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AAA+ ATPases constitute a large family of proteins that are involved in a plethora of cellular processes including DNA disassembly, protein degradation and protein complex disassembly. They typically form a hexametric ring-shaped structure with six subunits in a (pseudo) 6-fold symmetry. In a subset of AAA+ ATPases that facilitate protein unfolding and degradation, six subunits cooperate to translocate protein substrates through a central pore in the ring. The number and type of nucleotides in an AAA+ ATPase hexamer is inherently linked to the mechanism that underlies cooperation among subunits and couples ATP hydrolysis with substrate translocation. We conducted a native MS study of a monodispersed form of PAN, an archaeal proteasome AAA+ ATPase, to determine the number of nucleotides bound to each hexamer of the WT protein. We utilized ADP and its analogs (TNP-ADP and mant-ADP), and a nonhydrolyzable ATP analog (AMP-PNP) to study nucleotide site occupancy within the PAN hexamer in ADP- and ATP-binding states, respectively. Throughout all experiments we used a Walker A mutant (PANK217A) that is impaired in nucleotide binding as an internal standard to mitigate the effects of residual solvation on mass measurement accuracy and to serve as a reference protein to control for nonspecific nucleotide binding. This approach led to the unambiguous finding that a WT PAN hexamer carried - from expression host - six tightly bound ADP molecules that could be exchanged for ADP and ATP analogs. Although the Walker A mutant did not bind ADP analogs, it did bind AMP-PNP, albeit at multiple stoichiometries. We observed variable levels of hexamer dissociation and an appearance of multimeric species with the over-charged molecular ion distributions across repeated experiments. We posit that these phenomena originated during ESI process at the final stages of ESI droplet evolution.

Amide hydrogen-deuterium exchange mass spectrometry (HDX-MS) has become widely popular for mapping protein-ligand interfaces, for understanding protein-protein interactions, and for discovering dynamic allostery. Several platforms are now available which provide large data sets of amide hydrogen/deuterium exchange mass spectrometry (HDX-MS) data. Although many of these platforms provide some down-stream processing, a comprehensive software that provides the most commonly used down-stream processing tools such as automatic back-exchange correction options, analysis of overlapping peptides, calculations of relative deuterium uptake into regions of the protein after such corrections, rigorous statistical analysis of the significance of uptake differences, and generation of high quality figures for data presentation is not yet available. Here we describe the Deuterium Exchange Correction and Analysis (DECA) software package, which provides all these downstream processing options for data from the most popular mass spectrometry platforms. The major functions of the software are demonstrated on sample data.

Adenoviruses are non-enveloped icosahedral viruses with trimeric fibre proteins protruding from their vertices. There are five known genera, from which only Mastadenoviruses have been widely studied. Apart from studying adenovirus as a biological model system and with a view to prevent or combat viral infection, there is a major interest in using adenovirus for vaccination, cancer therapy and gene therapy purposes. Adenoviruses from the Atadenovirus genus have been isolated from squamate reptile hosts, ruminants and birds and have a characteristic gene organization and capsid morphology. The carboxy-terminal virus-distal fibre head domains are likely responsible for primary receptor recognition. We determined the high-resolution crystal structure of the Snake Adenovirus 1 (SnAdV-1) fibre head using the multi-wavelength anomalous dispersion (MAD) method. Despite the absence of significant sequence homology, this Atadenovirus fibre head has the same beta-sandwich propeller topology as other adenovirus fibre heads. However, it is about half the size, mainly due to much shorter loops connecting the beta-strands. The detailed structure of the SnAdV-1 fibre head and other animal adenovirus fibre heads, together with the future identification of their natural receptors, may lead to the development of new strategies to target adenovirus vectors to cells of interest. [ABSTRACT FROM AUTHOR]

The A. thaliana genome encodes five co-chaperonin homologs, three of which are destined to the chloroplast. Two of the proteins, Cpn10(2) and Cpn20, form functional homo-oligomers in vitro. In the current work, we present data on the structure and function of the third A. thaliana co-chaperonin, which exhibits unique properties. We found that purified recombinant Cpn10(1) forms inactive dimers in solution, in contrast to the active heptamers that are formed by canonical Cpn10s. Additionally, our data demonstrate that Cpn10(1) is capable of assembling into active hetero-oligomers together with Cpn20. This finding was reinforced by the formation of active co-chaperonin species upon mixing an inactive Cpn20 mutant with the inactive Cpn10(1). The present study constitutes the first report of a higher plant Cpn10 subunit that is able to function only upon formation of hetero-oligomers with other co-chaperonins. [ABSTRACT FROM AUTHOR]

The HIV-1 capsid is involved in all infectious steps from reverse transcription to integration site selection, and is the target of multiple host cell and pharmacologic ligands. However, structural studies have been limited to capsid monomers (CA), and the mechanistic basis for how these ligands influence infection is not well understood. Here we show that a multi-subunit interface formed exclusively within CA hexamers mediates binding to linear epitopes within cellular cofactors NUP153 and CPSF6, and is competed for by the antiretroviral compounds PF74 and BI-2. Each ligand is anchored via a shared phenylalanine-glycine (FG) motif to a pocket within the N-terminal domain of one monomer, and all but BI-2 also make essential interactions across the N-terminal domain: C-terminal domain (NTD:CTD) interface to a second monomer. Dissociation of hexamer into CA monomers prevents high affinity interaction with CPSF6 and PF74, and abolishes binding to NUP153. The second interface is conformationally dynamic, but binding of NUP153 or CPSF6 peptides is accommodated by only one conformation. NUP153 and CPSF6 have overlapping binding sites, but each makes unique CA interactions that, when mutated selectively, perturb cofactor dependency. These results reveal that multiple ligands share an overlapping interface in HIV-1 capsid that is lost upon viral disassembly. [ABSTRACT FROM AUTHOR]

