Helical Chirality: a Link between Local Interactions and Global Topology in DNA

DNA supercoiling plays a major role in many cellular functions. The global DNA conformation is however intimately linked to local DNA-DNA interactions influencing both the physical properties and the biological functions of the supercoiled molecule. Juxtaposition of DNA double helices in ubiquitous crossover arrangements participates in multiple functions such as recombination, gene regulation and DNA packaging. However, little is currently known about how the structure and stability of direct DNA-DNA interactions influence the topological state of DNA. Here, a crystallographic analysis shows that due to the intrinsic helical chirality of DNA, crossovers of opposite handedness exhibit markedly different geometries. While right-handed crossovers are self-fitted by sequence-specific groove-backbone interaction and bridging Mg2+ sites, left-handed crossovers are juxtaposed by groove-groove interaction. Our previous calculations have shown that the different geometries result in differential stabilisation in solution, in the presence of divalent cations. The present study reveals that the various topological states of the cell are associated with different inter-segmental interactions. While the unstable left-handed crossovers are exclusively formed in negatively supercoiled DNA, stable right-handed crossovers constitute the local signature of an unusual topological state in the cell, such as the positively supercoiled or relaxed DNA. These findings not only provide a simple mechanism for locally sensing the DNA topology but also lead to the prediction that, due to their different tertiary intra-molecular interactions, supercoiled molecules of opposite signs must display markedly different physical properties. Sticky inter-segmental interactions in positively supercoiled or relaxed DNA are expected to greatly slow down the slithering dynamics of DNA. We therefore suggest that the intrinsic helical chirality of DNA may have oriented the early evolutionary choices for DNA topology

Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein-protein interaction prediction and design methods. © 2013 American Chemical Society

Identification of hot-spot residues in protein-protein interactions by computational docking

<p>Abstract</p> <p>Background</p> <p>The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'). These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex.</p> <p>Results</p> <p>We have applied here normalized interface propensity (<it>NIP</it>) values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value), and the advantage of not requiring any prior structural knowledge of the complex.</p> <p>Conclusion</p> <p>The <it>NIP </it>values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.</p

Structural Analysis of the Essential Resuscitation Promoting Factor YeaZ Suggests a Mechanism of Nucleotide Regulation through Dimer Reorganization

Extent: 8p.Background: The yeaZ gene product forms part of the conserved network YjeE/YeaZ/YgjD essential for the survival of many Gram-negative eubacteria. Among other as yet unidentified roles, YeaZ functions as a resuscitation promoting factor required for survival and resuscitation of cells in a viable but non-culturable (VBNC) state. Methodology/Principal Findings: In order to investigate in detail the structure/function relationship of this family of proteins we have performed X-ray crystallographic studies of Vibrio parahaemolyticus YeaZ. The YeaZ structure showed that it has a classic actin-like nucleotide-binding fold. Comparisons of this crystal structure to that of available homologues from E. coli, T. maritima and S. typhimurium revealed two distinctly different modes of dimer formation. In one form, prevalent in the absence of nucleotide, the putative nucleotide-binding site is incomplete, lacking a binding pocket for a nucleotide base. In the second form, residues from the second subunit complete the nucleotide-binding site. This suggests that the two dimer architectures observed in the crystal structures correspond to a free and a nucleotide-bound form of YeaZ. A multiple sequence alignment of YeaZ proteins from different bacteria allowed us to identify a large conserved hydrophobic patch on the protein surface that becomes exposed upon nucleotide-driven dimer re-arrangement. We hypothesize that the transition between two dimer architectures represents the transition between the ‘on’ and ‘off’ states of YeaZ. The effect of this transition is to alternately expose and bury a docking site for the partner protein YgjD. Conclusions/Significance: This paper provides the first structural insight into the putative mechanism of nucleotide regulation of YeaZ through dimer reorganization. Our analysis suggests that nucleotide binding to YeaZ may act as a regulator or switch that changes YeaZ shape, allowing it to switch partners between YjeE and YgjD.Inci Aydin, Yumiko Saijo-Hamano, Keiichi Namba, Connor Thomas and Anna Roujeinikov

Searching for DNA Lesions: Structural Evidence for Lower- and Higher-Affinity DNA Binding Conformations of Human Alkyladenine DNA Glycosylase

To efficiently repair DNA, human alkyladenine DNA glycosylase (AAG) must search the million-fold excess of unmodified DNA bases to find a handful of DNA lesions. Such a search can be facilitated by the ability of glycosylases, like AAG, to interact with DNA using two affinities: a lower-affinity interaction in a searching process and a higher-affinity interaction for catalytic repair. Here, we present crystal structures of AAG trapped in two DNA-bound states. The lower-affinity depiction allows us to investigate, for the first time, the conformation of this protein in the absence of a tightly bound DNA adduct. We find that active site residues of AAG involved in binding lesion bases are in a disordered state. Furthermore, two loops that contribute significantly to the positive electrostatic surface of AAG are disordered. Additionally, a higher-affinity state of AAG captured here provides a fortuitous snapshot of how this enzyme interacts with a DNA adduct that resembles a one-base loop.National Institutes of Health (U.S.) (grant no. P30-ES002109)National Institutes of Health (U.S.) (grant no. GM65337)National Institutes of Health (U.S.) (grant no. GM65337-03S2)National Institutes of Health (U.S.) (grant no. CA055042)National Institutes of Health (U.S.) (grant no. CA092584)Repligen Corporation (KIICR Graduate Fellowship

