Does NMR mean "not for molecular replacement"? Using NMR-based search models to solve protein crystal structures

A base measure of precision for protein stability predictors: structural sensitivity

BACKGROUND

Prediction of the change in fold stability (ΔΔG) of a protein upon mutation is of major importance to protein engineering and screening of disease-causing variants. Many prediction methods can use 3D structural information to predict ΔΔG. While the performance of these methods has been extensively studied, a new problem has arisen due to the abundance of crystal structures: How precise are these methods in terms of structure input used, which structure should be used, and how much does it matter? Thus, there is a need to quantify the structural sensitivity of protein stability prediction methods.

RESULTS

We computed the structural sensitivity of six widely-used prediction methods by use of saturated computational mutagenesis on a diverse set of 87 structures of 25 proteins. Our results show that structural sensitivity varies massively and surprisingly falls into two very distinct groups, with methods that take detailed account of the local environment showing a sensitivity of ~ 0.6 to 0.8 kcal/mol, whereas machine-learning methods display much lower sensitivity (~ 0.1 kcal/mol). We also observe that the precision correlates with the accuracy for mutation-type-balanced data sets but not generally reported accuracy of the methods, indicating the importance of mutation-type balance in both contexts.

CONCLUSIONS

The structural sensitivity of stability prediction methods varies greatly and is caused mainly by the models and less by the actual protein structural differences. As a new recommended standard, we therefore suggest that ΔΔG values are evaluated on three protein structures when available and the associated standard deviation reported, to emphasize not just the accuracy but also the precision of the method in a specific study. Our observation that machine-learning methods deemphasize structure may indicate that folded wild-type structures alone, without the folded mutant and unfolded structures, only add modest value for assessing protein stability effects, and that side-chain-sensitive methods overstate the significance of the folded wild-type structure.

Helical ensembles outperform ideal helices in molecular replacement

Helical ensembles solve more structures by MR with AMPLE than do ideal helices and at no greater CPU cost.

The conventional approach in molecular replacement is the use of a related structure as a search model. However, this is not always possible as the availability of such structures can be scarce for poorly characterized families of proteins. In these cases, alternative approaches can be explored, such as the use of small ideal fragments that share high, albeit local, structural similarity with the unknown protein. Earlier versions of AMPLE enabled the trialling of a library of ideal helices, which worked well for largely helical proteins at suitable resolutions. Here, the performance of libraries of helical ensembles created by clustering helical segments is explored. The impacts of different B-factor treatments and different degrees of structural heterogeneity are explored. A 30% increase in the number of solutions obtained by AMPLE was observed when using this new set of ensembles compared with the performance with ideal helices. The boost in performance was notable across three different fold classes: transmembrane, globular and coiled-coil structures. Furthermore, the increased effectiveness of these ensembles was coupled to a reduction in the time required by AMPLE to reach a solution. AMPLE users can now take full advantage of this new library of search models by activating the ‘helical ensembles’ mode.

Factors influencing estimates of coordinate error for molecular replacement

Good prior estimates of the effective root-mean-square deviation (r.m.s.d.) between the atomic coordinates of the model and the target optimize the signal in molecular replacement, thereby increasing the success rate in difficult cases. Previous studies using protein structures solved by X-ray crystallography as models showed that optimal error estimates (refined after structure solution) were correlated with the sequence identity between the model and target, and with the number of residues in the model. Here, this work has been extended to find additional correlations between parameters of the model and the target and hence improved prior estimates of the coordinate error. Using a graph database, a curated set of 6030 molecular-replacement calculations using models that had been solved by X-ray crystallography was analysed to consider about 120 model and target parameters. Improved estimates were achieved by replacing the sequence identity with the Gonnet score for sequence similarity, as well as by considering the resolution of the target structure and the MolProbity score of the model. This approach was extended by analysing 12 610 additional molecular-replacement calculations where the model was determined by NMR. The median r.m.s.d. between pairs of models in an ensemble was found to be correlated with the estimated r.m.s.d. to the target. For models solved by NMR, the overall coordinate error estimates were larger than for structures determined by X-ray crystallography, and were more highly correlated with the number of residues.