Enteroaggregative Escherichia coli (EAEC) is a leading cause of acute and persistent diarrhea worldwide. A recently emerged Shiga-toxin-producing strain of EAEC resulted in significant mortality and morbidity due to progressive development of hemolytic-uremic syndrome. The attachment of EAEC to the human intestinal mucosa is mediated by aggregative adherence fimbria (AAF). Using X-ray crystallography and NMR structures, we present new atomic resolution insight into the structure of AAF variant I from the strain that caused the deadly outbreak in Germany in 2011, and AAF variant II from archetype strain 042, and propose a mechanism for AAF-mediated adhesion and biofilm formation. Our work shows that major subunits of AAF assemble into linear polymers by donor strand complementation where a single minor subunit is inserted at the tip of the polymer by accepting the donor strand from the terminal major subunit. Whereas the minor subunits of AAF have a distinct conserved structure, AAF major subunits display large structural differences, affecting the overall pilus architecture. These structures suggest a mechanism for AAF-mediated adhesion and biofilm formation. Binding experiments using wild type and mutant subunits (NMR and SPR) and bacteria (ELISA) revealed that despite the structural differences AAF recognize a common receptor, fibronectin, by employing clusters of basic residues at the junction between subunits in the pilus. We show that AAF-fibronectin attachment is based primarily on electrostatic interactions, a mechanism not reported previously for bacterial adhesion to biotic surfaces. [ABSTRACT FROM AUTHOR]

Kanadaptin is a nuclear protein of unknown function that is widely expressed in mammalian tissues. The crystal structure of the forkhead-associated (FHA) domain of human kanadaptin was determined to 1.6 Å resolution. The structure reveals an asymmetric dimer in which one monomer is complexed with a phosphopeptide mimic derived from a peptide segment from the N-terminus of a symmetry-related molecule as well as a sulfate bound to the structurally conserved phosphothreonine recognition cleft. This structure provides insights into the molecular recognition features utilized by this family of proteins and represents the first evidence that kanadaptin is likely involved in a phosphorylation-mediated signaling pathway. These results will be of use for designing experiments to further probe the function of kanadaptin. [ABSTRACT FROM AUTHOR]

Actin stress fibers (SFs) detect and transmit forces to the extracellular matrix through focal adhesions (FAs), and molecules in this pathway determine cellular behavior. Here, we designed two different computational tools to quantify actin SFs and the distribution of actin cytoskeletal proteins within a normalized cellular morphology. Moreover, a systematic cell response comparison between the control cells and those with impaired actin cytoskeleton polymerization was performed to demonstrate the reliability of the tools. Indeed, a variety of proteins that were present within the string beginning at the focal adhesions (vinculin) up to the actin SFs contraction (non-muscle myosin II (NMMII)) were analyzed. Finally, the software used allows for the quantification of the SFs based on the relative positions of FAs. Therefore, it provides a better insight into the cell mechanics and broadens the knowledge of the nature of SFs. [ABSTRACT FROM AUTHOR]

Protein-RNA complexes provide a wide range of essential functions in the cell. Their atomic experimental structure solving, despite essential to the understanding of these functions, is often difficult and expensive. Docking approaches that have been developed for proteins are often challenging to adapt for RNA because of its inherent flexibility and the structural data available being relatively scarce. In this study we adapted the RosettaDock protocol for protein-RNA complexes both at the nucleotide and atomic levels. Using a genetic algorithm-based strategy, and a non-redundant protein-RNA dataset, we derived a RosettaDock scoring scheme able not only to discriminate but also score efficiently docking decoys. The approach proved to be both efficient and robust for generating and identifying suitable structures when applied to two protein-RNA docking benchmarks in both bound and unbound settings. It also compares well to existing strategies. This is the first approach that currently offers a multi-level optimized scoring approach integrated in a full docking suite, leading the way to adaptive fully flexible strategies. [ABSTRACT FROM AUTHOR]

Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins. [ABSTRACT FROM AUTHOR]

Box C/D ribonucleoprotein particles (RNPs) are 2′-O-methylation enzymes required for maturation of ribosomal and small nuclear RNA. Previous biochemical and structural studies of the box C/D RNPs were limited by the unavailability of purified intact RNPs. We developed a bacterial co-expression strategy based on the combined use of a multi-gene expression system and a tRNA-scaffold construct that allowed the expression and purification of homogeneous archaeal and human box C/D RNPs. While the co-expressed and co-purified archaeal box C/D RNP was found to be fully active in a 2′-O-methylation assay, the intact human U14 box C/D RNP showed no detectable catalytic activity, consistent with the earlier findings that assembly of eukaryotic box C/D RNPs is nonspontaneous and requires additional protein factors. Our systems provide a means for further biochemical and structural characterization of box C/D RNPs and their assembly factors. [ABSTRACT FROM AUTHOR]

The expanding roles of PCNA in functional assembly of DNA replication and repair complexes motivated investigation of the structural and dynamic properties guiding specificity of PCNA-protein interactions. A series of biochemical and computational analyses were combined to evaluate the PIP Box recognition features impacting complex formation. The results indicate subtle differences in topological and molecular descriptors distinguishing both affinity and stoichiometry of binding among PCNA-peptide complexes through cooperative effects. These features were validated using peptide mimics of p85α and Akt, two previously unreported PCNA binding partners. This study characterizes for the first time a reverse PIP Box interaction with PCNA. Small molecule ligand binding at the PIP Box interaction site confirmed the adaptive nature of the protein in dictating overall shape and implicates allosterism in transmitting biological effects. [ABSTRACT FROM AUTHOR]

