Interfacial residues in protein-protein complexes are in the eyes of the beholder.

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

Identification, functional characterization, assembly and structure of ToxIN type III toxin-antitoxin complex from E. coli.

Toxin-antitoxin (TA) systems are proposed to play crucial roles in bacterial growth under stress conditions such as phage infection. The type III TA systems consist of a protein toxin whose activity is inhibited by a noncoding RNA antitoxin. The toxin is an endoribonuclease, while the antitoxin consists of multiple repeats of RNA. The toxin assembles with the individual antitoxin repeats into a cyclic complex in which the antitoxin forms a pseudoknot structure. While structure and functions of some type III TA systems are characterized, the complex assembly process is not well understood. Using bioinformatics analysis, we have identified type III TA systems belonging to the ToxIN family across different Escherichia coli strains and found them to be clustered into at least five distinct clusters. Furthermore, we report a 2.097 Å resolution crystal structure of the first E. coli ToxIN complex that revealed the overall assembly of the protein-RNA complex. Isothermal titration calorimetry experiments showed that toxin forms a high-affinity complex with antitoxin RNA resulting from two independent (5' and 3' sides of RNA) RNA binding sites on the protein. These results further our understanding of the assembly of type III TA complexes in bacteria.

Comparative analysis of permanent and transient domain-domain interactions in multi-domain proteins.

Protein domains are structural, functional, and evolutionary units. These domains bring out the diversity of functionality by means of interactions with other co-existing domains and provide stability. Hence, it is important to study intra-protein inter-domain interactions from the perspective of types of interactions. Domains within a chain could interact over short timeframes or permanently, rather like protein-protein interactions (PPIs). However, no systematic study has been carried out between two classes, namely permanent and transient domain-domain interactions. In this work, we studied 263 two-domain proteins, belonging to either of these classes and their interfaces on the basis of several factors, such as interface area and details of interactions (number, strength, and types of interactions). We also characterized them based on residue conservation at the interface, correlation of residue motions across domains, its involvement in repeat formation, and their involvement in particular molecular processes. Finally, we could analyze the interactions arising from domains in two-domain monomeric proteins, and we observed significant differences between these two classes of domain interactions and a few similarities. This study will help to obtain a better understanding of structure-function and folding principles of multi-domain proteins.

Comparison of structural networks across homologous proteins.

Protein sequence determines its structure and function. The indirect relationship between protein function and structure lies deep-rooted in the structural topology that has evolved into performing optimal function. The evolution of structure and its interconnectivity has been conventionally studied by comparing the root means square deviation between protein structures at the backbone level. Two factors that are necessary for the quantitative comparison of non-covalent interactions are (a) explicit inclusion of the coordinates of side-chain atoms and (b) consideration of multiple structures from the conformational landscape to account for structural variability. We have recently addressed these fundamental issues by investigating the alteration of inter-residue interactions across an ensemble of protein structure networks through a graph spectral approach. In this study, we have developed a rigorous method to compare the structure networks of homologous proteins, with a wide range of sequence identity percentages. A range of dissimilarity measures that show the extent of change in the network across homologous structures are generated, which also includes the comparison of the protein structure variability. We discuss in detail, scenarios where the variation of structure is not accompanied by loss or gain of the overall network and its vice versa. The sequence-based phylogeny among the homologs is also compared with the lineage obtained from information from such a robust structure comparison. In summary, we can obtain a quantitative comparison score for the structure networks of homologous proteins, which also enables us to study the evolution of protein function based on the variation of their topologies.

The alteration of structural network upon transient association between proteins studied using graph theory.

Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.

Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles.

The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.

'All That Glitters Is Not Gold': High-Resolution Crystal Structures of Ligand-Protein Complexes Need Not Always Represent Confident Binding Poses.

Our understanding of the structure-function relationships of biomolecules and thereby applying it to drug discovery programs are substantially dependent on the availability of the structural information of ligand-protein complexes. However, the correct interpretation of the electron density of a small molecule bound to a crystal structure of a macromolecule is not trivial. Our analysis involving quality assessment of ~0.28 million small molecule-protein binding site pairs derived from crystal structures corresponding to ~66,000 PDB entries indicates that the majority (65%) of the pairs might need little (54%) or no (11%) attention. Out of the remaining 35% of pairs that need attention, 11% of the pairs (including structures with high/moderate resolution) pose serious concerns. Unfortunately, most users of crystal structures lack the training to evaluate the quality of a crystal structure against its experimental data and, in general, rely on the resolution as a 'gold standard' quality metric. Our work aims to sensitize the non-crystallographers that resolution, which is a global quality metric, need not be an accurate indicator of local structural quality. In this article, we demonstrate the use of several freely available tools that quantify local structural quality and are easy to use from a non-crystallographer's perspective. We further propose a few solutions for consideration by the scientific community to promote quality research in structural biology and applied areas.