Using Phaser and ensembles to improve the performance of SIMBAD

The conventional approach to search-model identification in molecular replacement (MR) is to screen a database of known structures using the target sequence. However, this strategy is not always effective, for example when the relationship between sequence and structural similarity fails or when the crystal contents are not those expected. An alternative approach is to identify suitable search models directly from the experimental data. SIMBAD is a sequence-independent MR pipeline that uses either a crystal lattice search or MR functions to directly locate suitable search models from databases. The previous version of SIMBAD used the fast AMoRe rotation-function search. Here, a new version of SIMBAD which makes use of Phaser and its likelihood scoring to improve the sensitivity of the pipeline is presented. It is shown that the additional compute time potentially required by the more sophisticated scoring is counterbalanced by the greater sensitivity, allowing more cases to trigger early-termination criteria, rather than running to completion. Using Phaser solved 17 out of 25 test cases in comparison to the ten solved with AMoRe, and it is shown that use of ensemble search models produces additional performance benefits.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.

A fragmentation and reassembly method for ab initio phasing

Ab initio phasing with de novo models has become a viable approach for structural solution from protein crystallographic diffraction data. This approach takes advantage of the known protein sequence information, predicts de novo models and uses them for structure determination by molecular replacement. However, even the current state-of-the-art de novo modelling method has a limit as to the accuracy of the model predicted, which is sometimes insufficient to be used as a template for successful molecular replacement. A fragment-assembly phasing method has been developed that starts from an ensemble of low-accuracy de novo models, disassembles them into fragments, places them independently in the crystallographic unit cell by molecular replacement and then reassembles them into a whole structure that can provide sufficient phase information to enable complete structure determination by automated model building. Tests on ten protein targets showed that the method could solve structures for eight of these targets, although the predicted de novo models cannot be used as templates for successful molecular replacement since the best model for each target is on average more than 4.0 Å away from the native structure. The method has extended the applicability of the ab initio phasing by de novo models approach. The method can be used to solve structures when the best de novo models are still of low accuracy.

Crystallographic phasing with NMR models: an envelope approach

X-ray crystallography and NMR are complementary tools in structural biology. However, it is often difficult to use NMR structures as search models in molecular replacement (MR) to phase crystallographic data. In this study, a new approach is reported utilizing a molecular envelope of NMR structures for MR phasing with the programFSEARCHat low resolution (about 6 Å). Several targets with both crystallographic and NMR structures available have been tested.FSEARCHwas able to find the correct translation and orientation of the search model in the crystallographic unit cell, while conventional MR procedures were unsuccessful.

Molecular replacement then and now

The `phase problem' in crystallography results from the inability to directly measure the phases of individual diffracted X-ray waves. While intensities are directly measured during data collection, phases must be obtained by other means. Several phasing methods are available (MIR, SAR, MAD, SAD and MR) and they all rely on the premise that phase information can be obtained if the positions of marker atoms in the unknown crystal structure are known. This paper is dedicated to the most popular phasing method, molecular replacement (MR), and represents a personal overview of the development, use and requirements of the methodology. The first description of noncrystallographic symmetry as a tool for structure determination was explained by Rossmann and Blow [Rossmann & Blow (1962), Acta Cryst. 15, 24-31]. The term `molecular replacement' was introduced as the name of a book in which the early papers were collected and briefly reviewed [Rossmann (1972), The Molecular Replacement Method. New York: Gordon & Breach]. Several programs have evolved from the original concept to allow faster and more sophisticated searches, including six-dimensional searches and brute-force approaches. While careful selection of the resolution range for the search and the quality of the data will greatly influence the outcome, the correct choice of the search model is probably still the main criterion to guarantee success in solving a structure using MR. Two of the main parameters used to define the `best' search model are sequence identity (25% or more) and structural similarity. Another parameter that may often be undervalued is the quality of the probe: there is clearly a relationship between the quality and the correctness of the chosen probe and its usefulness as a search model. Efforts should be made by all structural biologists to ensure that their deposited structures, which are potential search probes for future systems, are of the best possible quality.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

Assessing the chemical accuracy of protein structures via peptide acidity

Although the protein native state is a Boltzmann conformational ensemble, practical applications often require a representative model from the most populated region of that distribution. The acidity of the backbone amides, as reflected in hydrogen exchange rates, is exquisitely sensitive to the surrounding charge and dielectric volume distribution. For each of four proteins, three independently determined X-ray structures of differing crystallographic resolution were used to predict exchange for the static solvent-exposed amide hydrogens. The average correlation coefficients range from 0.74 for ubiquitin to 0.93 for Pyrococcus furiosus rubredoxin, reflecting the larger range of experimental exchange rates exhibited by the latter protein. The exchange prediction errors modestly correlate with the crystallographic resolution. MODELLER 9v6-derived homology models at ~60% sequence identity (36% identity for chymotrypsin inhibitor CI2) yielded correlation coefficients that are ~0.1 smaller than for the cognate X-ray structures. The most recently deposited NOE-based ubiquitin structure and the original NMR structure of CI2 fail to provide statistically significant predictions of hydrogen exchange. However, the more recent RECOORD refinement study of CI2 yielded predictions comparable to the X-ray and homology model-based analyses.

