Fire and death: the pyrin domain joins the death-domain superfamily

Apoptosis and inflammation are important cellular processes that are highly regulated through specific protein-protein interactions (PPI). Proteins involved in these signaling cascades often carry PPI domains that belong to the death-domain superfamily. This includes the structurally well-characterized Death Domain (DD), the Death Effector Domain (DED) and the Caspase Recruitment Domain (CARD) subfamilies. Recently, a fourth member of the DD superfamily was identified, the Pyrin Domain (PYD). Based on sequence alignments, homology to other domains occurring in death-signalling pathways, and secondary-structure prediction, the PYD was predicted to have an overall fold similar to other DD superfamily members. Just recently, NMR structures of two PYDs have been determined. The PYD structures not only revealed the DD superfamily fold as previously predicted, but also distinct features that are characteristic exclusively for this subfamily. This review summarizes recent findings and developments regarding structural aspects of the DD superfamily, with a special emphasis on the PPIs of the DD superfamily.     

The death-domain fold of the ASC PYRIN domain, presenting a basis for PYRIN/PYRIN recognition

The PYRIN domain is a conserved sequence motif identified in more than 20 human proteins with putative functions in apoptotic and inflammatory signalling pathways. The three-dimensional structure of the PYRIN domain from human ASC was determined by NMR spectroscopy. The structure determination reveals close structural similarity to death domains, death effector domains, and caspase activation and recruitment domains, although the structural alignment with these other members of the death-domain superfamily differs from previously predicted amino acid sequence alignments. Two highly positively and negatively charged surfaces in the PYRIN domain of ASC result in a strong electrostatic dipole moment that is predicted to be present also in related PYRIN domains. These results suggest that electrostatic interactions play an important role for the binding between PYRIN domains. Consequently, the previously reported binding between the PYRIN domains of ASC and ASC2/POP1 or between the zebrafish PYRIN domains of zAsc and Caspy is proposed to involve interactions between helices 2 and 3 of one PYRIN domain with helices 1 and 4 of the other PYRIN domain, in analogy to previously reported homophilic interactions between caspase activation and recruitment domains.     

Generalized semi-refolding methods for purification of the functional death domain superfamily

The death domain (DD) superfamily comprising the death domain (DD) subfamily, the death effector domain (DED) subfamily, the caspase recruitment domain (CARD) subfamily and the pyrin domains (PYD) subfamily is one of the largest classes of protein interaction modules and plays a pivotal role in the apoptosis, inflammation, and immune cell signaling pathways. Despite the biological importance of the death domain superfamily, structural and in vitro biochemical studies have been limited because these domains are prone to aggregate under physiological conditions. Here, we describe a generalized method, termed semi-refolding, that is particularly applicable for purification of the functional death domain superfamily. The recombinant proteins Caspase-1 CARD, AIM2 PYD, NALP3 PYD, and RIP1 DD from inclusion bodies were successfully purified using this method.     

Threading a database of protein cores

We present an analysis of 10 blind predictions prepared for a recent conference, “Critical Assessment of Techniques for Protein Structure Prediction.”¹ The sequences of these proteins are not detectably similar to those of any protein in the structure database then available, but we attempted, by a threading method, to recognize similarity to known domain folds. Four of the 10 proteins, as we subsequently learned, do indeed show significant similarity to then-known structures. For 2 of these proteins the predictions were accurate, in the sense that a similar structure was at or near the top of the list of threading scores, and the threading alignment agreed well with the corresponding structural alignment. For the best predicted model mean alignment error relative to the optimal structural alignment was 2.7 residues, arising entirely from small “register shifts” of strands or helices. In the analysis we attempt to identify factors responsible for these successes and failures. Since our threading method does not use gap penalties, we may readily distinguish between errors arising from our prior definition of the “cores” of known structures and errors arising from inherent limitations in the threading potential. It would appear from the results that successful substructure recognition depends most critically on accurate definition of the “fold” of a database protein. This definition must correctly delineate substructures that are, and are not, likely to be conserved during protein evolution. © 1995 Wiley-Liss, Inc.     

