Specific versus non-specific contacts in protein crystals

Structural basis for coupled ATP-driven electron transfer in the double-cubane cluster protein

Electron transfers coupled to the hydrolysis of ATP allow various metalloenzymes to catalyze reductions at very negative reduction potentials. The double-cubane cluster protein (DCCP) catalyzes the reduction of small molecules, such as acetylene and hydrazine, with electrons provided by its cognate ATP-hydrolyzing reductase (DCCP-R). How ATP-driven electron transfer occurs is not known. To resolve the structural basis for ATP-driven electron transfer, we solved the structures of the DCCP:DCCP-R complex in three different states. The structures show that the DCCP-R homodimer is covalently bridged by a [4Fe4S] cluster that is aligned with the twofold axis of the DCCP homodimer, positioning the [4Fe4S] cluster to enable electron transfer to both double-cubane clusters in the DCCP dimer. DCCP and DCCP-R form stable complexes independent of oxidation state or nucleotides present, and electron transfer requires the hydrolysis of ATP. Electron transfer appears to be additionally driven by modulating the angle between the helices binding the [4Fe4S] cluster. We observed hydrogen bond networks running from the ATP binding site via the [4Fe4S] cluster in DCCP-R to the double-cubane cluster in DCCP, allowing the propagation of conformational changes. Remarkable similarities between the DCCP:DCCP-R complex and the nonhomologous nitrogenases suggest a convergent evolution of catalytic strategies to achieve ATP-driven electron transfers between iron-sulfur clusters.

QSalignWeb: A Server to Predict and Analyze Protein Quaternary Structure

The identification of physiologically relevant quaternary structures (QSs) in crystal lattices is challenging. To predict the physiological relevance of a particular QS, QSalign searches for homologous structures in which subunits interact in the same geometry. This approach proved accurate but was limited to structures already present in the Protein Data Bank (PDB). Here, we introduce a webserver (www.QSalign.org) allowing users to submit homo-oligomeric structures of their choice to the QSalign pipeline. Given a user-uploaded structure, the sequence is extracted and used to search homologs based on sequence similarity and PFAM domain architecture. If structural conservation is detected between a homolog and the user-uploaded QS, physiological relevance is inferred. The web server also generates alternative QSs with PISA and processes them the same way as the query submitted to widen the predictions. The result page also shows representative QSs in the protein family of the query, which is informative if no QS conservation was detected or if the protein appears monomeric. These representative QSs can also serve as a starting point for homology modeling.

The comparative analysis of the properties and structures of purine nucleoside phosphorylases from thermophilic bacterium Thermus thermophilus HB27

Two recombinant purine nucleoside phosphorylases from thermophilic bacterium Thermus thermophilus HB27 encoded by genes TT_C1070 (TthPNPI) and TT_C0194 (TthPNPII) were purified and characterized. The comparative analysis of their sequences, molecular weight, enzymes specificity and kinetics of the catalyzed reaction were realized. As a result, it was determined that the TthPNPI is specific to guanosine while the TthPNPII to adenosine. According to the results of the size exclusion chromatography and SAXS study both enzymes are hexameric molecules. Based on the sequence alignment with homologous purine nucleoside phosphorylases (PNPs), Asn was identified as a purine base recognizing residue in the active site of TthPNPI and Asp in TthPNPII. The three-dimensional structure of TthPNPII was solved at 2.5 Å resolution by molecular replacement method using crystals grown in microgravity. Position of phosphate in the active site cavity is located. The possible arrangement of adenosine and guanosine in TthPNPII active site cavity is considered using superposition with the structures of homologous trimeric and hexameric PNPs complexed with corresponding substrates. The peculiarities of oligomeric structure of TthPNPII in comparison with homologous PNPs are described. It is shown that two trimeric molecules of TthPNPII in the asymmetric part of the unit cell are connected by three two-fold axis into a hexamer with 32-point symmetry. This type of hexameric structure of PNP is found for the first time. The interface area between the subunits in trimeric molecule and between the trimers in TthPNPII hexamer is described.Communicated by Ramaswamy H. Sarma.

Electron Transfer in Nitrogenase

Nitrogenase is the only enzyme capable of reducing N2 to NH3. This challenging reaction requires the coordinated transfer of multiple electrons from the reductase, Fe-protein, to the catalytic component, MoFe-protein, in an ATP-dependent fashion. In the last two decades, there have been significant advances in our understanding of how nitrogenase orchestrates electron transfer (ET) from the Fe-protein to the catalytic site of MoFe-protein and how energy from ATP hydrolysis transduces the ET processes. In this review, we summarize these advances, with focus on the structural and thermodynamic redox properties of nitrogenase component proteins and their complexes, as well as on new insights regarding the mechanism of ET reactions during catalysis and how they are coupled to ATP hydrolysis. We also discuss recently developed chemical, photochemical, and electrochemical methods for uncoupling substrate reduction from ATP hydrolysis, which may provide new avenues for studying the catalytic mechanism of nitrogenase.