A structural entropy index to analyse local conformations in intrinsically disordered proteins.

Sequence - structure - function paradigm has been revolutionized by the discovery of disordered regions and disordered proteins more than two decades ago. While the definition of rigidity is simple with X-ray structures, the notion of flexibility is linked to high experimental B-factors. The definition of disordered regions is more complex as in these same X-ray structures; it is associated to the position of missing residues. Thus a continuum so seems to exist between rigidity, flexibility and disorder. However, it had not been precisely described. In this study, we used an ensemble of disordered proteins (or regions) and, we applied a structural alphabet to analyse their local conformation. This structural alphabet, namely Protein Blocks, had been efficiently used to highlight rigid local domains within flexible regions and so discriminates deformability and mobility concepts. Using an entropy index derived from this structural alphabet, we underlined its interest to measure these local dynamics, and to quantify, for the first time, continuum states from rigidity to flexibility and finally disorder. We also highlight non-disordered regions in the ensemble of disordered proteins in our study.

Bioinformatic and mutational studies of related toxin-antitoxin pairs in Mycobacterium tuberculosis predict and identify key functional residues.

Mycobacterium tuberculosis possesses an unusually large representation of type II toxin-antitoxin (TA) systems, whose functions and targets are mostly unknown. To better understand the basis of their unique expansion and to probe putative functional similarities among these systems, here we computationally and experimentally investigated their sequence relationships. Bioinformatic and phylogenetic investigations revealed that 51 sequences of the VapBC toxin family group into paralogous sub-clusters. On the basis of conserved sequence fingerprints within paralogues, we predicted functional residues and residues at the putative TA interface that are useful to evaluate TA interactions. Substitution of these likely functional residues abolished the toxin's growth-inhibitory activity. Furthermore, conducting similarity searches in 101 mycobacterial and ∼4500 other prokaryotic genomes, we assessed the relative conservation of the M. tuberculosis TA systems and found that most TA orthologues are well-conserved among the members of the M. tuberculosis complex, which cause tuberculosis in animal hosts. We found that soil-inhabiting, free-living Actinobacteria also harbor as many as 12 TA pairs. Finally, we identified five novel putative TA modules in M. tuberculosis. For one of them, we demonstrate that overexpression of the putative toxin, Rv2514c, induces bacteriostasis and that co-expression of the cognate antitoxin Rv2515c restores bacterial growth. Taken together, our findings reveal that toxin sequences are more closely related than antitoxin sequences in M. tuberculosis Furthermore, the identification of additional TA systems reported here expands the known repertoire of TA systems in M. tuberculosis.

Genome-wide and structural analyses of pseudokinases encoded in the genome of Arabidopsis thaliana provide functional insights.

Protein Kinase-Like Non-Kinases (PKLNKs), commonly known as "pseudokinases", are homologous to eukaryotic Ser/Thr/Tyr protein kinases (PKs) but lack the crucial aspartate residue in the catalytic loop, indispensable for phosphotransferase activity. Therefore, they are predicted to be "catalytically inactive" enzyme homologs. Analysis of protein-kinase like sequences from Arabidopsis thaliana led to the identification of more than 120 pseudokinases lacking catalytic aspartate, majority of which are closely related to the plant-specific receptor-like kinase family. These pseudokinases engage in different biological processes, enabled by their diverse domain architectures and specific subcellular localizations. Structural comparison of pseudokinases with active and inactive conformations of canonical PKs, belonging to both plant and animal origin, revealed unique structural differences. The currently available crystal structures of pseudokinases show that the loop topologically equivalent to activation segment of PKs adopts a distinct-folded conformation, packing against the pseudoenzyme core, in contrast to the extended and inhibitory geometries observed for active and inactive states, respectively, of catalytic PKs. Salt-bridge between ATP-binding Lys and DFG-Asp as well as hydrophobic interactions between the conserved nonpolar residue C-terminal to the equivalent DFG motif and nonpolar residues in C-helix mediate such a conformation in pseudokinases. This results in enhanced solvent accessibility of the pseudocatalytic loop in pseudokinases that can possibly serve as an interacting surface while associating with other proteins. Specifically, our analysis identified several residues that may be involved in pseudokinase regulation and hints at the repurposing of pseudocatalytic residues to achieve mechanistic control over noncatalytic functions of pseudoenzymes.