A proposed architecture for the central domain of the bacterial enhancer-binding proteins based on secondary structure prediction and fold recognition

The expression of genes transcribed by the RNA polymerase with the alternative sigma factor <r54 (Ecr54) is absolutely dependent on activator proteins that bind to enhancer-like sites, located far upstream from the promoter. These unique prokaryotic proteins, known as enhancer-binding proteins (EBP), mediate open promoter complex formation in a reaction dependent on NTP hydrolysis. The best characterized proteins of this family of regulators are NtrC and Nif A, which activate genes required for ammonia assimilation and nitrogen fixation, respectively. In a recent IRBM course (“Frontiers of protein structure prediction,” IRBM, Pomezia, Italy, 1995; see web site http://www.mrc-cpe.cam.uk/ irbm-course95/), one of us (J.O.) participated in the elaboration of the proposal that the Central domain of the EBPs might adopt the classical mononucleotide-binding fold. This suggestion was based on the results of a new protein fold recognition algorithm (Map) and in the mapping of correlated mutations calculated for the sequence family on the same mononucleotide-binding fold topology. In this work, we present new data that support the previous conclusion. The results from a number of different secondary structure prediction programs suggest that the Central domain could adopt an alfi topology. The fold recognition programs ProFIT 0.9, 3D PROFILE combined with secondary structure prediction, and 123D suggest a mononucleotide-binding fold topology for the Central domain amino acid sequence. Finally, and most importantly, three of five reported residue alterations that impair the Central domain ATPase activity of the Eo-54 activators are mapped to polypeptide regions that might be playing equivalent roles as those involved in nucleotide-binding in the mononucleotide-binding proteins. Furthermore, the known residue substitutions that alter the function of the Ecr54 activators, leaving intact the Central domain ATPase activity, are mapped on a region proposed to play an equivalent role as the effector region of the GTPase superfamily.     

The NLRP12 pyrin domain: structure, dynamics, and functional insights

The initial line of defense against infection is sustained by the innate immune system. Together, membrane-bound Toll-like receptors and cytosolic nucleotide-binding domain and leucine-rich repeat-containing receptors (NLR) play key roles in the innate immune response by detecting bacterial and viral invaders as well as endogenous stress signals. NLRs are multi-domain proteins with varying N-terminal effector domains that are responsible for regulating downstream signaling events. Here, we report the structure and dynamics of the N-terminal pyrin domain of NLRP12 (NLRP12 PYD) determined using NMR spectroscopy. NLRP12 is a non-inflammasome NLR that has been implicated in the regulation of Toll-like receptor-dependent nuclear factor-κB activation. NLRP12 PYD adopts a typical six-helical bundle death domain fold. By direct comparison with other PYD structures, we identified hydrophobic residues that are essential for the stable fold of the NLRP PYD family. In addition, we report the first in vitro confirmed non-homotypic PYD interaction between NLRP12 PYD and the pro-apoptotic protein Fas-associated factor 1 (FAF-1), which links the innate immune system to apoptotic signaling. Interestingly, all residues that participate in this protein:protein interaction are confined to the α2-α3 surface, a region of NLRP12 PYD that differs most between currently reported NLRP PYD structures. Finally, we experimentally highlight a significant role for tryptophan 45 in the interaction between NLRP12 PYD and the FAF-1 UBA domain.     

Protein structure prediction by threading methods: Evaluation of current techniques

This paper evaluates the results of a protein structure prediction contest. The predictions were made using threading procedures, which employ techniques for aligning sequences with 3D structures to select the correct fold of a given sequence from a set of alternatives. Nine different teams submitted 86 predictions, on a total of 21 target proteins with little or no sequence homology to proteins of known structure. The 3D structures of these proteins were newly determined by experimental methods, but not yet published or otherwise available to the predictors. The predictions, made from the amino acid sequence alone, thus represent a genuine test of the current performance of threading methods. Only a subset of all the predictions is evaluated here. It corresponds to the 44 predictions submitted for the 11 target proteins seen to adopt known folds. The predictions for the remaining 10 proteins were not analyzed, although weak similarities with known folds may also exist in these proteins. We find that threading methods are capable of identifying the correct fold in many cases, but not reliably enough as yet. Every team predicts correctly a different set of targets, with virtually all targets predicted correctly by at least one team. Also, common folds such as TIM barrels are recognized more readily than folds with only a few known examples. However, quite surprisingly, the quality of the sequence-structure alignments, corresponding to correctly recognized folds, is generally very poor, as judged by comparison with the corresponding 3D structure alignments. Thus, threading can presently not be relied upon to derive a detailed 3D model from the amino acid sequence. This raises a very intriguing question: how is fold recognition achieved? Our analysis suggests that it may be achieved because threading procedures maximize hydrophobic interactions in the protein core, and are reasonably good at recognizing local secondary structure. © 1995 Wiley-Liss, Inc.     