Distinguishing crystallographic from biological interfaces in protein complexes: role of intermolecular contacts and energetics for classification

BACKGROUND

Study of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems.

RESULTS

In this work, we are providing new insights into the differences between biological and crystallographic complexes by focusing on "pair-properties" of interfaces that have not yet been fully investigated. We investigated properties such intermolecular residue-residue contacts (already successfully applied to the prediction of binding affinities) and interaction energies (electrostatic, Van der Waals and desolvation). By using the XtalMany and BioMany interface datasets, we show that interfacial residue contacts, classified as a function of their physico-chemical properties, can distinguish between biological and crystallographic interfaces. The energetic terms show, on average, higher values for crystal interfaces, reflecting a less stable interface due to crystal packing compared to biological interfaces. By using a variety of machine learning approaches, we trained a new interface classification predictor based on contacts and interaction energetic features. Our predictor reaches an accuracy in classifying biological vs crystal interfaces of 0.92, compared to 0.88 for EPPIC (one of the main state-of-the-art classifiers reporting same performance as PISA).

CONCLUSION

In this work we have gained insights into the nature of intermolecular contacts and energetics terms distinguishing biological from crystallographic interfaces. Our findings might have a broader applicability in structural biology, for example for the identification of near native poses in docking. We implemented our classification approach into an easy-to-use and fast software, freely available to the scientific community from http://github.com/haddocking/interface-classifier .

Integrating co-evolutionary signals and other properties of residue pairs to distinguish biological interfaces from crystal contacts

It remains challenging to accurately discriminate between biological and crystal interfaces. Most existing analyses and algorithms focused on the features derived from a single side of the interface. However, less attention has been paid to the properties of residue pairs across protein interfaces. To address this problem, we defined a novel co-evolutionary feature for homodimers through integrating direct coupling analysis and image processing techniques. The residue pairs across biological homodimeric interfaces were significantly enriched in co-evolving residues compared to those across crystal contacts, resulting in a promising classification accuracy with area under the curves (AUCs) of >0.85. Considering the availability of co-evolutionary feature, we also designed other residue pair based features that were useful for both homodimers and heterodimers. The most informative residue pairs were identified to reflect the interaction preferences across protein interfaces. Regarding the other extant properties, we designed the new descriptors at the interface residue level as well as at the pairwise contact level. Extensive validation showed that these single properties can be used to identify biological interfaces with AUCs ranging from 0.60 to 0.88. By integrating co-evolutionary feature with other residue pair based properties, our final prediction model output excellent performance with AUCs of >0.91 on different datasets. Compared to existing methods, our algorithm not only yielded better or comparable results but also provided complementary information. An easy-to-use web server is freely accessible at http://liulab.hzau.edu.cn/RPAIAnalyst.

Identifying G protein-coupled receptor dimers from crystal packings

Dimers of G protein-coupled receptors (GPCRs) are believed to be important for signaling with their associated G proteins. Low-resolution electron microscopy has shown rhodopsin dimers in native retinal membranes, and CXCR4 dimers have been found in several different crystal structures. Evidence for dimers of other GPCRs is more indirect. An alternative to computational modeling studies is to search for parallel dimers in the packing environments of the reported crystal structures of GPCRs. Two major structural types of GPCR dimers exist (as predicted by others), but there is considerable structural variation within each cluster. The different structural variants described here might reflect different functional properties and should provide a range of model structures for computational and experimental examination.

Inferring and Using Protein Quaternary Structure Information from Crystallographic Data

A precise knowledge of the quaternary structure of proteins is essential to illuminate both their function and their evolution. The major part of our knowledge on quaternary structure is inferred from X-ray crystallography data, but this inference process is hard and error-prone. The difficulty lies in discriminating fortuitous protein contacts, which make up the lattice of protein crystals, from biological protein contacts that exist in the native cellular environment. Here, we review methods devised to discriminate between both types of contacts and describe resources for downloading protein quaternary structure information and identifying high-confidence quaternary structures. The use of high-confidence datasets of quaternary structures will be critical for the analysis of structural, functional, and evolutionary properties of proteins.

Packing topology in crystals of proteins and small molecules: a comparison

We compared the topologies of protein and small molecule crystals, which have many common features - both are molecular crystals with intermolecular interactions much weaker than intramolecular interactions. They also have different features - a considerably large fraction of the volume of protein crystals is occupied by liquid water while no room is available to other molecules in small molecule crystals. We analyzed the overall and local topology and performed multilevel topological analyses (with the software package ToposPro) of carefully selected high quality sets of protein and small molecule crystal structures. Given the suboptimal packing of protein crystals, which is due the special shape and size of proteins, it would be reasonable to expect that the topology of protein crystals is different from the topology of small molecule crystals. Surprisingly, we discovered that these two types of crystalline compounds have strikingly similar topologies. This might suggest that molecular crystal formations share symmetry rules independent of molecular dimension.