To understand the mechanism of reverse tRNA translocation in the ribosome, all-atom molecular dynamics simulations of the ribosome-tRNAs-mRNA-EFG complex were performed. The complex at the post-translocational state was directed towards the translocational and pre-translocational states by fitting the complex into cryo-EM density maps. Between a series of the fitting simulations, umbrella sampling simulations were performed to obtain the free-energy landscape. Multistep structural changes, such as a ratchet-like motion and rotation of the head of the small subunit were observed. The free-energy landscape showed that there were two main free-energy barriers: one between the post-translocational and intermediate states, and the other between the pre-translocational and intermediate states. The former corresponded to a clockwise rotation, which was coupled to the movement of P-tRNA over the P/E-gate made of G1338, A1339 and A790 in the small subunit. The latter corresponded to an anticlockwise rotation of the head, which was coupled to the location of the two tRNAs in the hybrid state. This indicates that the coupled motion of the head rotation and tRNA translocation plays an important role in opening and closing of the P/E-gate during the ratchet-like movement in the ribosome. Conformational change of EF-G was interpreted to be the result of the combination of the external motion by L12 around an axis passing near the sarcin-ricin loop, and internal hinge-bending motion. These motions contributed to the movement of domain IV of EF-G to maintain its interaction with A/P-tRNA. [ABSTRACT FROM AUTHOR]

Protein Phosphatase 2A (PP2A) is a major Ser/Thr phosphatase involved in the regulation of various cellular processes. PP2A assembles into diverse trimeric holoenzymes, which consist of a scaffolding (A) subunit, a catalytic (C) subunit and various regulatory (B) subunits. Here we report a 2.0 Å crystal structure of the free B’’/PR70 subunit and a SAXS model of an A/PR70 complex. The crystal structure of B’’/PR70 reveals a two domain elongated structure with two Ca2+ binding EF-hands. Furthermore, we have characterized the interaction of both binding partner and their calcium dependency using biophysical techniques. Ca2+ biophysical studies with Circular Dichroism showed that the two EF-hands display different affinities to Ca2+. In the absence of the catalytic C-subunit, the scaffolding A-subunit remains highly mobile and flexible even in the presence of the B’’/PR70 subunit as judged by SAXS. Isothermal Titration Calorimetry studies and SAXS data support that PR70 and the A-subunit have high affinity to each other. This study provides additional knowledge about the structural basis for the function of B’’ containing holoenzymes. [ABSTRACT FROM AUTHOR]

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. [ABSTRACT FROM AUTHOR]

Organizing experimentally determined protein associations as a hierarchy can be a good approach to elucidating the content of protein complexes and the modularity of subcomplexes. Several challenges exist. First, intrinsically sticky proteins, such as chaperones, are often falsely assigned to many functionally unrelated complexes. Second, the reported collections of proteins may not be true “complexes” in the sense that they bind together and perform a joint cellular function. Third, due to imperfect sensitivity of protein detection methods, both false positive and false negative assignments of a protein to complexes may occur. We mitigate the first issue by down-weighting sticky proteins by their occurrence frequencies. We approach the other two problems by merging nearly identical complexes and by constructing a directed acyclic graph (DAG) based on the relationship of partial inclusion. The constructed DAG, within which smaller complexes form parts of the larger, can reveal how different complexes are joined. By merging almost identical complexes one can deemphasize the influence of false positives, while allowing false negatives to be rescued by other nearly identical association data. We investigate several protein weighting schemes and compare their corresponding DAGs using yeast and human complexes. We find that the scheme incorporating weights based on information flow in the network of direct protein–protein interactions produces biologically most meaningful DAGs. In either yeast or human, isolated nodes form a large proportion of the final hierarchy. While most connected components encompass very few nodes, the largest one for each species contains a sizable portion of all nodes. By considering examples of subgraphs composed of nodes containing a specified protein, we illustrate that the graphs' topological features can correctly suggest the biological roles of protein complexes. The input data, final results and the source code are available at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbpmn/ProteinComplexDAG/. [ABSTRACT FROM AUTHOR]

The APOBEC3 family of DNA cytosine deaminases functions to block the spread of endogenous retroelements and retroviruses including HIV-1. Potency varies among family members depending on the type of parasitic substrate. APOBEC3A (A3A) is unique among the human enzymes in that it is expressed predominantly in myeloid lineage cell types, it is strongly induced by innate immune agonists such as type 1 interferon, and it has the capacity to accommodate both normal and 5-methyl cytosine nucleobases. Here we apply atomic force microscopy (AFM) to characterize the interaction between A3A and single- and double-stranded DNA using a hybrid DNA approach in which a single-stranded region is flanked by defined length duplexes. AFM image analyses reveal A3A binding to single-stranded DNA, and that this interaction becomes most evident (∼80% complex yield) at high protein-to-DNA ratios (at least 100∶1). A3A is predominantly monomeric when bound to single-stranded DNA, and it is also monomeric in solution at concentrations as high as 50 nM. These properties agree well with recent, biochemical, biophysical, and structural studies. However, these characteristics contrast with those of the related enzyme APOBEC3G, which in similar assays can exist as a monomer but tends to form oligomers in a concentration-dependent manner. These AFM data indicate that A3A has intrinsic biophysical differences that distinguish it from APOBEC3G. The potential relationships between these properties and biological functions in innate immunity are discussed. [ABSTRACT FROM AUTHOR]