Prediction of the conformation and geometry of loops in globular proteins: testing ArchDB, a structural classification of loops

In protein structure prediction, a central problem is defining the structure of a loop connecting 2 secondary structures. This problem frequently occurs in homology modeling, fold recognition, and in several strategies in ab initio structure prediction. In our previous work, we developed a classification database of structural motifs, ArchDB. The database contains 12,665 clustered loops in 451 structural classes with information about phi-psi angles in the loops and 1492 structural subclasses with the relative locations of the bracing secondary structures. Here we evaluate the extent to which sequence information in the loop database can be used to predict loop structure. Two sequence profiles were used, a HMM profile and a PSSM derived from PSI-BLAST. A jack-knife test was made removing homologous loops using SCOP superfamily definition and predicting afterwards against recalculated profiles that only take into account the sequence information. Two scenarios were considered: (1) prediction of structural class with application in comparative modeling and (2) prediction of structural subclass with application in fold recognition and ab initio. For the first scenario, structural class prediction was made directly over loops with X-ray secondary structure assignment, and if we consider the top 20 classes out of 451 possible classes, the best accuracy of prediction is 78.5%. In the second scenario, structural subclass prediction was made over loops using PSI-PRED (Jones, J Mol Biol 1999;292:195-202) secondary structure prediction to define loop boundaries, and if we take into account the top 20 subclasses out of 1492, the best accuracy is 46.7%. Accuracy of loop prediction was also evaluated by means of RMSD calculations.     

Retrospective analysis of a secondary structure prediction: the catalytic domain of matrix metalloproteinases.

Secondary structure prediction of the catalytic domain of matrix metalloproteinases is evaluated in the light of recently published experimentally determined structures. The prediction was made by combining conformational propensity, surface probability, and residue conservation calculated for an alignment of 19 sequences. The position of each observed secondary structure element was correctly predicted with a high degree of accuracy, with a single beta-strand falsely predicted. The domain fold was also anticipated from the prediction by analogy with the structural elements found in the distantly related metalloproteinases thermolysin, astacin, and adamalysin.     

Structural transformation-mediated dimerization of caspase recruitment domain revealed by the crystal structure of CARD-only protein in frog virus 3

Caspase recruitment domain (CARD)-only proteins (COPs), regulate apoptosis, inflammation, and innate immunity. They inhibit the assembly of NOD-like receptor complexes such as the inflammasome and NODosome, which are molecular complexes critical for caspase-1 activation. COPs are known to interact with either caspase-1 CARD or RIP2 CARD via a CARD-CARD interaction, and inhibit caspase-1 activation or further downstream signaling. In addition to the human COPs, Pseudo-ICE, INCA, and ICEBERG, several viruses also contain viral COPs that help them escape the host immune system. To elucidate the molecular mechanism of host immunity inhibition by viral COPs, we solved the structure of a viral COP for the first time. Our structure showed that viral COP forms a structural transformation-mediated dimer, which is unique and has not been reported in any structural study of a CARD domain. Based on the current structure, and the previously solved structures of other death domain superfamily members, we propose that structural transformation-mediated dimerization might be a new strategy for dimer assembly in the death domain superfamily.     

Evolutionary analysis reveals collective properties and specificity in the C-type lectin and lectin-like domain superfamily

Members of the C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily share a common fold and are involved in a variety of functions, such as generalized defense mechanisms against foreign agents, discrimination between healthy and pathogen-infected cells, and endocytosis and blood coagulation. In this work we used ConSurf, a computer program recently developed in our lab, to perform an evolutionary analysis of this superfamily in order to further identify characteristics of all or part of its members. Given a set of homologous proteins in the form of multiple sequence alignment (MSA) and an inferred phylogenetic tree, ConSurf calculates the conservation score in every alignment position, taking into account the relationships between the sequences and the physicochemical similarity between the amino acids. The scores are then color-coded onto the three-dimensional structure of one of the homologous proteins. We provide here and at http://ashtoret.tau.ac.il/ approximately sharon a detailed analysis of the conservation pattern obtained for the entire superfamily and for two subgroups of proteins: (a) 21 CTLs and (b) 11 heterodimeric CTLD toxins. We show that, in general, proteins of the superfamily have one face that is constructed mostly of conserved residues and another that is not, and we suggest that the former face is involved in binding to other proteins or domains. In the CTLs examined we detected a region of highly conserved residues, corresponding to the known calcium- and carbohydrate-binding site of the family, which is not conserved throughout the entire superfamily, and in the CTLD toxins we found a patch of highly conserved residues, corresponding to the known dimerization region of these proteins. Our analysis also detected patches of conserved residues with yet unknown function(s).     

Improving fold recognition without folds

The most reliable way to align two proteins of unknown structure is through sequence-profile and profile-profile alignment methods. If the structure for one of the two is known, fold recognition methods outperform purely sequence-based alignments. Here, we introduced a novel method that aligns generalised sequence and predicted structure profiles. Using predicted 1D structure (secondary structure and solvent accessibility) significantly improved over sequence-only methods, both in terms of correctly recognising pairs of proteins with different sequences and similar structures and in terms of correctly aligning the pairs. The scores obtained by our generalised scoring matrix followed an extreme value distribution; this yielded accurate estimates of the statistical significance of our alignments. We found that mistakes in 1D structure predictions correlated between proteins from different sequence-structure families. The impact of this surprising result was that our method succeeded in significantly out-performing sequence-only methods even without explicitly using structural information from any of the two. Since AGAPE also outperformed established methods that rely on 3D information, we made it available through. If we solved the problem of CPU-time required to apply AGAPE on millions of proteins, our results could also impact everyday database searches.     

