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  In many experimental assays, such generic interactions are rightfully filtered out. [...]the definition of PPI has to consider (1st) the interaction interface should be intentional and not accidental, i.e., the result of specific selected biomolecular events/forces; and (2nd) the interaction interface should be non-generic, i.e., evolved for a specific purpose distinct from totally generic functions such as protein production, degradation, and others. [...]the use of PPI data combined with related pathways allows for a useful and detailed exploration of protein networks.

Peptidyl-prolyl isomerases catalyze the conversion between cis and trans isomers of proline. The cyclophilin family of peptidyl-prolyl isomerases is well known for being the target of the immunosuppressive drug cyclosporin, used to combat organ transplant rejection. There is great interest in both the substrate specificity of these enzymes and the design of isoform-selective ligands for them. However, the dearth of available data for individual family members inhibits attempts to design drug specificity; additionally, in order to define physiological functions for the cyclophilins, definitive isoform characterization is required. In the current study, enzymatic activity was assayed for 15 of the 17 human cyclophilin isomerase domains, and binding to the cyclosporin scaffold was tested. In order to rationalize the observed isoform diversity, the high-resolution crystallographic structures of seven cyclophilin domains were determined. These models, combined with seven previously solved cyclophilin isoforms, provide the basis for a family-wide structure:function analysis. Detailed structural analysis of the human cyclophilin isomerase explains why cyclophilin activity against short peptides is correlated with an ability to ligate cyclosporin and why certain isoforms are not competent for either activity. In addition, we find that regions of the isomerase domain outside the proline-binding surface impart isoform specificity for both in vivo substrates and drug design. We hypothesize that there is a well-defined molecular surface corresponding to the substrate-binding S2 position that is a site of diversity in the cyclophilin family. Computational simulations of substrate binding in this region support our observations. Our data indicate that unique isoform determinants exist that may be exploited for development of selective ligands and suggest that the currently available small-molecule and peptide-based ligands for this class of enzyme are insufficient for isoform specificity.

We study apo and holo forms of the bacterial ferric binding protein (FBP) which exhibits the so-called ferric transport dilemma: it uptakes iron from the host with remarkable affinity, yet releases it with ease in the cytoplasm for subsequent use. The observations fit the \"conformational selection\" model whereby the existence of a weakly populated, higher energy conformation that is stabilized in the presence of the ligand is proposed. We introduce a new tool that we term perturbation-response scanning (PRS) for the analysis of remote control strategies utilized. The approach relies on the systematic use of computational perturbation/response techniques based on linear response theory, by sequentially applying directed forces on single-residues along the chain and recording the resulting relative changes in the residue coordinates. We further obtain closed-form expressions for the magnitude and the directionality of the response. Using PRS, we study the ligand release mechanisms of FBP and support the findings by molecular dynamics simulations. We find that the residue-by-residue displacements between the apo and the holo forms, as determined from the X-ray structures, are faithfully reproduced by perturbations applied on the majority of the residues of the apo form. However, once the stabilizing ligand (Fe) is integrated to the system in holo FBP, perturbing only a few select residues successfully reproduces the experimental displacements. Thus, iron uptake by FBP is a favored process in the fluctuating environment of the protein, whereas iron release is controlled by mechanisms including chelation and allostery. The directional analysis that we implement in the PRS methodology implicates the latter mechanism by leading to a few distant, charged, and exposed loop residues. Upon perturbing these, irrespective of the direction of the operating forces, we find that the cap residues involved in iron release are made to operate coherently, facilitating release of the ion.

High resolution structures of antibody-antigen complexes are useful for analyzing the binding interface and to make rational choices for antibody engineering. When a crystallographic structure of a complex is unavailable, the structure must be predicted using computational tools. In this work, we illustrate a novel approach, named SnugDock, to predict high-resolution antibody-antigen complex structures by simultaneously structurally optimizing the antibody-antigen rigid-body positions, the relative orientation of the antibody light and heavy chains, and the conformations of the six complementarity determining region loops. This approach is especially useful when the crystal structure of the antibody is not available, requiring allowances for inaccuracies in an antibody homology model which would otherwise frustrate rigid-backbone docking predictions. Local docking using SnugDock with the lowest-energy RosettaAntibody homology model produced more accurate predictions than standard rigid-body docking. SnugDock can be combined with ensemble docking to mimic conformer selection and induced fit resulting in increased sampling of diverse antibody conformations. The combined algorithm produced four medium (Critical Assessment of PRediction of Interactions-CAPRI rating) and seven acceptable lowest-interface-energy predictions in a test set of fifteen complexes. Structural analysis shows that diverse paratope conformations are sampled, but docked paratope backbones are not necessarily closer to the crystal structure conformations than the starting homology models. The accuracy of SnugDock predictions suggests a new genre of general docking algorithms with flexible binding interfaces targeted towards making homology models useful for further high-resolution predictions.

