Structural characterization of the PliG lysozyme inhibitor family

Structure and Function of the T4 Spackle Protein Gp61.3

The bacteriophage T4 genome contains two genes that code for proteins with lysozyme activity—e and 5. Gene e encodes the well-known T4 lysozyme (commonly called T4L) that functions to break the peptidoglycan layer late in the infection cycle, which is required for liberating newly assembled phage progeny. Gene product 5 (gp5) is the tail-associated lysozyme, a component of the phage particle. It forms a spike at the tip of the tail tube and functions to pierce the outer membrane of the Escherichia coli host cell after the phage has attached to the cell surface. Gp5 contains a T4L-like lysozyme domain that locally digests the peptidoglycan layer upon infection. The T4 Spackle protein (encoded by gene 61.3) has been thought to play a role in the inhibition of gp5 lysozyme activity and, as a consequence, in making cells infected by bacteriophage T4 resistant to later infection by T4 and closely related phages. Here we show that (1) gp61.3 is secreted into the periplasm where its N-terminal periplasm-targeting peptide is cleaved off; (2) gp61.3 forms a 1:1 complex with the lysozyme domain of gp5 (gp5Lys); (3) gp61.3 selectively inhibits the activity of gp5, but not that of T4L; (4) overexpression of gp5 causes cell lysis. We also report a crystal structure of the gp61.3-gp5Lys complex that demonstrates that unlike other known lysozyme inhibitors, gp61.3 does not interact with the active site cleft. Instead, it forms a “wall” that blocks access of an extended polysaccharide substrate to the cleft and, possibly, locks the enzyme in an “open-jaw”-like conformation making catalysis impossible.

Interplay between Peptidoglycan Biology and Virulence in Gram-Negative Pathogens

The clinical and epidemiological threat of the growing antimicrobial resistance in Gram-negative pathogens, particularly for β-lactams, the most frequently used and relevant antibiotics, urges research to find new therapeutic weapons to combat the infections caused by these microorganisms. An essential previous step in the development of these therapeutic solutions is to identify their potential targets in the biology of the pathogen. This is precisely what we sought to do in this review specifically regarding the barely exploited field analyzing the interplay among the biology of the peptidoglycan and related processes, such as β-lactamase regulation and virulence. Hence, here we gather, analyze, and integrate the knowledge derived from published works that provide information on the topic, starting with those dealing with the historically neglected essential role of the Gram-negative peptidoglycan in virulence, including structural, biogenesis, remodeling, and recycling aspects, in addition to proinflammatory and other interactions with the host. We also review the complex link between intrinsic β-lactamase production and peptidoglycan metabolism, as well as the biological costs potentially associated with the expression of horizontally acquired β-lactamases. Finally, we analyze the existing evidence from multiple perspectives to provide useful clues for identifying targets enabling the future development of therapeutic options attacking the peptidoglycan-virulence interconnection as a key weak point of the Gram-negative pathogens to be used, if not to kill the bacteria, to mitigate their capacity to produce severe infections.

Protecting Gram-negative bacterial cell envelopes from human lysozyme: Interactions with Ivy inhibitor proteins from Escherichia coli and Pseudomonas aeruginosa

Lysozymes play an important role in host defense by degrading peptidoglycan in the cell envelopes of pathogenic bacteria. Several Gram-negative bacteria can evade this mechanism by producing periplasmic proteins that inhibit the enzymatic activity of lysozyme. The Escherichia coli inhibitor of vertebrate lysozyme, Ivyc and its Pseudomonas aeruginosa homolog, Ivyp1 have been shown to be potent inhibitors of hen egg white lysozyme (HEWL). Since human lysozyme (HL) plays an important role in the innate immune response, we have examined the binding of HL to Ivyc and Ivyp1. Our results show that Ivyp1 is a weaker inhibitor of HL than Ivyc even though they inhibit HEWL with similar potency. Calorimetry experiments confirm that Ivyp1 interacts more weakly with HL than HEWL. Analytical ultracentrifugation studies revealed that Ivyp1 in solution is a monomer and forms a 30kDa heterodimer with both HL and HEWL, while Ivyc is a homodimer that forms a tetramer with both enzymes. The interaction of Ivyp1 with HL was further characterized by NMR chemical shift perturbation experiments. In addition to the characteristic His-containing Ivy inhibitory loop that binds into the active site of lysozyme, an extended loop (P2) between the final two beta-strands also participates in forming protein-protein interactions. The P2 loop is not conserved in Ivyc and it constitutes a flexible region in Ivyp1 that becomes more rigid in the complex with HL. We conclude that differences in the electrostatic interactions at the binding interface between Ivy inhibitors and distinct lysozymes determine the strength of this interaction. This article is part of a Special Issue entitled: Bacterial Resistance to Antimicrobial Peptides.