The "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability

Crystallization of macromolecules has long been perceived as a stochastic process, which cannot be predicted or controlled. This is consistent with another popular notion that the interactions of molecules within the crystal, i.e., crystal contacts, are essentially random and devoid of specific physicochemical features. In contrast, functionally relevant surfaces, such as oligomerization interfaces and specific protein-protein interaction sites, are under evolutionary pressures so their amino acid composition, structure, and topology are distinct. However, current theoretical and experimental studies are significantly changing our understanding of the nature of crystallization. The increasingly popular "sticky patch" model, derived from soft matter physics, describes crystallization as a process driven by interactions between select, specific surface patches, with properties thermodynamically favorable for cohesive interactions. Independent support for this model comes from various sources including structural studies and bioinformatics. Proteins that are recalcitrant to crystallization can be modified for enhanced crystallizability through chemical or mutational modification of their surface to effectively engineer "sticky patches" which would drive crystallization. Here, we discuss the current state of knowledge of the relationship between the microscopic properties of the target macromolecule and its crystallizability, focusing on the "sticky patch" model. We discuss state-of-the-art in silico methods that evaluate the propensity of a given target protein to form crystals based on these relationships, with the objective to design variants with modified molecular surface properties and enhanced crystallization propensity. We illustrate this discussion with specific cases where these approaches allowed to generate crystals suitable for structural analysis.

Common Evolutionary Origin of Procapsid Proteases, Phage Tail Tubes, and Tubes of Bacterial Type VI Secretion Systems

Many large viruses, including tailed dsDNA bacteriophages and herpesviruses, assemble their capsids via formation of precursors, called procapsids or proheads. The prohead has an internal core, made of scaffolding proteins, and an outer shell, formed by the major capsid protein. The prohead usually contains a protease, which is activated during capsid maturation to destroy the inner core and liberate space for the genome. Here, we report a 2.0 Å resolution structure of the pentameric procapsid protease of bacteriophage T4, gene product (gp)21. The structure corresponds to the enzyme's pre-active state in which its N-terminal region blocks the catalytic center, demonstrating that the activation mechanism involves self-cleavage of nine N-terminal residues. We describe similarities and differences between T4 gp21 and related herpesvirus proteases. We found that gp21 and the herpesvirus proteases have similarity with proteins forming the tubes of phage tails and bacterial type VI secretion systems, suggesting their common evolutionary origin.

ClusPro-DC: Dimer Classification by the Cluspro Server for Protein-Protein Docking

ClusPro-DC (https://cluspro.bu.edu/) implements a straightforward approach to the discrimination between crystallographic and biological dimers by docking the two subunits to exhaustively sample the interaction energy landscape. If a substantial number of low energy docked poses cluster in a narrow vicinity of the native structure of the dimer, then one can assume that there is a well-defined free energy well around the native state, which makes the interaction stable. In contrast, if the interaction sites in the docked poses do not form a large enough cluster around the native structure, then it is unlikely that the subunits form a stable biological dimer. The number of near-native structures is used to estimate the probability of a dimer being biological. Currently, the server examines only the stability of a given interface rather than generating all putative quaternary structures as accomplished by PISA or EPPIC, but it complements the information provided by these methods.

Spatiotemporal variation of mammalian protein complex stoichiometries

Background

Recent large-scale studies revealed cell-type specific proteomes. However, protein complexes, the basic functional modules of a cell, have been so far mostly considered as static entities with well-defined structures. The co-expression of their members has not been systematically charted at the protein level.

Results

We used measurements of protein abundance across 11 cell types and five temporal states to analyze the co-expression and the compositional variations of 182 well-characterized protein complexes. We show that although the abundance of protein complex members is generally co-regulated, a considerable fraction of all investigated protein complexes is subject to stoichiometric changes. Compositional variation is most frequently seen in complexes involved in chromatin regulation and cellular transport, and often involves paralog switching as a mechanism for the regulation of complex stoichiometry. We demonstrate that compositional signatures of variable protein complexes have discriminative power beyond individual cell states and can distinguish cancer cells from healthy ones.

Conclusions

Our work demonstrates that many protein complexes contain variable members that cause distinct stoichometries and functionally fine-tune complexes spatiotemporally. Only a fraction of these compositional variations is mediated by changes in transcription and other mechanisms regulating protein abundance contribute to determine protein complex stoichiometries. Our work highlights the superior power of proteome profiles to study protein complexes and their variants across cell states.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0912-5) contains supplementary material, which is available to authorized users.

