions in crystal structures reported in the Protein Data Bank. Specific interactions are illustrated by 70 protein-protein complexes and by subunit contacts in 122 homodimeric proteins; non-specific interactions are illustrated by 188 pairs of monomeric proteins making crystal-packing contacts selected to bury more than 800 A2 of protein surface. A majority of these pairs have 2-fold symmetry and form "crystal dimers" that cannot be distinguished from real dimers on the basis of the interface size or symmetry. The chemical and amino acid compositions of the large crystal-packing interfaces resemble the protein solvent-accessible surface. These interfaces are less hydrophobic than in homodimers and contain much fewer fully buried atoms. We develop a residue propensity score and a hydrophobic interaction score to assess preferences seen in the chemical and amino acid compositions of the different types of interfaces, and we derive indexes to evaluate the atomic packing, which we find to be less compact at non-specific than at specific interfaces. We test the capacity of these parameters to identify homodimeric proteins in crystal structures, and show that a simple combination of the non-polar interface area and the fraction of buried interface atoms assigns the quaternary structure of 88% of the homodimers and 77% of the monomers in our data set correctly. These success rates increase to 93-95% when the residue propensity score of the interfaces is taken into consideration.     

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).     

Structural segments and residue propensities in protein-RNA interfaces: comparison with protein-protein and protein-DNA complexes

The interface of a protein molecule that is involved in binding another protein, DNA or RNA has been characterized in terms of the number of unique secondary structural segments (SSSs), made up of stretches of helix, strand and non-regular (NR) regions. On average 10-11 segments define the protein interface in protein-protein (PP) and protein-DNA (PD) complexes, while the number is higher (14) for protein-RNA (PR) complexes. While the length of helical segments in PP interaction increases with the interface area, this is not the case in PD and PR complexes. The propensities of residues to occur in the three types of secondary structural elements (SSEs) in the interface relative to the corresponding elements in the protein tertiary structures have been calculated. Arg, Lys, Asn, Tyr, His and Gln are preferred residues in PR complexes; in addition, Ser and Thr are also favoured in PD interfaces.     

The architecture of the binding site in redox protein complexes: implications for fast dissociation

Interprotein electron transfer is characterized by protein interactions on the millisecond time scale. Such transient encounters are ensured by extremely high rates of complex dissociation. Computational analysis of the available crystal structures of redox protein complexes reveals features of the binding site that favor fast dissociation. In particular, the complex interface is shown to have low geometric complementarity and poor packing. These features are consistent with the necessity for fast dissociation since the absence of close packing facilitates solvation of the interface and disruption of the complex.     

Extracting contact energies from protein structures: A study using a simplified model

In this study, we exploited an elementary 2-dimensional square lattice model of HP polymers to test the premise of extracting contact energies from protein structures. Given a set of prespecified energies for H–H, H–P, and P–P contacts, all possible sequences of various lengths were exhaustively enumerated to find sequences that have unique lowest-energy conformations. The lowest-energy structures (or native structures) of such (native) sequences were used to extract contact energies using the Miyazawa-Jernigan procedure and here-defined reference state. The relative magnitudes of the original energies were restored reasonably well, but the extracted contact energies were independent of the absolute magnitudes of the initial energies. We turned to a more detailed characterization of the energy landscapes of the native sequences in light of a new theoretical framework on protein folding. Foldability of such sequences imposes two limits on the absolute value of the prespecified energies: a lower bound entailed by the minimum requirement for thermodynamic stability and an upper bound associated with the entrapment of the chain to local minima. We found that these two limits confine the prespecified energy values to a rather narrow range which, surprisingly, also contains the extracted energies in all the cases examined. These results indicate that the quasi-chemical approximation can be used to connect quantitatively the occurrence of various residue–residue contacts in an ensemble of native structures with the energies of the contacts. More importantly, they suggest that the extracted contact energies do contain information on structural stability and can be used to estimate actual structural energetics. This study also encourages the use of structure-derived contact energies in threading. The finding that there is a rather narrow range of energies that are optimal for folding a sequence also cautions the use of arbitrary energy Hamiltonion in minimal folding models. Proteins 31:299–308, 1998. © 1998 Wiley-Liss, Inc.     