The structure of the proteinaceous inhibitor PliI from Aeromonas hydrophila in complex with its target lysozyme

Recent microbiological data have revealed that Gram-negative bacteria are able to protect themselves against the lytic action of host lysozymes by secreting proteinaceous inhibitors. Four distinct classes of such inhibitors have been discovered that specifically act against c-type, g-type and i-type lysozymes. Here, the 1.24 Å resolution crystal structure of the periplasmic i-type lysozyme inhibitor from Aeromonas hydrophila (PliI-Ah) in complex with the i-type lysozyme from Meretrix lusoria is reported. The structure is the first to explain the inhibitory mechanism of the PliI family at the atomic level. A distinct `ridge' formed by three exposed PliI loops inserts into the substrate-binding groove of the lysozyme, resulting in a complementary `key-lock' interface. The interface is principally stabilized by the interactions made by the PliI-Ah residues Ser104 and Tyr107 belonging to the conserved SGxY motif, as well as by the other conserved residues Ser46 and Asp76. The functional importance of these residues is confirmed by inhibition assays with the corresponding point mutants of PliI-Ah. The accumulated structural data on lysozyme-inhibitor complexes from several classes indicate that in all cases an extensive interface of either a single or a double `key-lock' type is formed, resulting in highly efficient inhibition. These data provide a basis for the rational development of a new class of antibacterial drugs.

Crystal structure of the carbapenem intrinsic resistance protein CarG

In the Gram-negative enterobacterium Erwinia (Pectobacterium) and Serratia sp. ATCC 39006, intrinsic resistance to the carbapenem antibiotic 1-carbapen-2-em-3-carboxylic acid is mediated by the CarF and CarG proteins, by an unknown mechanism. Here, we report a high-resolution crystal structure for the Serratia sp. ATCC 39006 carbapenem resistance protein CarG. This structure of CarG is the first in the carbapenem intrinsic resistance (CIR) family of resistance proteins from carbapenem-producing bacteria. The crystal structure shows the protein to form a homodimer, in agreement with results from analytical gel filtration. The structure of CarG does not show homology with any known antibiotic resistance proteins nor does it belong to any well-characterised protein structural family. However, it is a close structural homologue of the bacterial inhibitor of invertebrate lysozyme, PliI-Ah, with some interesting structural variations, including the absence of the catalytic site responsible for lysozyme inhibition. Both proteins show a unique β-sandwich fold with short terminal α-helices. The core of the protein is formed by stacked anti-parallel sheets that are individually very similar in the two proteins but differ in their packing interface, causing the splaying of the two sheets in CarG. Furthermore, a conserved cation binding site identified in CarG is absent from the homologue.

Inclusion of the orientational entropic effect and low-resolution experimental information for protein-protein docking in Critical Assessment of PRedicted Interactions (CAPRI)

Inclusion of entropy is important and challenging for protein-protein binding prediction. Here, we present a statistical mechanics-based approach to empirically consider the effect of orientational entropy. Specifically, we globally sample the possible binding orientations based on a simple shape-complementarity scoring function using an FFT-type docking method. Then, for each generated orientation, we calculate the probability through the partition function of the ensemble of accessible states, which are assumed to be represented by the set of nearby binding modes. For each mode, the interaction energy is calculated using our ITScorePP scoring function that was developed in our laboratory based on principles of statistical mechanics. Using the above protocol, we present the results of our participation in Rounds 22-27 of the Critical Assessment of PRedicted Interactions (CAPRI) experiment for 10 targets (T46-T58). Additional experimental information, such as low-resolution small-angle X-ray scattering data, was used when available. In the prediction (or docking) experiments of the 10 target complexes, we achieved correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T48 and T57), and three with acceptable accuracy (T49, T50, and T58). In the scoring experiments of seven target complexes, we obtained correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T49 and T50), and three with acceptable accuracy (T46, T51, and T53).