Improved crystallographic models through iterated local density-guided model deformation and reciprocal-space refinement

An approach is presented for addressing the challenge of model rebuilding after molecular replacement in cases where the placed template is very different from the structure to be determined. The approach takes advantage of the observation that a template and target structure may have local structures that can be superimposed much more closely than can their complete structures. A density-guided procedure for deformation of a properly placed template is introduced. A shift in the coordinates of each residue in the structure is calculated based on optimizing the match of model density within a 6 Å radius of the center of that residue with a prime-and-switch electron-density map. The shifts are smoothed and applied to the atoms in each residue, leading to local deformation of the template that improves the match of map and model. The model is then refined to improve the geometry and the fit of model to the structure-factor data. A new map is then calculated and the process is repeated until convergence. The procedure can extend the routine applicability of automated molecular replacement, model building and refinement to search models with over 2 Å r.m.s.d. representing 65-100% of the structure.

Challenges and surprises that arise with nucleic acids during model building and refinement

The process of building and refining crystal structures of nucleic acids, although similar to that for proteins, has some peculiarities that give rise to both various complications and various benefits. Although conventional isomorphous replacement phasing techniques are typically used to generate an experimental electron-density map for the purposes of determining novel nucleic acid structures, it is also possible to couple the phasing and model-building steps to permit the solution of complex and novel RNA three-dimensional structures without the need for conventional heavy-atom phasing approaches.

phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta

The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.

Improved technologies now routinely provide protein NMR structures useful for molecular replacement

Molecular replacement (MR) is widely used for addressing the phase problem in X-ray crystallography. Historically, crystallographers have had limited success using NMR structures as MR search models. Here, we report a comprehensive investigation of the utility of protein NMR ensembles as MR search models, using data for 25 pairs of X-ray and NMR structures solved and refined using modern NMR methods. Starting from NMR ensembles prepared by an improved protocol, FindCore, correct MR solutions were obtained for 22 targets. Based on these solutions, automatic model rebuilding could be done successfully. Rosetta refinement of NMR structures provided MR solutions for another two proteins. We also demonstrate that such properly prepared NMR ensembles and X-ray crystal structures have similar performance when used as MR search models for homologous structures, particularly for targets with sequence identity >40%.

SAD phasing using iodide ions in a high-throughput structural genomics environment

The Seattle Structural Genomics Center for Infectious Disease (SSGCID) focuses on the structure elucidation of potential drug targets from class A, B, and C infectious disease organisms. Many SSGCID targets are selected because they have homologs in other organisms that are validated drug targets with known structures. Thus, many SSGCID targets are expected to be solved by molecular replacement (MR), and reflective of this, all proteins are expressed in native form. However, many community request targets do not have homologs with known structures and not all internally selected targets readily solve by MR, necessitating experimental phase determination. We have adopted the use of iodide ion soaks and single wavelength anomalous dispersion (SAD) experiments as our primary method for de novo phasing. This method uses existing native crystals and in house data collection, resulting in rapid, low cost structure determination. Iodide ions are non-toxic and soluble at molar concentrations, facilitating binding at numerous hydrophobic or positively charged sites. We have used this technique across a wide range of crystallization conditions with successful structure determination in 16 of 17 cases within the first year of use (94% success rate). Here we present a general overview of this method as well as several examples including SAD phasing of proteins with novel folds and the combined use of SAD and MR for targets with weak MR solutions. These cases highlight the straightforward and powerful method of iodide ion SAD phasing in a high-throughput structural genomics environment.