Many important protein-protein interactions are mediated by the binding of a short peptide stretch in one protein to a large globular segment in another. Recent efforts have provided hundreds of examples of new peptides binding to proteins for which a three-dimensional structure is available (either known experimentally or readily modeled) but where no structure of the protein-peptide complex is known. To address this gap, we present an approach that can accurately predict peptide binding sites on protein surfaces. For peptides known to bind a particular protein, the method predicts binding sites with great accuracy, and the specificity of the approach means that it can also be used to predict whether or not a putative or predicted peptide partner will bind. We used known protein-peptide complexes to derive preferences, in the form of spatial position specific scoring matrices, which describe the binding-site environment in globular proteins for each type of amino acid in bound peptides. We then scan the surface of a putative binding protein for sites for each of the amino acids present in a peptide partner and search for combinations of high-scoring amino acid sites that satisfy constraints deduced from the peptide sequence. The method performed well in a benchmark and largely agreed with experimental data mapping binding sites for several recently discovered interactions mediated by peptides, including RG-rich proteins with SMN domains, Epstein-Barr virus LMP1 with TRADD domains, DBC1 with Sir2, and the Ago hook with Argonaute PIWI domain. The method, and associated statistics, is an excellent tool for predicting and studying binding sites for newly discovered peptides mediating critical events in biology.

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 A backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 A backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available.

Aggregation of unfolded proteins occurs mainly through the exposed hydrophobic surfaces. Any mechanism of inhibition of this aggregation should explain the prevention of these hydrophobic interactions. Though arginine is prevalently used as an aggregation suppressor, its mechanism of action is not clearly understood. We propose a mechanism based on the hydrophobic interactions of arginine. We have analyzed arginine solution for its hydrotropic effect by pyrene solubility and the presence of hydrophobic environment by 1-anilino-8-naphthalene sulfonic acid fluorescence. Mass spectroscopic analyses show that arginine forms molecular clusters in the gas phase and the cluster composition is dependent on the solution conditions. Light scattering studies indicate that arginine exists as clusters in solution. In the presence of arginine, the reverse phase chromatographic elution profile of Alzheimer's amyloid beta 1-42 (Abeta(1-42)) peptide is modified. Changes in the hydrodynamic volume of Abeta(1-42) in the presence of arginine measured by size exclusion chromatography show that arginine binds to Abeta(1-42). Arginine increases the solubility of Abeta(1-42) peptide in aqueous medium. It decreases the aggregation of Abeta(1-42) as observed by atomic force microscopy. Based on our experimental results we propose that molecular clusters of arginine in aqueous solutions display a hydrophobic surface by the alignment of its three methylene groups. The hydrophobic surfaces present on the proteins interact with the hydrophobic surface presented by the arginine clusters. The masking of hydrophobic surface inhibits protein-protein aggregation. This mechanism is also responsible for the hydrotropic effect of arginine on various compounds. It is also explained why other amino acids fail to inhibit the protein aggregation.