β-Subunit Binding Is Sufficient for Ligands to Open the Integrin αIIbβ3 Headpiece

The platelet integrin αIIbβ3 binds to a KQAGDV motif at the fibrinogen γ-chain C terminus and to RGD motifs present in loops in many extracellular matrix proteins. These ligands bind in a groove between the integrin α and β-subunits; the basic Lys or Arg side chain hydrogen bonds to the αIIb-subunit, and the acidic Asp side chain coordinates to a metal ion held by the β3-subunit. Ligand binding induces headpiece opening, with conformational change in the β-subunit. During this opening, RGD slides in the ligand-binding pocket toward αIIb, with movement of the βI-domain β1-α1 loop toward αIIb, enabling formation of direct, charged hydrogen bonds between the Arg side chain and αIIb. Here we test whether ligand interactions with β3 suffice for stable ligand binding and headpiece opening. We find that the AGDV tetrapeptide from KQAGDV binds to the αIIbβ3 headpiece with affinity comparable with the RGDSP peptide from fibronectin. AGDV induced complete headpiece opening in solution as shown by increase in hydrodynamic radius. Soaking of AGDV into closed αIIbβ3 headpiece crystals induced intermediate states similarly to RGDSP. AGDV has very little contact with the α-subunit. Furthermore, as measured by epitope exposure, AGDV, like the fibrinogen γ C-terminal peptide and RGD, caused integrin extension on the cell surface. Thus, pushing by the β3-subunit on Asp is sufficient for headpiece opening and ligand sliding, and no pulling by the αIIb subunit on Arg is required.

Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein–protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein–protein docking.

Supplementary information: Supplementary data are available at Bioinformatics online.

Contact:guido.capitani@psi.ch

What Glues a Homodimer Together: Systematic Analysis of the Stabilizing Effect of an Aromatic Hot Spot in the Protein-Protein Interface of the tRNA-Modifying Enzyme Tgt

Shigella bacteria constitute the causative agent of bacillary dysentery, an acute inflammatory disease causing the death of more than one million humans per year. A null mutation in the tgt gene encoding the tRNA-modifying enzyme tRNA-guanine transglycosylase (Tgt) was found to drastically decrease the pathogenicity of Shigella bacteria, suggesting the use of Tgt as putative target for selective antibiotics. The enzyme is only functionally active as a homodimer; thus, interference with the formation of its protein-protein interface is an attractive opportunity for therapeutic intervention. To better understand the driving forces responsible for the assembly, stability, and formation of the homodimer, we studied the properties of the residues that establish the dimer interface in detail. We performed site-directed mutagenesis and controlled shifts in the monomer/dimer equilibrium ratio in solution in a concentration-dependent manner by native mass spectrometry and used crystal structure analysis to elucidate the geometrical modulations resulting from mutational variations. The wild-type enzyme exhibits nearly exclusive dimer geometry. A patch of four aromatic amino acids, embedded into a ring of hydrophobic residues and further stabilized by a network of H-bonds, is essential for the stability of the dimer's contact. Accordingly, any perturbance in the constitution of this aromatic patch by nonaromatic residues reduces dimer stability significantly, with some of these exchanges resulting in a nearly exclusively monomeric state. Apart from the aromatic hot spot, the interface comprises an extended loop-helix motif that exhibits remarkable flexibility. In the destabilized mutated variants, the loop-helix motif adopts deviating conformations in the interface region, and a number of water molecules, penetrating into the interface, are observed.

Nonspecific yet decisive: Ubiquitination can affect the native-state dynamics of the modified protein

Ubiquitination is one of the most common post-translational modifications of proteins, and mediates regulated protein degradation among other cellular processes. A fundamental question regarding the mechanism of protein ubiquitination is whether and how ubiquitin affects the biophysical nature of the modified protein. For some systems, it was shown that the position of ubiquitin within the attachment site is quite flexible and ubiquitin does not specifically interact with its substrate. Nevertheless, it was revealed that polyubiquitination can decrease the thermal stability of the modified protein in a site-specific manner because of alterations of the thermodynamic properties of the folded and unfolded states. In this study, we used detailed atomistic simulations to focus on the molecular effects of ubiquitination on the native structure of the modified protein. As a model, we used Ubc7, which is an E2 enzyme whose in vivo ubiquitination process is well characterized and known to lead to degradation. We found that, despite the lack of specific direct interactions between the ubiquitin moiety and Ubc7, ubiquitination decreases the conformational flexibility of certain regions of the substrate Ubc7 protein, which reduces its entropy and thus destabilizes it. The strongest destabilizing effect was observed for systems in which Lys48-linked tetra-ubiquitin was attached to sites used for in vivo degradation. These results reveal how changes in the configurational entropy of the folded state may modulate the stability of the protein's native state. Overall, our results imply that ubiquitination can modify the biophysical properties of the attached protein in the folded state and that, in some proteins, different ubiquitination sites will lead to different biophysical outcomes. We propose that this destabilizing effect of polyubiquitin on the substrate is linked to the functions carried out by the modification, and in particular, regulatory control of protein half-life through proteasomal degradation.