Solving novel RNA structures using only secondary structural fragments

The crystallographic phase problem is the primary bottleneck encountered when attempting to solve macromolecular structures for which no close crystallographic structural homologues are known. Typically, isomorphous "heavy-atom" replacement and/or anomalous dispersion methods must be used in such cases to obtain experimentally-determined phases. Even three-dimensional NMR structures of the same macromolecule are often not sufficient to solve the crystallographic phase problem. RNA crystal structures present additional challenges due to greater difficulty in obtaining suitable heavy-atom derivatives. We present a unique approach to solve the phase problem for novel RNA crystal structures that has enjoyed a reasonable degree of success. This approach involves modeling only those portions of the RNA sequence whose structure can be predicted readily, i.e., the individual A-form helical regions and well-known stem-loop sub-structures. We have found that no prior knowledge of how the helices and other structural elements are arranged with respect to one another in three-dimensional space, or in some cases, even the sequence, is required to obtain a useable solution to the phase problem, using simultaneous molecular replacement of a set of generic helical RNA fragments.

Crystal structures of Streptococcus pyogenes Dpr reveal a dodecameric iron-binding protein with a ferroxidase site

DNA-binding protein from starved cells (Dps)-like proteins are key factors involved in oxidative stress protection in bacteria. They bind and oxidize iron, thus preventing the formation of harmful reactive oxygen species that can damage biomolecules, particularly DNA. Dps-like proteins are composed of 12 identical subunits assembled in a spherical structure with a hollow central cavity. The iron oxidation occurs at 12 intersubunit sites located at dimer interfaces. Streptococcus pyogenes Dps-like peroxide resistance protein (Dpr) has been previously found to protect the catalase-lacking S. pyogenes bacterium from oxidative stress. We have determined the crystal structure of S. pyogenes Dpr, the second Dpr structure from a streptococcal bacterium, in iron-free and iron-bound forms at 2.0- and 1.93-A resolution, respectively. The iron binds to well-conserved sites at dimer interfaces and is coordinated directly to Asp77 and Glu81 from one monomer, His50 from a twofold symmetry-related monomer, a glycerol molecule, and a water molecule. Upon iron binding, Asp77 and Glu81 change conformation. Site-directed mutagenesis of active-site residues His50, His62, Asp66, Asp77, and Glu81 to Ala revealed a dramatic decrease in iron incorporation. A short helix at the N-terminal was found in a different position compared with other Dps-like proteins. Two types of pores were identified in the dodecamer. Although the N-terminal pore was found to be similar to that of other Dps-like proteins, the C-terminal pore was found to be blocked by bulky Tyr residues instead of small residues present in other Dps-like proteins.

Cluster analysis for phasing with molecular replacement: a feasibility study

Molecular replacement with the simultaneous use of several search functions may solve the phase problem when the conventional molecular-replacement procedure fails to identify the solution.

Molecular replacement can fail to find a solution, namely a unique orientation and position of a search model, even when many search models are tested under various conditions. Simultaneous use of the results of these searches may help in the solution of such difficult structures. A closeness between the peaks of several calculated rotation functions may identify the model orientation. The largest and most compact cluster of such peaks usually corresponds to models which are oriented similarly to the molecule under study. A search for the optimal translation may be more problematic and both individual translation functions and straightforward cluster analysis in the space of geometric parameters such as rotation angles and translation vectors may give no result. An improvement may be obtained by performing cluster analysis of the peaks of several translation functions in phase-set space. In this case, the Fourier maps computed using the observed structure-factor magnitudes and the phases calculated from differently positioned models are compared. Again, as a rule, the largest and the most compact cluster corresponds to the correct solution. The result of the updated procedure is no longer a single search model but an averaged Fourier map.

Synergy of NMR, computation, and X-ray crystallography for structural biology

NMR spectroscopy and X-ray crystallography are currently the two most widely applied methods for the determination of macromolecular structures at high resolution. More recently, significant advances have been made in algorithms for the de novo prediction of protein structure, and, in favorable cases, the predicted models agree extremely well with experimentally determined structures. Here, we demonstrate a synergistic combination of NMR spectroscopy, de novo structure prediction, and X-ray crystallography in an effective overall strategy for rapidly determining the structure of the coat protein C-terminal domain from the Sulfolobus islandicus rod-shaped virus (SIRV). This approach takes advantage of the most accessible aspects of each structural technique and may be widely applicable for structure determination.