The protein Keap1 is central to the regulation of the Nrf2-mediated cytoprotective response, and is increasingly recognized as an important target for therapeutic intervention in a range of diseases involving excessive oxidative stress and inflammation. The BTB domain of Keap1 plays key roles in sensing environmental electrophiles and in mediating interactions with the Cul3/Rbx1 E3 ubiquitin ligase system, and is believed to be the target for several small molecule covalent activators of the Nrf2 pathway. However, despite structural information being available for several BTB domains from related proteins, there have been no reported crystal structures of Keap1 BTB, and this has precluded a detailed understanding of its mechanism of action and interaction with antagonists. We report here the first structure of the BTB domain of Keap1, which is thought to contain the key cysteine residue responsible for interaction with electrophiles, as well as structures of the covalent complex with the antagonist CDDO/bardoxolone, and of the constitutively inactive C151W BTB mutant. In addition to providing the first structural confirmation of antagonist binding to Keap1 BTB, we also present biochemical evidence that adduction of Cys 151 by CDDO is capable of inhibiting the binding of Cul3 to Keap1, and discuss how this class of compound might exert Nrf2 activation through disruption of the BTB-Cul3 interface. [ABSTRACT FROM AUTHOR]

Macromolecular crowding within the cell can impact both protein folding and binding. Earlier models of cellular crowding focused on the excluded volume, entropic effect of crowding agents, which generally favors compact protein states. Recently, other effects of crowding have been explored, including enthalpically-related crowder–protein interactions and changes in solvation properties. In this work, we explore the effects of macromolecular crowding on the electrostatic desolvation and solvent-screened interaction components of protein–protein binding. Our simple model enables us to focus exclusively on the electrostatic effects of water depletion on protein binding due to crowding, providing us with the ability to systematically analyze and quantify these potentially intuitive effects. We use the barnase–barstar complex as a model system and randomly placed, uncharged spheres within implicit solvent to model crowding in an aqueous environment. On average, we find that the desolvation free energy penalties incurred by partners upon binding are lowered in a crowded environment and solvent-screened interactions are amplified. At a constant crowder density (fraction of total available volume occupied by crowders), this effect generally increases as the radius of model crowders decreases, but the strength and nature of this trend can depend on the water probe radius used to generate the molecular surface in the continuum model. In general, there is huge variation in desolvation penalties as a function of the random crowder positions. Results with explicit model crowders can be qualitatively similar to those using a lowered “effective” solvent dielectric to account for crowding, although the “best” effective dielectric constant will likely depend on multiple system properties. Taken together, this work systematically demonstrates, quantifies, and analyzes qualitative intuition-based insights into the effects of water depletion due to crowding on the electrostatic component of protein binding, and it provides an initial framework for future analyses. [ABSTRACT FROM AUTHOR]

Many if not most proteins function in oligomeric assemblies of one or more protein sequences. The Protein Data Bank provides coordinates for biological assemblies for each entry, at least 60% of which are dimers or larger assemblies. BioAssemblyModeler (BAM) is a graphical user interface to the basic steps in homology modeling of protein homooligomers and heterooligomers from the biological assemblies provided in the PDB. BAM takes as input up to six different protein sequences and begins by assigning Pfam domains to the target sequences. The program utilizes a complete assignment of Pfam domains to sequences in the PDB, PDBfam (http://dunbrack2.fccc.edu/protcid/pdbfam), to obtain templates that contain any or all of the domains assigned to the target sequence(s). The contents of the biological assemblies of potential templates are provided, and alignments of the target sequences to the templates are produced with a profile-profile alignment algorithm. BAM provides for visual examination and mouse-editing of the alignments supported by target and template secondary structure information and a 3D viewer of the template biological assembly. Side-chain coordinates for a model of the biological assembly are built with the program SCWRL4. A built-in protocol navigation system guides the user through all stages of homology modeling from input sequences to a three-dimensional model of the target complex. Availability: http://dunbrack.fccc.edu/BAM. [ABSTRACT FROM AUTHOR]

The high concentration of macromolecules in the crowded cellular interior influences different thermodynamic and kinetic properties of proteins, including their structural stabilities, intermolecular binding affinities and enzymatic rates. Moreover, various structural biology methods, such as NMR or different spectroscopies, typically involve samples with relatively high protein concentration. Due to large sampling requirements, however, the accuracy of classical molecular dynamics (MD) simulations in capturing protein behavior at high concentration still remains largely untested. Here, we use explicit-solvent MD simulations and a total of 6.4 µs of simulated time to study wild-type (folded) and oxidatively damaged (unfolded) forms of villin headpiece at 6 mM and 9.2 mM protein concentration. We first perform an exhaustive set of simulations with multiple protein molecules in the simulation box using GROMOS 45a3 and 54a7 force fields together with different types of electrostatics treatment and solution ionic strengths. Surprisingly, the two villin headpiece variants exhibit similar aggregation behavior, despite the fact that their estimated aggregation propensities markedly differ. Importantly, regardless of the simulation protocol applied, wild-type villin headpiece consistently aggregates even under conditions at which it is experimentally known to be soluble. We demonstrate that aggregation is accompanied by a large decrease in the total potential energy, with not only hydrophobic, but also polar residues and backbone contributing substantially. The same effect is directly observed for two other major atomistic force fields (AMBER99SB-ILDN and CHARMM22-CMAP) as well as indirectly shown for additional two (AMBER94, OPLS-AAL), and is possibly due to a general overestimation of the potential energy of protein-protein interactions at the expense of water-water and water-protein interactions. Overall, our results suggest that current MD force fields may distort the picture of protein behavior in biologically relevant crowded environments. [ABSTRACT FROM AUTHOR]

Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs), from Functionally uncorrelated Contacts (FunCs), is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations. [ABSTRACT FROM AUTHOR]

: The flexibility of individual proteins aids their evolutionary recruitment into complexes with increasing numbers of distinct subunits. [ABSTRACT FROM AUTHOR]

Altogether few protein oligomers undergo a conformational transition to a state that impairs their function and leads to diseases. But when it happens, the consequences are not harmless and the so-called conformational diseases pose serious public health problems. Notorious examples are the Alzheimer's disease and some cancers associated with a conformational change of the amyloid precursor protein (APP) and of the p53 tumor suppressor, respectively. The transition is linked with the propensity of β-strands to aggregate into amyloid fibers. Nevertheless, a huge number of protein oligomers associate chains via β-strand interactions (intermolecular β-strand interface) without ever evolving into fibers. We analyzed the layout of 1048 intermolecular β-strand interfaces looking for features that could provide the β-strands resistance to conformational transitions. The interfaces were reconstructed as networks with the residues as the nodes and the interactions between residues as the links. The networks followed an exponential decay degree distribution, implying an absence of hubs and nodes with few links. Such layout provides robustness to changes. Few links per nodes do not restrict the choices of amino acids capable of making an interface and maintain high sequence plasticity. Few links reduce the “bonding” cost of making an interface. Finally, few links moderate the vulnerability to amino acid mutation because it entails limited communication between the nodes. This confines the effects of a mutation to few residues instead of propagating them to many residues via hubs. We propose that intermolecular β-strand interfaces are organized in networks that tolerate amino acid mutation to avoid chain dissociation, the first step towards fiber formation. This is tested by looking at the intermolecular β-strand network of the p53 tetramer. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphisms (SNPs) are a major contributor to genetic and phenotypic variation within populations. Non-synonymous SNPs (nsSNPs) modify the sequence of proteins and can affect their folding or binding properties. Experimental analysis of all nsSNPs is currently unfeasible and therefore computational predictions of the molecular effect of nsSNPs are helpful to guide experimental investigations. While some nsSNPs can be accurately characterized, for instance if they fall into strongly conserved or well annotated regions, the molecular consequences of many others are more challenging to predict. In particular, nsSNPs affecting less structured, and often less conserved regions, are difficult to characterize. Binding sites that mediate protein-protein or other protein interactions are an important class of functional sites on proteins and can be used to help interpret nsSNPs. Binding sites targeted by the PDZ modular peptide recognition domain have recently been characterized. Here we use this data to show that it is possible to computationally identify nsSNPs in PDZ binding motifs that modify or prevent binding to the proteins containing the motifs. We confirm these predictions by experimentally validating a selected subset with ELISA. Our work also highlights the importance of better characterizing linear motifs in proteins as many of these can be affected by genetic variations. [ABSTRACT FROM AUTHOR]

Multispecific proteins play a major role in controlling various functions such as signaling, regulation of transcription/translation, and immune response. Hence, a thorough understanding of the atomic-level principles governing multispecific interactions is important not only for the advancement of basic science but also for applied research such as drug design. Here, we study evolution of an exemplary multispecific protein, a Tissue Inhibitor of Matrix Metalloproteinases 2 (TIMP2) that binds with comparable affinities to more than twenty-six members of the Matrix Metalloproteinase (MMP) and the related ADAMs families. We postulate that due to its multispecific nature, TIMP2 is not optimized to bind to any individual MMP type, but rather embodies a compromise required for interactions with all MMPs. To explore this hypothesis, we perform computational saturation mutagenesis of the TIMP2 binding interface and predict changes in free energy of binding to eight MMP targets. Computational results reveal the non-optimality of the TIMP2 binding interface for all studied proteins, identifying many affinity-enhancing mutations at multiple positions. Several TIMP2 point mutants predicted to enhance binding affinity and/or binding specificity towards MMP14 were selected for experimental verification. Experimental results show high abundance of affinity-enhancing mutations in TIMP2, with some point mutations producing more than ten-fold improvement in affinity to MMP14. Our computational and experimental results collaboratively demonstrate that the TIMP2 sequence lies far from the fitness maximum when interacting with its target enzymes. This non-optimality of the binding interface and high potential for improvement might characterize all proteins evolved for binding to multiple targets. [ABSTRACT FROM AUTHOR]

One of the many factors involved in determining the distribution and metabolism of a compound is the strength of its binding to human serum albumin. While experimental and QSAR approaches for determining binding to albumin exist, various factors limit their ability to provide accurate binding affinity for novel compounds. Thus, to complement the existing tools, we have developed a structure-based model of serum albumin binding. Our approach for predicting binding incorporated the inherent flexibility and promiscuity known to exist for albumin. We found that a weighted combination of the predicted logP and docking score most accurately distinguished between binders and nonbinders. This model was successfully used to predict serum albumin binding in a large test set of therapeutics that had experimental binding data. [ABSTRACT FROM AUTHOR]

Population structure is known to cause false-positive detection in association studies. We compared the power, precision, and type-I error rates of various association models in analyses of a simulated dataset with structure at the population (admixture from two populations; P) and family (K) levels. We also compared type-I error rates among models in analyses of publicly available human and dog datasets. The models corrected for none, one, or both structure levels. Correction for K was performed with linear mixed models incorporating familial relationships estimated from pedigrees or genetic markers. Linear models that ignored K were also tested. Correction for P was performed using principal component or structured association analysis. In analyses of simulated and real data, linear mixed models that corrected for K were able to control for type-I error, regardless of whether they also corrected for P. In contrast, correction for P alone in linear models was insufficient. The power and precision of linear mixed models with and without correction for P were similar. Furthermore, power, precision, and type-I error rate were comparable in linear mixed models incorporating pedigree and genomic relationships. In summary, in association studies using samples with both P and K, ancestries estimated using principal components or structured assignment were not sufficient to correct type-I errors. In such cases type-I errors may be controlled by use of linear mixed models with relationships derived from either pedigree or from genetic markers. [ABSTRACT FROM AUTHOR]