The WWWH of remote homolog detection: the state of the art

The detection of remote homolog pairs of proteins using computational methods is a pivotal problem in structural bioinformatics, aiming to compute protein folds on the basis of information in the database of known structures. In the last 25 years, several methods have been developed to tackle this problem, based on different approaches including sequence-sequence alignments and/or structure comparison. In this article, we will briefly discuss When, Why, Where and How (WWWH) to perform remote homology search, reviewing some of the most widely adopted computational approaches. The specific aim is highlighting the basic criteria implemented by different research groups and commenting on the status of the art as well as on still-open questions.     

Evidence for a novel domain of bacterial outer membrane ushers

Many pathogenic bacteria possess adhesive surface organelles (called pili), anchored to their outer membrane, which mediate the first step of infection by binding to host tissue. Pilus biogenesis occurs via the "chaperone-usher" pathway: the usher, a large outer membrane protein, binds complexes of a periplasmic chaperone with pilus subunits, unloads the subunits from the chaperone, and assembles them into the pilus, which is extruded into the extracellular space. Ushers comprise an N-terminal periplasmic domain, a large transmembrane beta-barrel central domain, and a C-terminal periplasmic domain. Since structural data are available only for the N-terminal domain, we performed an in-depth bioinformatic analysis of bacterial ushers. Our analysis led us to the conclusion that the transmembrane beta-barrel region of ushers contains a so far unrecognized soluble domain, the "middle domain", which possesses a beta-sandwich fold. Two other bacterial beta-sandwich domains, the TT0351 protein from Thermus thermophilus and the carbohydrate binding module CBM36 from Paenibacillus polymyxa, are possible distant relatives of the usher "middle domain". Several mutations reported to abolish in vivo pilus formation cluster in this region, underlining its functional importance.     

Protein models: The Grand Challenge of protein docking

Characterization of life processes at the molecular level requires structural details of protein–protein interactions (PPIs). The number of experimentally determined protein structures accounts only for a fraction of known proteins. This gap has to be bridged by modeling, typically using experimentally determined structures as templates to model related proteins. The fraction of experimentally determined PPI structures is even smaller than that for the individual proteins, due to a larger number of interactions than the number of individual proteins, and a greater difficulty of crystallizing protein–protein complexes. The approaches to structural modeling of PPI (docking) often have to rely on modeled structures of the interactors, especially in the case of large PPI networks. Structures of modeled proteins are typically less accurate than the ones determined by X‐ray crystallography or nuclear magnetic resonance. Thus the utility of approaches to dock these structures should be assessed by thorough benchmarking, specifically designed for protein models. To be credible, such benchmarking has to be based on carefully curated sets of structures with levels of distortion typical for modeled proteins. This article presents such a suite of models built for the benchmark set of the X‐ray structures from the Dockground resource ( http://dockground.bioinformatics.ku.edu ) by a combination of homology modeling and Nudged Elastic Band method. For each monomer, six models were generated with predefined C^α root mean square deviation from the native structure (1, 2, …, 6 Å). The sets and the accompanying data provide a comprehensive resource for the development of docking methodology for modeled proteins. Proteins 2014; 82:278–287. © 2013 Wiley Periodicals, Inc.     

Prediction of VH–VL domain orientation for antibody variable domain modeling

The antigen‐binding site of antibodies forms at the interface of their two variable domains, VH and VL, making VH–VL domain orientation a factor that codetermines antibody specificity and affinity. Preserving VH–VL domain orientation in the process of antibody engineering is important in order to retain the original antibody properties, and predicting the correct VH–VL orientation has also been recognized as an important factor in antibody homology modeling. In this article, we present a fast sequence‐based predictor that predicts VH–VL domain orientation with Q² values ranging from 0.54 to 0.73 on the evaluation set. We describe VH–VL orientation in terms of the six absolute ABangle parameters that have recently been proposed as a means to separate the different degrees of freedom of VH–VL domain orientation. In order to assess the impact of adjusting VH–VL orientation according to our predictions, we use the set of antibody structures of the recently published Antibody Modeling Assessment (AMA) II study. In comparison to the original AMAII homology models, we find an improvement in the accuracy of VH–VL orientation modeling, which also translates into an improvement in the average root‐mean‐square deviation with regard to the crystal structures. Proteins 2015; 83:681–695. © 2015 Wiley Periodicals, Inc.