Weak conservation of structural features in the interfaces of homologous transient protein–protein complexes

Residue types at the interface of protein–protein complexes (PPCs) are known to be reasonably well conserved. However, we show, using a dataset of known 3‐D structures of homologous transient PPCs, that the 3‐D location of interfacial residues and their interaction patterns are only moderately and poorly conserved, respectively. Another surprising observation is that a residue at the interface that is conserved is not necessarily in the interface in the homolog. Such differences in homologous complexes are manifested by substitution of the residues that are spatially proximal to the conserved residue and structural differences at the interfaces as well as differences in spatial orientations of the interacting proteins. Conservation of interface location and the interaction pattern at the core of the interfaces is higher than at the periphery of the interface patch. Extents of variability of various structural features reported here for homologous transient PPCs are higher than the variation in homologous permanent homomers. Our findings suggest that straightforward extrapolation of interfacial nature and inter‐residue interaction patterns from template to target could lead to serious errors in the modeled complex structure. Understanding the evolution of interfaces provides insights to improve comparative modeling of PPC structures.     

Prediction of protein loop geometries in solution

The ability to determine the structure of a protein in solution is a critical tool for structural biology, as proteins in their native state are found in aqueous environments. Using a physical chemistry based prediction protocol, we demonstrate the ability to reproduce protein loop geometries in experimentally derived solution structures. Predictions were run on loops drawn from (1)NMR entries in the Protein Databank (PDB), and from (2) the RECOORD database in which NMR entries from the PDB have been standardized and re-refined in explicit solvent. The predicted structures are validated by comparison with experimental distance restraints, a test of structural quality as defined by the WHAT IF structure validation program, root mean square deviation (RMSD) of the predicted loops to the original structural models, and comparison of precision of the original and predicted ensembles. Results show that for the RECOORD ensembles, the predicted loops are consistent with an average of 95%, 91%, and 87% of experimental restraints for the short, medium and long loops respectively. Prediction accuracy is strongly affected by the quality of the original models, with increases in the percentage of experimental restraints violated of 2% for the short loops, and 9% for both the medium and long loops in the PDB derived ensembles. We anticipate the application of our protocol to theoretical modeling of protein structures, such as fold recognition methods; as well as to experimental determination of protein structures, or segments, for which only sparse NMR restraint data is available.     

All-atom contact potential approach to protein thermostability analysis

In this paper we use all-atom potential energy to define and analyze the inter-residue contacts in mesophilic and thermophilic proteins. Fifteen families of proteins are selected and each family has two representative proteins with greatly different preferred environmental temperatures. We find that both the number and energy of the contacts defined in this way show stronger correlations with the preferred temperatures of proteins than other factors used before. We also find that the charged-polar and charged-nonpolar residue contacts not only have larger contact numbers but also have lower single contact energies. Furthermore, the most important is that most of the thermophilic proteins have more charged-polar and charged-nonpolar residue contacts than their mesophilic counterparts. This suggests that they may play an important role in the thermostability of proteins, except usual charged-charged and nonpolar-nonpolar residue contacts. Charged residues may exert their profound influence by forming contacts not only with other charged residues but also with polar or nonpolar residues, thus further increasing the strength of contact network and then the thermostability of proteins.     

Taking advantage of local structure descriptors to analyze interresidue contacts in protein structures and protein complexes

Interresidue protein contacts in proteins structures and at protein-protein interface are classically described by the amino acid types of interacting residues and the local structural context of the contact, if any, is described using secondary structures. In this study, we present an alternate analysis of interresidue contact using local structures defined by the structural alphabet introduced by Camproux et al. This structural alphabet allows to describe a 3D structure as a sequence of prototype fragments called structural letters, of 27 different types. Each residue can then be assigned to a particular local structure, even in loop regions. The analysis of interresidue contacts within protein structures defined using Vorono? tessellations reveals that pairwise contact specificity is greater in terms of structural letters than amino acids. Using a simple heuristic based on specificity score comparison, we find that 74% of the long-range contacts within protein structures are better described using structural letters than amino acid types. The investigation is extended to a set of protein-protein complexes, showing that the similar global rules apply as for intraprotein contacts, with 64% of the interprotein contacts best described by local structures. We then present an evaluation of pairing functions integrating structural letters to decoy scoring and show that some complexes could benefit from the use of structural letter-based pairing functions.     

Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking

One approach to incorporate protein flexibility in molecular docking is the use of an ensemble consisting of multiple protein structures. Sequentially docking each ligand into a large number of protein structures is computationally too expensive to allow large-scale database screening. It is challenging to achieve a good balance between docking accuracy and computational efficiency. In this work, we have developed a fast, novel docking algorithm utilizing multiple protein structures, referred to as ensemble docking, to account for protein structural variations. The algorithm can simultaneously dock a ligand into an ensemble of protein structures and automatically select an optimal protein structure that best fits the ligand by optimizing both ligand coordinates and the conformational variable m, where m represents the m-th structure in the protein ensemble. The docking algorithm was validated on 10 protein ensembles containing 105 crystal structures and 87 ligands in terms of binding mode and energy score predictions. A success rate of 93% was obtained with the criterion of root-mean-square deviation <2.5 A if the top five orientations for each ligand were considered, comparable to that of sequential docking in which scores for individual docking are merged into one list by re-ranking, and significantly better than that of single rigid-receptor docking (75% on average). Similar trends were also observed in binding score predictions and enrichment tests of virtual database screening. The ensemble docking algorithm is computationally efficient, with a computational time comparable to that for docking a ligand into a single protein structure. In contrast, the computational time for the sequential docking method increases linearly with the number of protein structures in the ensemble. The algorithm was further evaluated using a more realistic ensemble in which the corresponding bound protein structures of inhibitors were excluded. The results show that ensemble docking successfully predicts the binding modes of the inhibitors, and discriminates the inhibitors from a set of noninhibitors with similar chemical properties. Although multiple experimental structures were used in the present work, our algorithm can be easily applied to multiple protein conformations generated by computational methods, and helps improve the efficiency of other existing multiple protein structure(MPS)-based methods to accommodate protein flexibility.     

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.     

S100-annexin complexes: some insights from structural studies

Several annexins have been shown to bind proteins that belong to the S100 calcium-binding protein family. The two best-characterized complexes are annexin II with p11 and annexin I with S100C, the former of which has been implicated in membrane fusion processes. We have solved the crystal structures of the complexes of p11 with annexin II N-terminus and of S100C with annexin I N-terminus. Using these structural results, as well as electron microscopy observations of liposome junctions formed in the presence of such complexes (Lambert et al., 1997 J Mol Biol 272, 42-55), we propose a computer generated model for the entire annexin II/p11 complex.     

Identifying protein complexes from heterogeneous biological data

With the increasing availability of diverse biological information for proteins, integration of heterogeneous data becomes more useful for many problems in proteomics, such as annotating protein functions, predicting novel protein–protein interactions and so on. In this paper, we present an integrative approach called InteHC (Inte grative H ierarchical C lustering) to identify protein complexes from multiple data sources. Although integrating multiple sources could effectively improve the coverage of current insufficient protein interactome (the false negative issue), it could also introduce potential false‐positive interactions that could hurt the performance of protein complex prediction. Our proposed InteHC method can effectively address these issues to facilitate accurate protein complex prediction and it is summarized into the following three steps. First, for each individual source/feature, InteHC computes the matrices to store the affinity scores between a protein pair that indicate their propensity to interact or co‐complex relationship. Second, InteHC computes a final score matrix, which is the weighted sum of affinity scores from individual sources. In particular, the weights indicating the reliability of individual sources are learned from a supervised model (i.e., a linear ranking SVM). Finally, a hierarchical clustering algorithm is performed on the final score matrix to generate clusters as predicted protein complexes. In our experiments, we compared the results collected by our hierarchical clustering on each individual feature with those predicted by InteHC on the combined matrix. We observed that integration of heterogeneous data significantly benefits the identification of protein complexes. Moreover, a comprehensive comparison demonstrates that InteHC performs much better than 14 state‐of‐the‐art approaches. All the experimental data and results can be downloaded from http://www.ntu.edu.sg/home/zhengjie/data/InteHC . Proteins 2013; 81:2023–2033. © 2013 Wiley Periodicals, Inc.     