Molecular phylogenetics and phylogenomics are subject to noise from horizontal gene transfer (HGT) and bias from convergence in macromolecular compositions. Extensive variation in size, structure and base composition of alphaproteobacterial genomes has complicated their phylogenomics, sparking controversy over the origins and closest relatives of the SAR11 strains. SAR11 are highly abundant, cosmopolitan aquatic Alphaproteobacteria with streamlined, A+T-biased genomes. A dominant view holds that SAR11 are monophyletic and related to both Rickettsiales and the ancestor of mitochondria. Other studies dispute this, finding evidence of a polyphyletic origin of SAR11 with most strains distantly related to Rickettsiales. Although careful evolutionary modeling can reduce bias and noise in phylogenomic inference, entirely different approaches may be useful to extract robust phylogenetic signals from genomes. Here we develop simple phyloclassifiers from bioinformatically derived tRNA Class-Informative Features (CIFs), features predicted to target tRNAs for specific interactions within the tRNA interaction network. Our tRNA CIF-based model robustly and accurately classifies alphaproteobacterial genomes into one of seven undisputed monophyletic orders or families, despite great variability in tRNA gene complement sizes and base compositions. Our model robustly rejects monophyly of SAR11, classifying all but one strain as Rhizobiales with strong statistical support. Yet remarkably, conventional phylogenetic analysis of tRNAs classifies all SAR11 strains identically as Rickettsiales. We attribute this discrepancy to convergence of SAR11 and Rickettsiales tRNA base compositions. Thus, tRNA CIFs appear more robust to compositional convergence than tRNA sequences generally. Our results suggest that tRNA-CIF-based phyloclassification is robust to HGT of components of the tRNA interaction network, such as aminoacyl-tRNA synthetases. We explain why tRNAs are especially advantageous for prediction of traits governing macromolecular interactions from genomic data, and why such traits may be advantageous in the search for robust signals to address difficult problems in classification and phylogeny. [ABSTRACT FROM AUTHOR]

The relative promiscuity of hub proteins such as postsynaptic density protein-95 (PSD-95) can be achieved by alternative splicing, allosteric regulation, and post-translational modifications, the latter of which is the most efficient method of accelerating cellular responses to environmental changes in vivo. Here, a mutational approach was used to determine the impact of phosphorylation and succinimidation post-translational modifications on the binding affinity of the postsynaptic density protein-95/discs large/zonula occludens-1 (PDZ3) domain of PSD-95. Molecular dynamics simulations revealed that the binding affinity of this domain is influenced by an interplay between salt-bridges linking the α3 helix, the β2–β3 loop and the positively charged Lys residues in its high-affinity hexapeptide ligand KKETAV. The α3 helix is an extra structural element that is not present in other PDZ domains, which links PDZ3 with the following SH3 domain in the PSD-95 protein. This regulatory mechanism was confirmed experimentally via thermodynamic and NMR chemical shift perturbation analyses, discarding intra-domain long-range effects. Taken together, the results presented here reveal the molecular basis of the regulatory role of the α3 extra-element and the effects of post-translational modifications of PDZ3 on its binding affinity, both energetically and dynamically. [ABSTRACT FROM AUTHOR]

The distance-dependent knowledge-based DrugScorePPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking “unbound perturbation” (“unbound docking”) decoys generated by Baker and coworkers a 4-fold (1.5-fold) enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScorePPI/FRODOCK finds up to 10% (15%) more high accuracy solutions in the top 1 (top 10) predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼2-fold to 18% (58%) for an at least acceptable solution in the top 10 (top 100) predictions when performing knowledge-driven unbound docking. This suggests that DrugScorePPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScorePPI/FRODOCK will be successful. [ABSTRACT FROM AUTHOR]

In Archaea the two major modes of DNA packaging are wrapping by histone proteins or bending by architectural non-histone proteins. To supplement our knowledge about the binding mode of the different DNA-bending proteins observed across the three domains of life, we present here the first model of a complex in which the monomeric Methanogen Chromosomal protein 1 (MC1) from Euryarchaea binds to the concave side of a strongly bent DNA. In laboratory growth conditions MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55. Like most proteins that strongly bend DNA, MC1 is known to bind in the minor groove. Interaction areas for MC1 and DNA were mapped by Nuclear Magnetic Resonance (NMR) data. The polarity of protein binding was determined using paramagnetic probes attached to the DNA. The first structural model of the DNA-MC1 complex we propose here was obtained by two complementary docking approaches and is in good agreement with the experimental data previously provided by electron microscopy and biochemistry. Residues essential to DNA-binding and -bending were highlighted and confirmed by site-directed mutagenesis. It was found that the Arg25 side-chain was essential to neutralize the negative charge of two phosphates that come very close in response to a dramatic curvature of the DNA. [ABSTRACT FROM AUTHOR]