How good are comparative models in the understanding of protein dynamics?

The 3D structure of a protein is essential to understand protein dynamics. If experimentally determined structure is unavailable, comparative models could be used to infer dynamics. However, the effectiveness of comparative models, compared to experimental structures, in inferring dynamics is not clear. To address this, we compared dynamics features of ~800 comparative models with their crystal structures using normal mode analysis. Average similarity in magnitude, direction, and correlation of residue motions is >0.8 (where value 1 is identical) indicating that the dynamics of models and crystal structures are highly similar. Accuracy of 3D structure and dynamics is significantly higher for models built on multiple and/or high sequence identity templates (>40%). Three-dimensional (3D) structure and residue fluctuations of models are closer to that of crystal structures than to templates (TM score 0.9 vs 0.7 and square inner product 0.92 vs 0.88). Furthermore, long-range molecular dynamics simulations on comparative models of RNase 1 and Angiogenin showed significant differences in the conformational sampling of conserved active-site residues that characterize differences in their activity levels. Similar analyses on two EGFR kinase variant models highlight the effect of mutations on the functional state-specific αC helix motions and these results corroborate with the previous experimental observations. Thus, our study adds confidence to the use of comparative models in understanding protein dynamics.

Artificial protein sequences enable recognition of vicinal and distant protein functional relationships.

High divergence in protein sequences makes the detection of distant protein relationships through homology-based approaches challenging. Grouping protein sequences into families, through similarities in either sequence or 3-D structure, facilitates in the improved recognition of protein relationships. In addition, strategically designed protein-like sequences have been shown to bridge distant structural domain families by serving as artificial linkers. In this study, we have augmented a search database of known protein domain families with such designed sequences, with the intention of providing functional clues to domain families of unknown structure. When assessed using representative query sequences from each family, we obtain a success rate of 94% in protein domain families of known structure. Further, we demonstrate that the augmented search space enabled fold recognition for 582 families with no structural information available a priori. Additionally, we were able to provide reliable functional relationships for 610 orphan families. We discuss the application of our method in predicting functional roles through select examples for DUF4922, DUF5131, and DUF5085. Our approach also detects new associations between families that were previously not known to be related, as demonstrated through new sub-groups of the RNA polymerase domain among three distinct RNA viruses. Taken together, designed sequences-augmented search databases direct the detection of meaningful relationships between distant protein families. In turn, they enable fold recognition and offer reliable pointers to potential functional sites that may be probed further through direct mutagenesis studies.

NU-6027 Inhibits Growth of Mycobacterium tuberculosis by Targeting Protein Kinase D and Protein Kinase G.

Tuberculosis (TB) is a global health concern, and this situation has further worsened due to the emergence of drug-resistant strains and the failure of BCG vaccine to impart protection. There is an imperative need to develop highly sensitive, specific diagnostic tools, novel therapeutics, and vaccines for the eradication of TB. In the present study, a chemical screen of a pharmacologically active compound library was performed to identify antimycobacterial compounds. The phenotypic screen identified a few novel small-molecule inhibitors, including NU-6027, a known CDK-2 inhibitor. We demonstrate that NU-6027 inhibits Mycobacterium bovis BCG growth in vitro and also displayed cross-reactivity with Mycobacterium tuberculosis protein kinase D (PknD) and protein kinase G (PknG). Comparative structural and sequence analysis along with docking simulation suggest that the unique binding site stereochemistry of PknG and PknD accommodates NU-6027 more favorably than other M. tuberculosis Ser/Thr protein kinases. Further, we also show that NU-6027 treatment induces the expression of proapoptotic genes in macrophages. Finally, we demonstrate that NU-6027 inhibits M. tuberculosis growth in both macrophage and mouse tissues. Taken together, these results indicate that NU-6027 can be optimized further for the development of antimycobacterial agents.

Recognition of sites of functional specialisation in all known eukaryotic protein kinase families.