Simulation of protein association: Kinetic pathways towards crystal contacts

We conducted molecular dynamics simulations combined with distance-based umbrella sampling and forward flux sampling to investigate the early stages of protein crystallization. Formation of contacts with long-range interactions and/or an exposed position on the protein surface was kinetically preferred over more stable hydrophobic contacts with a shorter attractive range, while the thermodynamic stability of the protein crystal was provided by hydrophobic interactions. Contacts with a large interaction area showed complex dissociation pathways that were not detected by distance-based umbrella sampling. Instead, forward flux sampling simulations of contact dissociation identified long-range attractive interactions.

A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta

Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.

Structural evidence for asymmetrical nucleotide interactions in nitrogenase

The roles of ATP hydrolysis in electron-transfer (ET) reactions of the nitrogenase catalytic cycle remain obscure. Here, we present a new structure of a nitrogenase complex crystallized with MgADP and MgAMPPCP, an ATP analogue. In this structure the two nucleotides are bound asymmetrically by the Fe-protein subunits connected to the two different MoFe-protein subunits. This binding mode suggests that ATP hydrolysis and phosphate release may proceed by a stepwise mechanism. Through the associated Fe-protein conformational changes, a stepwise mechanism is anticipated to prolong the lifetime of the Fe-protein-MoFe-protein complex and, in turn, could orchestrate the sequence of intracomplex ET required for substrate reduction.

Use B-factor related features for accurate classification between protein binding interfaces and crystal packing contacts

Background

Distinction between true protein interactions and crystal packing contacts is important for structural bioinformatics studies to respond to the need of accurate classification of the rapidly increasing protein structures. There are many unannotated crystal contacts and there also exist false annotations in this rapidly expanding volume of data. Previous tools have been proposed to address this problem. However, challenging issues still remain, such as low performance when the training and test data contain mixed interfaces having diverse sizes of contact areas.

Methods and results

B factor is a measure to quantify the vibrational motion of an atom, a more relevant feature than interface size to characterize protein binding. We propose to use three features related to B factor for the classification between biological interfaces and crystal packing contacts. The first feature is the sum of the normalized B factors of the interfacial atoms in the contact area, the second is the average of the interfacial B factor per residue in the chain, and the third is the average number of interfacial atoms with a negative normalized B factor per residue in the chain. We investigate the distribution properties of these basic features and a compound feature on four datasets of biological binding and crystal packing, and on a protein binding-only dataset with known binding affinity. We also compare the cross-dataset classification performance of these features with existing methods and with a widely-used and the most effective feature interface area. The results demonstrate that our features outperform the interface area approach and the existing prediction methods remarkably for many tests on all of these datasets.

Conclusions

The proposed B factor related features are more effective than interface area to distinguish crystal packing from biological binding interfaces. Our computational methods have a potential for large-scale and accurate identification of biological interactions from the experimentally determined structural data stored at PDB which may have diverse interface sizes.

Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling

Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES) simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

Dynamic nature of the protein-protein interactions is an important element of cellular processes such as metabolic reactions and signal transduction, but its atomistic details are still unclear. Computational survey using molecular dynamics simulation is a straightforward method to elucidate these atomistic protein-protein interaction processes. However, a sufficient configurational sampling of the large system containing the atomistic protein complex model and explicit solvent remains a great challenge due to the long timescale involved. Here, we demonstrate that the multiscale enhanced sampling (MSES) successfully captured the atomistic details of the association/dissociation processes of a barnase-barstar complex covering the sampled space from the native complex structure to fully non-native configurations. The landscape derived from the simulation indicates that the association process is funnel-like downhill, analogously to the funnel landscape of fast-folding proteins. The funnel was found to be originated from near-native orientations guided by the shape complementarity between barnase and barstar, accelerating the formation of native inter-molecular interactions to complete the final complex structure.

A PDB-wide, evolution-based assessment of protein-protein interfaces

Background

Thanks to the growth in sequence and structure databases, more than 50 million sequences are now available in UniProt and 100,000 structures in the PDB. Rich information about protein–protein interfaces can be obtained by a comprehensive study of protein contacts in the PDB, their sequence conservation and geometric features.