In Archaea the two major modes of DNA packaging are wrapping by histone proteins or bending by architectural non-histone proteins. To supplement our knowledge about the binding mode of the different DNA-bending proteins observed across the three domains of life, we present here the first model of a complex in which the monomeric Methanogen Chromosomal protein 1 (MC1) from Euryarchaea binds to the concave side of a strongly bent DNA. In laboratory growth conditions MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55. Like most proteins that strongly bend DNA, MC1 is known to bind in the minor groove. Interaction areas for MC1 and DNA were mapped by Nuclear Magnetic Resonance (NMR) data. The polarity of protein binding was determined using paramagnetic probes attached to the DNA. The first structural model of the DNA-MC1 complex we propose here was obtained by two complementary docking approaches and is in good agreement with the experimental data previously provided by electron microscopy and biochemistry. Residues essential to DNA-binding and -bending were highlighted and confirmed by site-directed mutagenesis. It was found that the Arg25 side-chain was essential to neutralize the negative charge of two phosphates that come very close in response to a dramatic curvature of the DNA. [ABSTRACT FROM AUTHOR]

The Human Immunodeficiency Virus type 1 protease enzyme (HIV-1 PR) is one of the most important targets of antiretroviral therapy used in the treatment of AIDS patients. The success of protease-inhibitors (PIs), however, is often limited by the emergence of protease mutations that can confer resistance to a specific drug, or even to multiple PIs. In the present study, we used bioinformatics tools to evaluate the impact of the unusual mutations D30V and V32E over the dynamics of the PR-Nelfinavir complex, considering that codons involved in these mutations were previously related to major drug resistance to Nelfinavir. Both studied mutations presented structural features that indicate resistance to Nelfinavir, each one with a different impact over the interaction with the drug. The D30V mutation triggered a subtle change in the PR structure, which was also observed for the well-known Nelfinavir resistance mutation D30N, while the V32E exchange presented a much more dramatic impact over the PR flap dynamics. Moreover, our in silico approach was also able to describe different binding modes of the drug when bound to different proteases, identifying specific features of HIV-1 subtype B and subtype C proteases. [ABSTRACT FROM AUTHOR]

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html). [ABSTRACT FROM AUTHOR]

Aptamers are oligonucleic acid or peptide molecules that bind to specific target molecules. As a novel and powerful class of ligands, aptamers are thought to have excellent potential for applications in the fields of biosensing, diagnostics and therapeutics. In this study, a new method for predicting aptamer-target interacting pairs was proposed by integrating features derived from both aptamers and their targets. Features of nucleotide composition and traditional amino acid composition as well as pseudo amino acid were utilized to represent aptamers and targets, respectively. The predictor was constructed based on Random Forest and the optimal features were selected by using the maximum relevance minimum redundancy (mRMR) method and the incremental feature selection (IFS) method. As a result, 81.34% accuracy and 0.4612 MCC were obtained for the training dataset, and 77.41% accuracy and 0.3717 MCC were achieved for the testing dataset. An optimal feature set of 220 features were selected, which were considered as the ones that contributed significantly to the interacting aptamer-target pair predictions. Analysis of the optimal feature set indicated several important factors in determining aptamer-target interactions. It is anticipated that our prediction method may become a useful tool for identifying aptamer-target pairs and the features selected and analyzed in this study may provide useful insights into the mechanism of interactions between aptamers and targets. [ABSTRACT FROM AUTHOR]

Human leukocyte antigen (HLA) class I molecules are critical components of the cell-mediated immune system that bind and present intracellular antigenic peptides to CD8+ T cell receptors. To understand the interaction mechanism underlying human leukocyte antigen (HLA) class I specificity in detail, we studied the structural interaction characteristics of 16,393 nonameric peptides binding to 58 HLA-A and -B molecules. Our analysis showed for the first time that HLA-peptide intermolecular bonding patterns vary among different alleles and may be grouped in a superfamily dependent manner. Through the use of these HLA class I ‘fingerprints’, a high resolution HLA class I superfamily classification schema was developed. This classification is capable of separating HLA alleles into well resolved, non-overlapping clusters, which is consistent with known HLA superfamily definitions. Such structural interaction approach serves as an excellent alternative to the traditional methods of HLA superfamily definitions that use peptide binding motifs or receptor information, and will help identify appropriate antigens suitable for broad-based subunit vaccine design. [ABSTRACT FROM AUTHOR]

The regulation of chromosome separation during mitosis is not fully understood yet. Microtubules forming mitotic spindles are targets of treatment strategies which are aimed at (i) the triggering of the apoptosis or (ii) the interruption of uncontrolled cell division. Despite these facts, only few physical models relating to the dynamics of mitotic spindles exist up to now. In this paper, we present the first electromechanical model which enables calculation of the electromagnetic field coupled to acoustic vibrations of the mitotic spindle. This electromagnetic field originates from the electrical polarity of microtubules which form the mitotic spindle. The model is based on the approximation of resonantly vibrating microtubules by a network of oscillating electric dipoles. Our computational results predict the existence of a rapidly changing electric field which is generated by either driven or endogenous vibrations of the mitotic spindle. For certain values of parameters, the intensity of the electric field and its gradient reach values which may exert a not-inconsiderable force on chromosomes which are aligned in the spindle midzone. Our model may describe possible mechanisms of the effects of ultra-short electrical and mechanical pulses on dividing cells—a strategy used in novel methods for cancer treatment. [ABSTRACT FROM AUTHOR]