Protein binding hot spots and the residue-residue pairing preference: a water exclusion perspective

<p>Abstract</p> <p>Background</p> <p>A protein binding hot spot is a small cluster of residues tightly packed at the center of the interface between two interacting proteins. Though a hot spot constitutes a small fraction of the interface, it is vital to the stability of protein complexes. Recently, there are a series of hypotheses proposed to characterize binding hot spots, including the pioneering O-ring theory, the insightful 'coupling' and 'hot region' principle, and our 'double water exclusion' (DWE) hypothesis. As the perspective changes from the O-ring theory to the DWE hypothesis, we examine the physicochemical properties of the binding hot spots under the new hypothesis and compare with those under the O-ring theory.</p> <p>Results</p> <p>The requirements for a cluster of residues to form a hot spot under the DWE hypothesis can be mathematically satisfied by a biclique subgraph if a vertex is used to represent a residue, an edge to indicate a close distance between two residues, and a bipartite graph to represent a pair of interacting proteins. We term these hot spots as DWE bicliques. We identified DWE bicliques from crystal packing contacts, obligate and non-obligate interactions. Our comparative study revealed that there are abundant <it>unique </it>bicliques to the biological interactions, indicating specific biological binding behaviors in contrast to crystal packing. The two sub-types of biological interactions also have their own signature bicliques. In our analysis on residue compositions and residue pairing preferences in DWE bicliques, the focus was on interaction-preferred residues (ipRs) and interaction-preferred residue pairs (ipRPs). It is observed that hydrophobic residues are heavily involved in the ipRs and ipRPs of the obligate interactions; and that aromatic residues are in favor in the ipRs and ipRPs of the biological interactions, especially in those of the non-obligate interactions. In contrast, the ipRs and ipRPs in crystal packing are dominated by hydrophilic residues, and most of the anti-ipRs of crystal packing are the ipRs of the obligate or non-obligate interactions.</p> <p>Conclusions</p> <p>These ipRs and ipRPs in our DWE bicliques describe a diverse binding features among the three types of interactions. They also highlight the specific binding behaviors of the biological interactions, sharply differing from the artifact interfaces in the crystal packing. It can be noted that DWE bicliques, especially the unique bicliques, can capture deep insights into the binding characteristics of protein interfaces.</p

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual aminoacids are systematically mutated to alanine and changes in free energy of binding (Delta Delta G) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which Delta Delta G >= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration

Interferon-γ-producing immature myeloid cells confer protection against severe invasive group A Streptococcus infections

Cytokine-activated neutrophils are known to be essential for protection against group A Streptococcus infections. However, during severe invasive group A Streptococcus infections that are accompanied by neutropenia, it remains unclear which factors are protective against such infections, and which cell population is the source of them. Here we show that mice infected with severe invasive group A Streptococcus isolates, but not with non-invasive group A Streptococcus isolates, exhibit high concentrations of plasma interferon-γ during the early stage of infection. Interferon-γ is necessary to protect mice, and is produced by a novel population of granulocyte–macrophage colony-stimulating factor-dependent immature myeloid cells with ring-shaped nuclei. These interferon-γ-producing immature myeloid cells express monocyte and granulocyte markers, and also produce nitric oxide. The adoptive transfer of interferon-γ-producing immature myeloid cells ameliorates infection in wild-type and interferon-γ-deficient mice. Our results indicate that interferon-γ-producing immature myeloid cells have a protective role during the early stage of severe invasive group A Streptococcus infections

Origin and Evolution of GALA-LRR, a New Member of the CC-LRR Subfamily: From Plants to Bacteria?

The phytopathogenic bacterium Ralstonia solanacearum encodes type III effectors, called GALA proteins, which contain F-box and LRR domains. The GALA LRRs do not perfectly fit any of the previously described LRR subfamilies. By applying protein sequence analysis and structural prediction, we clarify this ambiguous case of LRR classification and assign GALA-LRRs to CC-LRR subfamily. We demonstrate that side-by-side packing of LRRs in the 3D structures may control the limits of repeat variability within the LRR subfamilies during evolution. The LRR packing can be used as a criterion, complementing the repeat sequences, to classify newly identified LRR domains. Our phylogenetic analysis of F-box domains proposes the lateral gene transfer of bacterial GALA proteins from host plants. We also present an evolutionary scenario which can explain the transformation of the original plant LRRs into slightly different bacterial LRRs. The examination of the selective evolutionary pressure acting on GALA proteins suggests that the convex side of their horse-shoe shaped LRR domains is more prone to positive selection than the concave side, and we therefore hypothesize that the convex surface might be the site of protein binding relevant to the adaptor function of the F-box GALA proteins. This conclusion provides a strong background for further functional studies aimed at determining the role of these type III effectors in the virulence of R. solanacearum