Results

An automated computational pipeline was developed to run our Evolutionary Protein–Protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces. This allows the analysis of interface data on a PDB-wide scale. Two large benchmark datasets of biological interfaces and crystal contacts, each containing about 3000 entries, were automatically generated based on criteria thought to be strong indicators of interface type. The BioMany set of biological interfaces includes NMR dimers solved as crystal structures and interfaces that are preserved across diverse crystal forms, as catalogued by the Protein Common Interface Database (ProtCID) from Xu and Dunbrack. The second dataset, XtalMany, is derived from interfaces that would lead to infinite assemblies and are therefore crystal contacts. BioMany and XtalMany were used to benchmark the EPPIC approach. The performance of EPPIC was also compared to classifications from the Protein Interfaces, Surfaces, and Assemblies (PISA) program on a PDB-wide scale, finding that the two approaches give the same call in about 88% of PDB interfaces. By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB. Additionally, we developed a PyMOL plugin for direct download and easy visualization of EPPIC interfaces for any PDB entry. Both the datasets and the PyMOL plugin are available at http://www.eppic-web.org/ewui/#downloads.

Conclusions

Our computational pipeline allows us to analyze protein–protein contacts and their sequence conservation across the entire PDB. Two new benchmark datasets are provided, which are over an order of magnitude larger than existing manually curated ones. These tools enable the comprehensive study of several aspects of protein–protein contacts in the PDB and represent a basis for future, even larger scale studies of protein–protein interactions.

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

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

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine.

A method for predicting protein-protein interaction types

Protein-protein interactions (PPIs) govern basic cellular processes through signal transduction and complex formation. The diversity of those processes gives rise to a remarkable diversity of interactions types, ranging from transient phosphorylation interactions to stable covalent bonding. Despite our increasing knowledge on PPIs in humans and other species, their types remain relatively unexplored and few annotations of types exist in public databases. Here, we propose the first method for systematic prediction of PPI type based solely on the techniques by which the interaction was detected. We show that different detection methods are better suited for detecting specific types. We apply our method to ten interaction types on a large scale human PPI dataset. We evaluate the performance of the method using both internal cross validation and external data sources. In cross validation, we obtain an area under receiver operating characteristic (ROC) curve ranging from 0.65 to 0.97 with an average of 0.84 across the predicted types. Comparing the predicted interaction types to external data sources, we obtained significant agreements for phosphorylation and ubiquitination interactions, with hypergeometric p-value = 2.3e(-54) and 5.6e(-28) respectively. We examine the biological relevance of our predictions using known signaling pathways and chart the abundance of interaction types in cell processes. Finally, we investigate the cross-relations between different interaction types within the network and characterize the discovered patterns, or motifs. We expect the resulting annotated network to facilitate the reconstruction of process-specific subnetworks and assist in predicting protein function or interaction.

Crystal structure and immunological properties of the first annexin from Schistosoma mansoni: insights into the structural integrity of the schistosomal tegument

Schistosomiasis is a major parasitic disease of humans, second only to malaria in its global impact. The disease is caused by digenean trematodes that infest the vasculature of their human hosts. These flukes are limited externally by a body wall composed of a syncytial epithelium, the apical surface membrane of which is a parasitism-adapted dual membrane complex. Annexins are thought to be of integral importance for the stability of this apical membrane system. Here, we present the first structural and immunobiochemical characterization of an annexin from Schistosoma mansoni. The crystal structure of annexin B22 confirms the presence of the previously predicted α-helical segment in the II/III linker and reveals a covalently linked head-to-head dimer. From the calcium-bound crystal structure of this protein, canonical type II, type III and B site positions are occupied, and a novel binding site has been identified. The dimer arrangement observed in the crystal structure suggests the presence of two prominent features, a potential non-canonical membrane binding site and a potential binding groove opposite to the former. Results from transcriptional profiling during development show that annexin B22 expression is correlated with life stages of the parasite that possess the syncytial tegument layer, and ultrastructural localization by immuno-electron microscopy confirms the occurrence of annexins in the tegument of S. mansoni. Data from membrane binding and aggregation assays indicate the presence of differential molecular mechanisms and support the hypothesis of annexin B22 providing structural integrity in the tegument.

Molecular origins of binding affinity: seeking the Archimedean point

Connecting three dimensional structure and affinity is analogous to seeking the 'Archimedean point', a vantage point from where any observer can quantitatively perceive the subject of inquiry. Here we review current knowledge and challenges that lie ahead of us in the quest for this Archimedean point. We argue that current models are limited in reproducing measured data because molecular description of binding affinity must expand beyond the interfacial contribution and also incorporate effects stemming from conformational changes/dynamics and long-range interactions. Fortunately, explicit modeling of various kinetic schemes underlying biomolecular recognition and confined systems that reflect in vivo interactions are coming within reach. This quest will hopefully lead to an accurate biophysical interpretation of binding affinity that would allow unprecedented understanding of the molecular basis of life through unraveling the why's of interaction networks.