The conserved function of protein phosphorylation, catalysed by members of protein kinase superfamily, is regulated in different ways in different kinase families. Further, differences in activating triggers, cellular localisation, domain architecture and substrate specificity between kinase families are also well known. While the transfer of γ-phosphate from ATP to the hydroxyl group of Ser/Thr/Tyr is mediated by a conserved Asp, the characteristic functional and regulatory sites are specialized at the level of families or sub-families. Such family-specific sites of functional specialization are unknown for most families of kinases. In this work, we systematically identify the family-specific residue features by comparing the extent of conservation of physicochemical properties, Shannon entropy and statistical probability of residue distributions between families of kinases. An integrated discriminatory score, which combines these three features, is developed to demarcate the functionally specialized sites in a kinase family from other sites. We achieved an area under ROC curve of 0.992 for the discrimination of kinase families. Our approach was extensively tested on well-studied families CDK and MAPK, wherein specific protein interaction sites and substrate recognition sites were successfully detected (p-value < 0.05). We also find that the known family-specific oncogenic driver mutation sites were scored high by our method. The method was applied to all known kinases encompassing 107 families from diverse eukaryotic organisms leading to a comprehensive list of family-specific functional sites. Apart from other uses, our method facilitates identification of specific protein interaction sites and drug target sites in a kinase family.

Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains.

The majority of the proteins encoded in the genomes of eukaryotes contain more than one domain. Reasons for high prevalence of multi-domain proteins in various organisms have been attributed to higher stability and functional and folding advantages over single-domain proteins. Despite these advantages, many proteins are composed of only one domain while their homologous domains are part of multi-domain proteins. In the study presented here, differences in the properties of protein domains in single-domain and multi-domain systems and their influence on functions are discussed. We studied 20 pairs of identical protein domains, which were crystallized in two forms (a) tethered to other proteins domains and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain. Results suggest that tethering of domains in multi-domain proteins influences the structural, dynamic and energetic properties of the constituent protein domains. 50% of the protein domain pairs show significant structural deviations while 90% of the protein domain pairs show differences in dynamics and 12% of the residues show differences in the energetics. To gain further insights on the influence of tethering on the function of the domains, 4 pairs of homologous protein domains, where one of them is a full-length single-domain protein and the other protein domain is a part of a multi-domain protein, were studied. Analyses showed that identical and structurally equivalent functional residues show differential dynamics in homologous protein domains; though comparable dynamics between in-silico generated chimera protein and multi-domain proteins were observed. From these observations, the differences observed in the functions of homologous proteins could be attributed to the presence of tethered domain. Overall, we conclude that tethered domains in multi-domain proteins not only provide stability or folding advantages but also influence pathways resulting in differences in function or regulatory properties.

Clustering of multi-domain protein sequences.

The overall function of a multi-domain protein is determined by the functional and structural interplay of its constituent domains. Traditional sequence alignment-based methods commonly utilize domain-level information and provide classification only at the level of domains. Such methods are not capable of taking into account the contributions of other domains in the proteins, and domain-linker regions and classify multi-domain proteins. An alignment-free protein sequence comparison tool, CLAP (CLAssification of Proteins) was previously developed in our laboratory to especially handle multi-domain protein sequences without a requirement of defining domain boundaries and sequential order of domains. Through this method we aim to achieve a biologically meaningful classification scheme for multi-domain protein sequences. In this article, CLAP-based classification has been explored on 5 datasets of multi-domain proteins and we present detailed analysis for proteins containing (1) Tyrosine phosphatase and (2) SH3 domain. At the domain-level CLAP-based classification scheme resulted in a clustering similar to that obtained from an alignment-based method. CLAP-based clusters obtained for full-length datasets were shown to comprise of proteins with similar functions and domain architectures. Our study demonstrates that multi-domain proteins could be classified effectively by considering full-length sequences without a requirement of identification of domains in the sequence.

Design, Synthesis, and Experimental Validation of Peptide Ligands Targeting Mycobacterium tuberculosis σ Factors.

Transcription in prokaryotes is a multistep process and is primarily regulated at the initiation stage. σ factors are involved in promoter recognition and thus govern prokaryotic gene expression. Mycobacterium tuberculosis (Mtb) σ factors have been previously suggested as important drug targets through large-scale genome analyses. Here we demonstrate the feasibility of specific targeting of Mtb σ factors using designed peptides. A peptide library was generated using three-dimensional structural features corresponding to the interface regions of σ factors and the RNA polymerase. In silico optimization of the peptides, employing structural as well as sequence features, aided specific targeting of σA and σB. We synthesized and characterized the best hit peptide from the peptide library along with other control peptides and studied the interaction of these peptides with σB using biolayer interferometry. The experimental data validate the design strategy. These studies suggest the feasibility of designing specific peptides via in silico methods that bind σB with nanomolar affinity. We note that this strategy can be broadly applied to modulate prokaryotic transcription by designed peptides, thereby providing a tool for studying bacterial adaptation as well as host-pathogen interactions in infectious bacteria.