Viral attachment to specific host receptors is the first step in viral infection and serves an essential function in the selection of target cells. Mammalian reoviruses are highly useful experimental models for studies of viral pathogenesis and show promise as vectors for oncolytics and vaccines. Reoviruses engage cells by binding to carbohydrates and the immunoglobulin superfamily member, junctional adhesion molecule-A (JAM-A). JAM-A exists at the cell surface as a homodimer formed by extensive contacts between its N-terminal immunoglobulin-like domains. We report the crystal structure of reovirus attachment protein σ1 in complex with a soluble form of JAM-A. The σ1 protein disrupts the JAM-A dimer, engaging a single JAM-A molecule via virtually the same interface that is used for JAM-A homodimerization. Thus, reovirus takes advantage of the adhesive nature of an immunoglobulin-superfamily receptor by usurping the ligand-binding site of this molecule to attach to the cell surface. The dissociation constant (KD) of the interaction between σ1 and JAM-A is 1,000-fold lower than that of the homophilic interaction between JAM-A molecules, indicating that JAM-A strongly prefers σ1 as a ligand. Analysis of reovirus mutants engineered by plasmid-based reverse genetics revealed residues in σ1 required for binding to JAM-A and infectivity of cultured cells. These studies define biophysical mechanisms of reovirus cell attachment and provide a platform for manipulating reovirus tropism to enhance vector targeting. Mammalian orthoreoviruses (reoviruses) are useful models for studies of virus–receptor interactions and viral pathogenesis. They are closely related in structure to adenoviruses and share similar mechanisms of cell attachment and entry. The receptor for reovirus, junctional adhesion molecule-A (JAM-A), is a component of cellular junctions and also used as a receptor by feline calicivirus. To better understand how viruses engage cellular receptors, we determined the structure of reovirus attachment protein σ1 bound to JAM-A. The structure provides an understanding of the biological function of the interaction and yields information that may enable targeting of reovirus to alternate receptors. Since the repertoire of receptors bound by a virus contributes importantly to determining which types of cells are infected, such targeting plays an essential role in gene delivery for vaccine or therapeutic applications. New cancer therapy approaches include the use of viruses, including reovirus, to lyse tumor cells. New knowledge about reovirus attachment to cellular receptors at an atomic level will help to harness the therapeutic potential of this virus.

Escherichia coli strains adhere to the normally sterile human uroepithelium using type 1 pili, that are long, hairy surface organelles exposing a mannose-binding FimH adhesin at the tip. A small percentage of adhered bacteria can successfully invade bladder cells, presumably via pathways mediated by the high-mannosylated uroplakin-Ia and alpha3beta1 integrins found throughout the uroepithelium. Invaded bacteria replicate and mature into dense, biofilm-like inclusions in preparation of fluxing and of infection of neighbouring cells, being the major cause of the troublesome recurrent urinary tract infections. We demonstrate that alpha-D-mannose based inhibitors of FimH not only block bacterial adhesion on uroepithelial cells but also antagonize invasion and biofilm formation. Heptyl alpha-D-mannose prevents binding of type 1-piliated E. coli to the human bladder cell line 5637 and reduces both adhesion and invasion of the UTI89 cystitis isolate instilled in mouse bladder via catheterization. Heptyl alpha-D-mannose also specifically inhibited biofilm formation at micromolar concentrations. The structural basis of the great inhibitory potential of alkyl and aryl alpha-D-mannosides was elucidated in the crystal structure of the FimH receptor-binding domain in complex with oligomannose-3. FimH interacts with Man alpha1,3Man beta1,4GlcNAc beta1,4GlcNAc in an extended binding site. The interactions along the alpha1,3 glycosidic bond and the first beta1,4 linkage to the chitobiose unit are conserved with those of FimH with butyl alpha-D-mannose. The strong stacking of the central mannose with the aromatic ring of Tyr48 is congruent with the high affinity found for synthetic inhibitors in which this mannose is substituted for by an aromatic group. The potential of ligand-based design of antagonists of urinary tract infections is ruled by the structural mimicry of natural epitopes and extends into blocking of bacterial invasion, intracellular growth and capacity to fluxing and of recurrence of the infection.

Transcription factors are central components of the intracellular regulatory networks that control gene expression. An increasingly recognized phenomenon among human transcription factors is the formation of structure upon target binding. Here, we study the folding and binding of the pKID domain of CREB to the KIX domain of the co-activator CBP. Our simulations of a topology-based Gō-type model predict a coupled folding and binding mechanism, and the existence of partially bound intermediates. From transition-path and Phi-value analyses, we find that the binding transition state resembles the unstructured state in solution, implying that CREB becomes structured only after committing to binding. A change of structure following binding is reminiscent of an induced-fit mechanism and contrasts with models in which binding occurs to pre-structured conformations that exist in the unbound state at equilibrium. Interestingly, increasing the amount of structure in the unbound pKID reduces the rate of binding, suggesting a \"fly-casting\"-like process. We find that the inclusion of attractive non-native interactions results in the formation of non-specific encounter complexes that enhance the on-rate of binding, but do not significantly change the binding mechanism. Our study helps explain how being unstructured can confer an advantage in protein target recognition. The simulations are in general agreement with the results of a recently reported nuclear magnetic resonance study, and aid in the interpretation of the experimental binding kinetics.