Improving NMR protein structure quality by Rosetta refinement: a molecular replacement study

The structure of human protein HSPC034 has been determined by both solution nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. Refinement of the NMR structure ensemble, using a Rosetta protocol in the absence of NMR restraints, resulted in significant improvements not only in structure quality, but also in molecular replacement (MR) performance with the raw X-ray diffraction data using MOLREP and Phaser. This method has recently been shown to be generally applicable with improved MR performance demonstrated for eight NMR structures refined using Rosetta (Qian et al., Nature 2007;450:259-264). Additionally, NMR structures of HSPC034 calculated by standard methods that include NMR restraints have improvements in the RMSD to the crystal structure and MR performance in the order DYANA, CYANA, XPLOR-NIH, and CNS with explicit water refinement (CNSw). Further Rosetta refinement of the CNSw structures, perhaps due to more thorough conformational sampling and/or a superior force field, was capable of finding alternative low energy protein conformations that were equally consistent with the NMR data according to the Recall, Precision, and F-measure (RPF) scores. On further examination, the additional MR-performance shortfall for NMR refined structures as compared with the X-ray structure were attributed, in part, to crystal-packing effects, real structural differences, and inferior hydrogen bonding in the NMR structures. A good correlation between a decrease in the number of buried unsatisfied hydrogen-bond donors and improved MR performance demonstrates the importance of hydrogen-bond terms in the force field for improving NMR structures. The superior hydrogen-bond network in Rosetta-refined structures demonstrates that correct identification of hydrogen bonds should be a critical goal of NMR structure refinement. Inclusion of nonbivalent hydrogen bonds identified from Rosetta structures as additional restraints in the structure calculation results in NMR structures with improved MR performance.

Prospects for de novo phasing with de novo protein models

The prospect of phasing diffraction data sets ;de novo' for proteins with previously unseen folds is appealing but largely untested. In a first systematic exploration of phasing with Rosetta de novo models, it is shown that all-atom refinement of coarse-grained models significantly improves both the model quality and performance in molecular replacement with the Phaser software. 15 new cases of diffraction data sets that are unambiguously phased with de novo models are presented. These diffraction data sets represent nine space groups and span a large range of solvent contents (33-79%) and asymmetric unit copy numbers (1-4). No correlation is observed between the ease of phasing and the solvent content or asymmetric unit copy number. Instead, a weak correlation is found with the length of the modeled protein: larger proteins required somewhat less accurate models to give successful molecular replacement. Overall, the results of this survey suggest that de novo models can phase diffraction data for approximately one sixth of proteins with sizes of 100 residues or less. However, for many of these cases, ;de novo phasing with de novo models' requires significant investment of computational power, much greater than 10(3) CPU days per target. Improvements in conformational search methods will be necessary if molecular replacement with de novo models is to become a practical tool for targets without homology to previously solved protein structures.

A general method for phasing novel complex RNA crystal structures without heavy-atom derivatives

The crystallographic phase problem [Muirhead & Perutz (1963), Nature (London), 199, 633-638] remains the single major impediment to obtaining a three-dimensional structure of a macromolecule once suitable crystals have been obtained. Recently, it was found that it was possible to solve the structure of a 142-nucleotide L1 ligase ribozyme heterodimer that possesses no noncrystallographic symmetry without heavy-atom derivatives, anomalous scattering atoms or other modifications and without a model of the tertiary structure of the ribozyme [Robertson & Scott (2007), Science, 315, 1549-1553]. Using idealized known RNA secondary-structural fragments such as A-form helices and GNRA tetraloops in an iterative molecular-replacement procedure, it was possible to obtain an estimated phase set that, when subjected to solvent flattening, yielded an interpretable electron-density map with minimized model bias, allowing the tertiary structure of the ribozyme to be solved. This approach has also proven successful with other ribozymes, structured RNAs and RNA-protein complexes.

High-resolution structure prediction and the crystallographic phase problem

The energy-based refinement of low-resolution protein structure models to atomic-level accuracy is a major challenge for computational structural biology. Here we describe a new approach to refining protein structure models that focuses sampling in regions most likely to contain errors while allowing the whole structure to relax in a physically realistic all-atom force field. In applications to models produced using nuclear magnetic resonance data and to comparative models based on distant structural homologues, the method can significantly improve the accuracy of the structures in terms of both the backbone conformations and the placement of core side chains. Furthermore, the resulting models satisfy a particularly stringent test: they provide significantly better solutions to the X-ray crystallographic phase problem in molecular replacement trials. Finally, we show that all-atom refinement can produce de novo protein structure predictions that reach the high accuracy required for molecular replacement without any experimental phase information and in the absence of templates suitable for molecular replacement from the Protein Data Bank. These results suggest that the combination of high-resolution structure prediction with state-of-the-art phasing tools may be unexpectedly powerful in phasing crystallographic data for which molecular replacement is hindered by the absence of sufficiently accurate previous models.