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems.

Using the concept of transient complex for affinity predictions in CAPRI rounds 20-27 and beyond

Predictions of protein-protein binders and binding affinities have traditionally focused on features pertaining to the native complexes. In developing a computational method for predicting protein-protein association rate constants, we introduced the concept of transient complex after mapping the interaction energy surface. The transient complex is located at the outer boundary of the bound-state energy well, having near-native separation and relative orientation between the subunits but not yet formed most of the short-range native interactions. We found that the width of the binding funnel and the electrostatic interaction energy of the transient complex are among the features predictive of binders and binding affinities. These ideas were very promising for the five affinity-related targets (T43-45, 55, and 56) of CAPRI rounds 20-27. For T43, we ranked the single crystallographic complex as number 1 and were one of only two groups that clearly identified that complex as a true binder; for T44, we ranked the only design with measurable binding affinity as number 4. For the nine docking targets, continuing on our success in previous CAPRI rounds, we produced 10 medium-quality models for T47 and acceptable models for T48 and T49. We conclude that the interaction energy landscape and the transient complex in particular will complement existing features in leading to better prediction of binding affinities.

Expanding the frontiers of protein-protein modeling: from docking and scoring to binding affinity predictions and other challenges

In addition to protein-protein docking, this CAPRI edition included new challenges, like protein-water and protein-sugar interactions, or the prediction of binding affinities and ΔΔG changes upon mutation. Regarding the standard protein-protein docking cases, our approach, mostly based on the pyDock scheme, submitted correct models as predictors and as scorers for 67% and 57% of the evaluated targets, respectively. In this edition, available information on known interface residues hardly made any difference for our predictions. In one of the targets, the inclusion of available experimental small-angle X-ray scattering (SAXS) data using our pyDockSAXS approach slightly improved the predictions. In addition to the standard protein-protein docking assessment, new challenges were proposed. One of the new problems was predicting the position of the interface water molecules, for which we submitted models with 20% and 43% of the water-mediated native contacts predicted as predictors and scorers, respectively. Another new problem was the prediction of protein-carbohydrate binding, where our submitted model was very close to being acceptable. A set of targets were related to the prediction of binding affinities, in which our pyDock scheme was able to discriminate between natural and designed complexes with area under the curve = 83%. It was also proposed to estimate the effect of point mutations on binding affinity. Our approach, based on machine learning methods, showed high rates of correctly classified mutations for all cases. The overall results were highly rewarding, and show that the field is ready to move forward and face new interesting challenges in interactomics.

Structural basis of bacterial defense against g-type lysozyme-based innate immunity

Gram-negative bacteria can produce specific proteinaceous inhibitors to defend themselves against the lytic action of host lysozymes. So far, four different lysozyme inhibitor families have been identified. Here, we report the crystal structure of the Escherichia coli periplasmic lysozyme inhibitor of g-type lysozyme (PliG-Ec) in complex with Atlantic salmon g-type lysozyme (SalG) at a resolution of 0.95 Å, which is exceptionally high for a complex of two proteins. The structure reveals for the first time the mechanism of g-type lysozyme inhibition by the PliG family. The latter contains two specific conserved regions that are essential for its inhibitory activity. The inhibitory complex formation is based on a double 'key-lock' mechanism. The first key-lock element is formed by the insertion of two conserved PliG regions into the active site of the lysozyme. The second element is defined by a distinct pocket of PliG accommodating a lysozyme loop. Computational analysis indicates that this pocket represents a suitable site for small molecule binding, which opens an avenue for the development of novel antibacterial agents that suppress the inhibitory activity of PliG.