Crystal structure of Mycobacterium tuberculosis polyketide synthase 11 (PKS11) reveals intermediates in the synthesis of methyl-branched alkylpyrones

PKS11 is one of three type III polyketide synthases (PKSs) identified in Mycobacterium tuberculosis. Although many PKSs in M. tuberculosis have been implicated in producing complex cell wall glycolipids, the biological function of PKS11 is unknown. PKS11 has previously been proposed to synthesize alkylpyrones from fatty acid substrates. We solved the crystal structure of M. tuberculosis PKS11 and found the overall fold to be similar to other type III PKSs. PKS11 has a deep hydrophobic tunnel proximal to the active site Cys-138 to accommodate substrates. We observed electron density in this tunnel from a co-purified molecule that was identified by mass spectrometry to be palmitate. Co-crystallization with malonyl-CoA (MCoA) or methylmalonyl-CoA (MMCoA) led to partial turnover of the substrate, resulting in trapped intermediates. Reconstitution of the reaction in solution confirmed that both co-factors are required for optimal activity, and kinetic analysis shows that MMCoA is incorporated first, then MCoA, followed by lactonization to produce methyl-branched alkylpyrones.

Structural basis for dual roles of Aar2p in U5 snRNP assembly

Yeast U5 small nuclear ribonucleoprotein particle (snRNP) is assembled via a cytoplasmic precursor that contains the U5-specific Prp8 protein but lacks the U5-specific Brr2 helicase. Instead, pre-U5 snRNP includes the Aar2 protein not found in mature U5 snRNP or spliceosomes. Aar2p and Brr2p bind competitively to a C-terminal region of Prp8p that comprises consecutive RNase H-like and Jab1/MPN-like domains. To elucidate the molecular basis for this competition, we determined the crystal structure of Aar2p in complex with the Prp8p RNase H and Jab1/MPN domains. Aar2p binds on one side of the RNase H domain and extends its C terminus to the other side, where the Jab1/MPN domain is docked onto a composite Aar2p-RNase H platform. Known Brr2p interaction sites of the Jab1/MPN domain remain available, suggesting that Aar2p-mediated compaction of the Prp8p domains sterically interferes with Brr2p binding. Moreover, Aar2p occupies known RNA-binding sites of the RNase H domain, and Aar2p interferes with binding of U4/U6 di-snRNA to the Prp8p C-terminal region. Structural and functional analyses of phospho-mimetic mutations reveal how phosphorylation reduces affinity of Aar2p for Prp8p and allows Brr2p and U4/U6 binding. Our results show how Aar2p regulates both protein and RNA binding to Prp8p during U5 snRNP assembly.

Domain 1 of mucosal addressin cell adhesion molecule has an I1-set fold and a flexible integrin-binding loop

Mucosal addressin cell adhesion molecule (MAdCAM) binds integrin α4β7. Their interaction directs lymphocyte homing to mucosa-associated lymphoid tissues. The interaction between the two immunoglobulin superfamily (IgSF) domains of MAdCAM and integrin α4β7 is unusual in its ability to mediate either rolling adhesion or firm adhesion of lymphocytes on vascular surfaces. We determined four crystal structures of the IgSF domains of MAdCAM to test for unusual structural features that might correlate with this functional diversity. Higher resolution 1.7- and 1.4-Å structures of the IgSF domains of MAdCAM in a previously described crystal lattice revealed two alternative conformations of the integrin-binding loop, which were deformed by large lattice contacts. New crystal forms in the presence of two different Fabs to MAdCAM demonstrate a shift in IgSF domain topology from the I2- to I1-set, with a switch of integrin-binding loop from CC' to CD. The I1-set fold and CD loop appear biologically relevant. The different conformations seen in crystal structures suggest that the integrin-binding loop of MAdCAM is inherently flexible. This contrasts with rigidity of the corresponding loops in vascular cell adhesion molecule, intercellular adhesion molecule (ICAM)-1, ICAM-2, ICAM-3, and ICAM-5 and may reflect a specialization of MAdCAM to mediate both rolling and firm adhesion by binding to different α4β7 integrin conformations.

Structural, evolutionary, and assembly principles of protein oligomerization

In the protein universe, 30-50% of proteins self-assemble to form symmetrical complexes consisting of multiple copies of themselves, called homomers. The prevalence of homomers motivates us to review many of their properties. In Section 1, we describe the methods and challenges associated with quaternary structure inference-these methods are indeed at the basis of any analysis on homomers. In Section 2, we describe the morphological properties of homomers, as well as the database 3DComplex, which provides a taxonomy for both homomeric and heteromeric protein complexes. In Section 3, we review interface properties of homomeric complexes. In Section 4, we then present recent findings on the evolution of homomer interfaces, which we link in Section 5 to the evolution of homomers as entire entities. In Section 6, we discuss mechanisms involved in their assembly and how these mechanisms can be linked to evolution.