Crystal structures of RsbQ, a stress-response regulator in Bacillus subtilis

Growth-limiting stresses in bacteria induce the general stress response to protect the cells against future stresses. Energy stress caused by starvation conditions in Bacillus subtilis is transmitted to the sigma(B) transcription factor by stress-response regulators. RsbP, a positive regulator, is a phosphatase containing a PAS (Per-ARNT-Sim) domain and requires catalytic function of a putative alpha/beta hydrolase, RsbQ, to be activated. These two proteins have been found to interact with each other. We determined the crystal structures of RsbQ in native and inhibitor-bound forms to investigate why RsbP requires RsbQ. These structures confirm that RsbQ belongs to the alpha/beta hydrolase superfamily. Since the catalytic triad is buried inside the molecule due to the closed conformation, the active site is constructed as a hydrophobic cavity that is nearly isolated from the solvent. This suggests that RsbQ has specificity for a hydrophobic small compound rather than a macromolecule such as RsbP. Moreover, structural comparison with other alpha/beta hydrolases demonstrates that a unique loop region of RsbQ is a likely candidate for the interaction site with RsbP, and the interaction might be responsible for product release by operating the hydrophobic gate equipped between the cavity and the solvent. Our results support the possibility that RsbQ provides a cofactor molecule for the mature functionality of RsbP.

Structural insight into modest binding of a non-PXXP ligand to the signal transducing adaptor molecule-2 Src homology 3 domain

Although some exceptional motifs have been identified, it is well known that the PXXP motif is the motif of ligand proteins generally recognized by the Src homology 3 (SH3) domain. SH3-ligand interactions are usually weak, with ordinary KD approximately 10 microM. The structural basis for a tight and specific association (KD = 0.24 microm) between Gads SH3 and a novel motif, PX(V/I)(D/N)RXXKP, was revealed in a previous structural analysis of the complex formed between them. In this paper, we report the crystal structure of the signal transducing adaptor molecule-2 (STAM2) SH3 domain in complex with a peptide with a novel motif derived from a ligand protein, UBPY. The derived KD value for this complex is 27 microM. The notable difference in affinity for these parallel complexes may be explained because the STAM2 SH3 structure does not provide a specificity pocket for binding, whereas the Gads SH3 structure does. Instead, the structure of STAM2 SH3 is analogous to that of Grb2 SH3 which, in addition to normal PXXP ligands, has also been shown to moderately recognize the novel motif discussed herein. Thus, the extremely tight interaction observed between Gads SH3 and the novel motif is caused not by an innate ability of the novel motif but rather by an evolutionary change in the Gads SH3 domain. Instead, SH3 domains of STAM2 and Grb2 retain the moderate characteristics of recognizing their ligand proteins like other SH3 domains for appropriate transient interactions between signaling molecules.

Crystal Structure of Trimestatin, a Disintegrin Containing a Cell Adhesion Recognition Motif RGD

Disintegrins are a family of small proteins containing an Arg-Gly-Asp (RGD) sequence motif that binds specifically to integrin receptors. Since the integrin is known to serve as the final common pathway leading to aggregation via formation of platelet-platelet bridges, disintegrins act as fibrinogen receptor antagonists. Here, we report the first crystal structure of a disintegrin, trimestatin, found in snake venom. The structure of trimestatin at 1.7A resolution reveals that a number of turns and loops form a rigid core stabilized by six disulfide bonds. Electron densities of the RGD sequence are visible clearly at the tip of a hairpin loop, in such a manner that the Arg and Asp side-chains point in opposite directions. A docking model using the crystal structure of integrin alphaVbeta3 suggests that the Arg binds to the propeller domain, and Asp to the betaA domain. This model indicates that the C-terminal region is another potential binding site with integrin receptors. In addition to the RGD sequence, the structural evidence of a C-terminal region (Arg66, Trp67 and Asn68) important for disintegrin activity allows understanding of the high affinity and selectiveness of snake venom disintegrin for integrin receptors. The crystal structure of trimestatin should provide a useful framework for designing and developing more effective drugs for controlling platelet aggregation and anti-angiogenesis cancer.