Structure determination of contaminant proteins using the MarathonMR procedure.

In the recent decades, essential steps of protein structure determination such as phasing by multiple isomorphous replacement and multi wave length anomalous dispersion, molecular replacement, refinement of the structure determined and its validation have been fully automated. Several computer program suites that execute all these steps as a pipeline operation have been made available. In spite of these great advances, determination of a protein structure may turn out to be a challenging task for a variety of reasons. It might be difficult to obtain multiple isomorphous replacement or multi wave length anomalous dispersion data or the crystal may have defects such as twinning or pseudo translation. Apart from these usual difficulties, more frequent difficulties have been encountered in recent years because of the large number of projects handled by structural biologists. These new difficulties usually result from contamination of the protein of interest by other proteins or presence of proteins from pathogenic organisms that could withstand the antibiotics used to prevent bacterial contamination. It could also be a result of poor book keeping. Recently, we have developed a procedure called MarathonMR that has the power to resolve some of these problems automatically. In this communication, we describe how the MarathonMR was used to determine four different protein structures that had remained elusive for several years. We describe the plausible reasons for the difficulties encountered in determining these structures and point out that the method presented here could be a validation tool for protein structures deposited in the protein data bank.

Deciphering common recognition principles of nucleoside mono/di and tri-phosphates binding in diverse proteins via structural matching of their binding sites.

Nucleoside triphosphate (NTP) ligands are of high biological importance and are essential for all life forms. A pre-requisite for them to participate in diverse biochemical processes is their recognition by diverse proteins. It is thus of great interest to understand the basis for such recognition in different proteins. Towards this, we have used a structural bioinformatics approach and analyze structures of 4677 NTP complexes available in Protein Data Bank (PDB). Binding sites were extracted and compared exhaustively using PocketMatch, a sensitive in-house site comparison algorithm, which resulted in grouping the entire dataset into 27 site-types. Each of these site-types represent a structural motif comprised of two or more residue conservations, derived using another in-house tool for superposing binding sites, PocketAlign. The 27 site-types could be grouped further into 9 super-types by considering partial similarities in the sites, which indicated that the individual site-types comprise different combinations of one or more site features. A scan across PDB using the 27 structural motifs determined the motifs to be specific to NTP binding sites, and a computational alanine mutagenesis indicated that residues identified to be highly conserved in the motifs are also most contributing to binding. Alternate orientations of the ligand in several site-types were observed and rationalized, indicating the possibility of some residues serving as anchors for NTP recognition. The presence of multiple site-types and the grouping of multiple folds into each site-type is strongly suggestive of convergent evolution. Knowledge of determinants obtained from this study will be useful for detecting function in unknown proteins. Proteins 2017; 85:1699-1712. © 2017 Wiley Periodicals, Inc.

Resolving protein structure-function-binding site relationships from a binding site similarity network perspective.

Functional annotation is seldom straightforward with complexities arising due to functional divergence in protein families or functional convergence between non-homologous protein families, leading to mis-annotations. An enzyme may contain multiple domains and not all domains may be involved in a given function, adding to the complexity in function annotation. To address this, we use binding site information from bound cognate ligands and catalytic residues, since it can help in resolving fold-function relationships at a finer level and with higher confidence. A comprehensive database of 2,020 fold-function-binding site relationships has been systematically generated. A network-based approach is employed to capture the complexity in these relationships, from which different types of associations are deciphered, that identify versatile protein folds performing diverse functions, same function associated with multiple folds and one-to-one relationships. Binding site similarity networks integrated with fold, function, and ligand similarity information are generated to understand the depth of these relationships. Apart from the observed continuity in the functional site space, network properties of these revealed versatile families with topologically different or dissimilar binding sites and structural families that perform very similar functions. As a case study, subtle changes in the active site of a set of evolutionarily related superfamilies are studied using these networks. Tracing of such similarities in evolutionarily related proteins provide clues into the transition and evolution of protein functions. Insights from this study will be helpful in accurate and reliable functional annotations of uncharacterized proteins, poly-pharmacology, and designing enzymes with new functional capabilities. Proteins 2017; 85:1319-1335. © 2017 Wiley Periodicals, Inc.