Protein interface classification by evolutionary analysis

Background

Distinguishing biologically relevant interfaces from lattice contacts in protein crystals is a fundamental problem in structural biology. Despite efforts towards the computational prediction of interface character, many issues are still unresolved.

Results

We present here a protein-protein interface classifier that relies on evolutionary data to detect the biological character of interfaces. The classifier uses a simple geometric measure, number of core residues, and two evolutionary indicators based on the sequence entropy of homolog sequences. Both aim at detecting differential selection pressure between interface core and rim or rest of surface. The core residues, defined as fully buried residues (>95% burial), appear to be fundamental determinants of biological interfaces: their number is in itself a powerful discriminator of interface character and together with the evolutionary measures it is able to clearly distinguish evolved biological contacts from crystal ones. We demonstrate that this definition of core residues leads to distinctively better results than earlier definitions from the literature. The stringent selection and quality filtering of structural and sequence data was key to the success of the method. Most importantly we demonstrate that a more conservative selection of homolog sequences - with relatively high sequence identities to the query - is able to produce a clearer signal than previous attempts.

Conclusions

An evolutionary approach like the one presented here is key to the advancement of the field, which so far was missing an effective method exploiting the evolutionary character of protein interfaces. Its coverage and performance will only improve over time thanks to the incessant growth of sequence databases. Currently our method reaches an accuracy of 89% in classifying interfaces of the Ponstingl 2003 datasets and it lends itself to a variety of useful applications in structural biology and bioinformatics. We made the corresponding software implementation available to the community as an easy-to-use graphical web interface at http://www.eppic-web.org.

Crystal structure of the glutamate receptor GluA1 N-terminal domain

The AMPA (α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid) subfamily of iGluRs (ionotropic glutamate receptors) is essential for fast excitatory neurotransmission in the central nervous system. The malfunction of AMPARs (AMPA receptors) has been implicated in many neurological diseases, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. The active channels of AMPARs and other iGluR subfamilies are tetramers formed exclusively by assembly of subunits within the same subfamily. It has been proposed that the assembly process is controlled mainly by the extracellular ATD (N-terminal domain) of iGluR. In addition, ATD has also been implicated in synaptogenesis, iGluR trafficking and trans-synaptic signalling, through unknown mechanisms. We report in the present study a 2.5 Å (1 Å=0.1 nm) resolution crystal structure of the ATD of GluA1. Comparative analyses of the structure of GluA1-ATD and other subunits sheds light on our understanding of how ATD drives subfamily-specific assembly of AMPARs. In addition, analysis of the crystal lattice of GluA1-ATD suggests a novel mechanism by which the ATD might participate in inter-tetramer AMPAR clustering, as well as in trans-synaptic protein-protein interactions.

Insights into the membrane interactions of the saposin-like proteins Na-SLP-1 and Ac-SLP-1 from human and dog hookworm

Saposin-like proteins (SAPLIPs) from soil-transmitted helminths play pivotal roles in host-pathogen interactions and have a high potential as targets for vaccination against parasitic diseases. We have identified two non-orthologous SAPLIPs from human and dog hookworm, Na-SLP-1 and Ac-SLP-1, and solved their three-dimensional crystal structures. Both proteins share the property of membrane binding as monitored by liposome co-pelleting assays and monolayer adsorption. Neither SAPLIP displayed any significant haemolytic or bactericidal activity. Based on the structural information, as well as the results from monolayer adsorption, we propose models of membrane interactions for both SAPLIPs. Initial membrane contact of the monomeric Na-SLP-1 is most likely by electrostatic interactions between the membrane surface and a prominent basic surface patch. In case of the dimeric Ac-SLP-1, membrane interactions are most likely initiated by a unique tryptophan residue that has previously been implicated in membrane interactions in other SAPLIPs.

HIV-1 Tat: Its Dependence on Host Factors is Crystal Clear

HIV-1 transcription is regulated at the level of elongation by the viral Tat protein together with the cellular elongation factor P-TEFb, which is composed of cyclin T1 and Cdk9 subunits. The crystal structure of a Tat:P-TEFb complex (Tahirov, T.H.; Babayeva, N.D.; Varzavand, K.; Cooper, J.J.; Sedore, S.C.; and Price, D.H. Crystal structure of HIV-1 Tat complexed with human P-TEFb. Nature2010, 465, 747–751.) reveals molecular details of Tat and its interactions that have eluded investigators for more than two decades and provides provocative insights into the mechanism of Tat activation.