Crystal structures of active SRC kinase domain complexes

c-Src was the first proto-oncoprotein to be identified, and has become the focus of many drug discovery programs. Src structures of a major inactive form have shown how the protein kinase is rigidified by several interdomain interactions; active configurations of Src are generated by release from this "assembled" or "bundled" form. Despite the importance of Src as a drug target, there is relatively little structural information available regarding the presumably more flexible active forms. Here we report three crystal structures of a dimeric active c-Src kinase domain, in an apo and two ligand complexed forms, with resolutions ranging from 2.9A to 1.95A. The structures show how the kinase domain, in the absence of the rigidifying interdomain interactions of the inactivation state, adopts a more open and flexible conformation. The ATP site inhibitor CGP77675 binds to the protein kinase with canonical hinge hydrogen bonds and also to the c-Src specific threonine 340. In contrast to purvalanol B binding in CDK2, purvalanol A binds in c-Src with a conformational change in a more open ATP pocket.     

Crystal structures of biotin protein ligase from Pyrococcus horikoshii OT3 and its complexes: structural basis of biotin activation

Biotin protein ligase (EC 6.3.4.15) catalyses the synthesis of an activated form of biotin, biotinyl-5'-AMP, from substrates biotin and ATP followed by biotinylation of the biotin carboxyl carrier protein subunit of acetyl-CoA carboxylase. The three-dimensional structure of biotin protein ligase from Pyrococcus horikoshii OT3 has been determined by X-ray diffraction at 1.6A resolution. The structure reveals a homodimer as the functional unit. Each subunit contains two domains, a larger N-terminal catalytic domain and a smaller C-terminal domain. The structural feature of the active site has been studied by determination of the crystal structures of complexes of the enzyme with biotin, ADP and the reaction intermediate biotinyl-5'-AMP at atomic resolution. This is the first report of the liganded structures of biotin protein ligase with nucleotide and biotinyl-5'-AMP. The structures of the unliganded and the liganded forms are isomorphous except for an ordering of the active site loop upon ligand binding. Catalytic binding sites are suitably arranged to minimize the conformational changes required during the reaction, as the pockets for biotin and nucleotide are located spatially adjacent to each other in a cleft of the catalytic domain and the pocket for biotinyl-5'-AMP binding mimics the combination of those of the substrates. The exact locations of the ligands and the active site residues allow us to propose a general scheme for the first step of the reaction carried out by biotin protein ligase in which the positively charged epsilon-amino group of Lys111 facilitates the nucleophilic attack on the ATP alpha-phosphate group by the biotin carboxyl oxygen atom and stabilizes the negatively charged intermediates.     

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.     

High-resolution structures of retinol-binding protein in complex with retinol: pH-induced protein structural changes in the crystal state

The targeted delivery of non-polar ligands by binding proteins to membranes or membrane receptors involves the release of these ligands on or near the plasma membrane of target cells. Because these hydrophobic ligands are often bound inside a deep cavity of binding proteins, as shown previously for plasma retinol-binding protein (RBP), their release from these proteins might require the destabilization of the protein structure by partially denaturing conditions, such as those possibly present near plasma membranes. RBP is a plasma transport protein which delivers specifically retinol from its store sites to target cells. Here, we report the high-resolution (1.1-1.4A) crystal structures of bovine holo-RBP at five different pH values, ranging from 9 to 2. While unraveling details of the native protein structure and of the interactions with retinol at nearly atomic resolution at neutral pH, this study provides evidence for definite pH-induced modifications of several structural features of RBP. The structure most representative of the changes that holo-RBP undergoes at different pH values is that of its flexible state at pH 2. At this pH, most significant are the alteration of the arrangement of salt bridges and of the network of water molecules/H-bonds that participates in the retinol-RBP interaction, an appreciable increase of the volume of the beta-barrel cavity, a considerably higher degree of mobility of the RBP-bound ligand and of several protein regions and the disorder of a large number of solvent molecules that are ordered at neutral pH. These changes are likely to be accompanied by a modification of the pattern of charge distribution on the protein surface. All these changes, which reveal a substantially lowered conformational stability of RBP, presumably occur at the initial stages of the acidic denaturation of RBP and are possibly associated with a facilitated release of the retinol molecule from its carrier protein.