While the mechanism by which Grp94 displays its chaperone function with client peptides in the cell has been elucidated extensively, much less is known about the nature and properties of how Grp94 can engage binding to proteins once it is exposed on the cell surface or liberated in the extra-cellular milieu, as occurs in pathological conditions. In this work, we wanted to investigate the molecular aspects and structural characteristics of complexes that Grp94 forms with human IgG, posing the attention on the influence that glycosylation of Grp94 might have on the binding capacity to IgG, and on the identification of sites involved in the binding. To this aim, we employed both native, fully glycosylated and partially glycosylated Grp94, and recombinant, non-glycosylated Grp94, as well as IgG subunits, in different experimental conditions, including the physiological setting of human plasma. Regardless of the species and type, Grp94 engages a similar, highly specific and stable binding with IgG that involves sites located in the N-terminal domain of Grp94 and the hinge region of whole IgG. Grp94 does not form stable complex with Fab, F(ab)2 or Fc. Glycosylation turns out to be an obstacle to the Grp94 binding to IgG, although this negative effect can be counteracted by ATP and spontaneously also disappears in time in a physiological setting of incubation. ATP does not affect at all the binding capacity of non-glycosylated Grp94. However, complexes that native, partially glycosylated Grp94 forms with IgG in the presence of ATP show strikingly different characteristics with respect to those formed in absence of ATP. Results have relevance for the mechanism regulating the formation of stable Grp94-IgG complexes in vivo, in the pathological conditions associated with the extra-cellular location of Grp94. [ABSTRACT FROM AUTHOR]

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at http://istar.cse.cuhk.edu.hk/idock. [ABSTRACT FROM AUTHOR]

Background: Understanding protein complexes is important for understanding the science of cellular organization and function. Many computational methods have been developed to identify protein complexes from experimentally obtained protein-protein interaction (PPI) networks. However, interaction information obtained experimentally can be unreliable and incomplete. Reconstructing these PPI networks with PPI evidences from other sources can improve protein complex identification. Results: We combined PPI information from 6 different sources and obtained a reconstructed PPI network for yeast through machine learning. Some popular protein complex identification methods were then applied to detect yeast protein complexes using the new PPI networks. Our evaluation indicates that protein complex identification algorithms using the reconstructed PPI network significantly outperform ones on experimentally verified PPI networks. Conclusions: We conclude that incorporating PPI information from other sources can improve the effectiveness of protein complex identification. [ABSTRACT FROM AUTHOR]

The specific targeting of protein to organelles is achieved by targeting signals being recognised by their cognate receptors. Cytosolic chaperones, bound to precursor proteins, are recognized by specific receptors of the import machinery enabling transport into the specific organelle. The aim of this study was to gain greater insight into the mode of recognition of the C-termini of Hsp70 and Hsp90 chaperones by the Tetratricopeptide Repeat (TPR) domain of the chloroplast import receptor Toc64 from Arabidopsis thaliana (At). The monomeric TPR domain binds with 1∶1 stoichiometry in similar micromolar affinity to both Hsp70 and Hsp90 as determined by isothermal titration calorimetry (ITC). Mutations of the terminal EEVD motif caused a profound decrease in affinity. Additionally, this study considered the contributions of residues upstream as alanine scanning experiments of these residues showed reduced binding affinity. Molecular dynamics simulations of the TPR domain helices upon peptide binding predicted that two helices within the TPR domain move backwards, exposing the cradle surface for interaction with the peptide. Our findings from ITC and molecular dynamics studies suggest that AtToc64_TPR does not discriminate between C-termini peptides of Hsp70 and Hsp90. [ABSTRACT FROM AUTHOR]

The specific targeting of protein to organelles is achieved by targeting signals being recognised by their cognate receptors. Cytosolic chaperones, bound to precursor proteins, are recognized by specific receptors of the import machinery enabling transport into the specific organelle. The aim of this study was to gain greater insight into the mode of recognition of the C-termini of Hsp70 and Hsp90 chaperones by the Tetratricopeptide Repeat (TPR) domain of the chloroplast import receptor Toc64 from Arabidopsis thaliana (At). The monomeric TPR domain binds with 1∶1 stoichiometry in similar micromolar affinity to both Hsp70 and Hsp90 as determined by isothermal titration calorimetry (ITC). Mutations of the terminal EEVD motif caused a profound decrease in affinity. Additionally, this study considered the contributions of residues upstream as alanine scanning experiments of these residues showed reduced binding affinity. Molecular dynamics simulations of the TPR domain helices upon peptide binding predicted that two helices within the TPR domain move backwards, exposing the cradle surface for interaction with the peptide. Our findings from ITC and molecular dynamics studies suggest that AtToc64_TPR does not discriminate between C-termini peptides of Hsp70 and Hsp90. [ABSTRACT FROM AUTHOR]

Genome packaging for viruses with segmented genomes is often a complex problem. This is particularly true for influenza viruses and other orthomyxoviruses, whose genome consists of multiple negative-sense RNAs encapsidated as ribonucleoprotein (RNP) complexes. To better understand the structural features of orthomyxovirus RNPs that allow them to be packaged, we determined the crystal structure of the nucleoprotein (NP) of a fish orthomyxovirus, the infectious salmon anemia virus (ISAV) (genus Isavirus). As the major protein component of the RNPs, ISAV-NP possesses a bi-lobular structure similar to the influenza virus NP. Because both RNA-free and RNA-bound ISAV NP forms stable dimers in solution, we were able to measure the NP RNA binding affinity as well as the stoichiometry using recombinant proteins and synthetic oligos. Our RNA binding analysis revealed that each ISAV-NP binds ∼12 nts of RNA, shorter than the 24–28 nts originally estimated for the influenza A virus NP based on population average. The 12-nt stoichiometry was further confirmed by results from electron microscopy and dynamic light scattering. Considering that RNPs of ISAV and the influenza viruses have similar morphologies and dimensions, our findings suggest that NP-free RNA may exist on orthomyxovirus RNPs, and selective RNP packaging may be accomplished through direct RNA-RNA interactions. [ABSTRACT FROM AUTHOR]