A quantitative approach for studying IgE-FcepsilonRI aggregation

Targeting Intramembrane Protein-Protein Interactions: Novel Therapeutic Strategy of Millions Years Old

Intramembrane protein-protein interactions (PPIs) are involved in transmembrane signal transduction mediated by cell surface receptors and play an important role in health and disease. Recently, receptor-specific modulatory peptides rationally designed using a general platform of transmembrane signaling, the signaling chain homooligomerization (SCHOOL) model, have been proposed to therapeutically target these interactions in a variety of serious diseases with unmet needs including cancer, sepsis, arthritis, retinopathy, and thrombosis. These peptide drug candidates use ligand-independent mechanisms of action (SCHOOL mechanisms) and demonstrate potent efficacy in vitro and in vivo. Recent studies surprisingly revealed that in order to modify and/or escape the host immune response, human viruses use similar mechanisms and modulate cell surface receptors by targeting intramembrane PPIs in a ligand-independent manner. Here, I review these intriguing mechanistic similarities and discuss how the viral strategies optimized over a billion years of the coevolution of viruses and their hosts can help to revolutionize drug discovery science and develop new, disruptive therapies. Examples are given.

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions.

Synthetic allergen design reveals the significance of moderate affinity epitopes in mast cell degranulation

This study describes the design of a well-defined homotetravalent synthetic allergen (HTA) system to investigate the effect of hapten-IgE interactions on mast cell degranulation. A library of DNP variants with varying affinities for IgE(DNP) was generated (K(d) from 8.1 nM to 9.2 μM), and 8 HTAs spanning this range were synthesized via conjugation of each DNP variant to the tetravalent scaffold. HTAs with hapten K(d) < 235 nM stimulated degranulation following a bell-shaped dose response curve with maximum response occurring near the hapten K(d). HTAs with hapten K(d) ≥ 235 nM failed to stimulate degranulation. To mimic physiological conditions, the percent of allergen specific IgE on cell surface was varied, and maximum degranulation occurred at 25% IgE(DNP). These results demonstrated that moderate hapten-IgE affinities are sufficient to trigger mast cell degranulation. Moreover, this study established the HTA design as a well-defined, controllable, and physiologically relevant experimental system to elucidate the mast cell degranulation mechanism.

Design of a heterobivalent ligand to inhibit IgE clustering on mast cells

We describe the design, synthesis, and characterization of a heterobivalent ligand (HBL) system that competitively inhibits allergen binding to mast cell bound IgE antibody, thereby inhibiting mast cell degranulation. HBLs are composed of a hapten conjugated to a nucleotide analog allowing simultaneous targeting of the antigen-binding site as well the "unconventional nucleotide binding site" on IgE Fab domains. Simultaneous bivalent binding to both sites provides HBLs with over 100-fold enhancement both in avidity for IgE(DNP) (K(d) = 0.33 μM) and in inhibition of allergen binding to IgE(DNP) (IC(50) = 0.45 μM) than the monovalent hapten (K(d)(mono) = 41 μM; IC(50)(mono) = 55.4 μM, respectively). In cellular assays, HBL2 effectively inhibits mast cell degranulation (IC(50) = 15 μM), whereas no inhibition is detected by the monovalent hapten. In conclusion, this study establishes the use of multivalency in a novel HBL design to inhibit mast cell degranulation.

The SCHOOL of nature: III. From mechanistic understanding to novel therapies

Protein-protein interactions play a central role in biological processes and thus represent an appealing target for innovative drug design and development. They can be targeted by small molecule inhibitors, modulatory peptides and peptidomimetics, which represent a superior alternative to protein therapeutics that carry many disadvantages. Considering that transmembrane signal transduction is an attractive process to therapeutically control multiple diseases, it is fundamentally and clinically important to mechanistically understand how signal transduction occurs. Uncovering specific protein-protein interactions critical for signal transduction, a general platform for receptor-mediated signaling, the signaling chain homooligomerization (SCHOOL) platform, suggests these interactions as universal therapeutic targets. Within the platform, the general principles of signaling are similar for a variety of functionally unrelated receptors. This suggests that global therapeutic strategies targeting key protein-protein interactions involved in receptor triggering and transmembrane signal transduction may be used to treat a diverse set of diseases. This also assumes that clinical knowledge and therapeutic strategies can be transferred between seemingly disparate disorders, such as T cell-mediated skin diseases and platelet disorders or combined to develop novel pharmacological approaches. Intriguingly, human viruses use the SCHOOL-like strategies to modulate and/or escape the host immune response. These viral mechanisms are highly optimized over the millennia, and the lessons learned from viral pathogenesis can be used practically for rational drug design. Proof of the SCHOOL concept in the development of novel therapies for atopic dermatitis, rheumatoid arthritis, cancer, platelet disorders and other multiple indications with unmet needs opens new horizons in therapeutics.

Modeling multivalent ligand-receptor interactions with steric constraints on configurations of cell-surface receptor aggregates

We use flow cytometry to characterize equilibrium binding of a fluorophore-labeled trivalent model antigen to bivalent IgE-FcepsilonRI complexes on RBL cells. We find that flow cytometric measurements are consistent with an equilibrium model for ligand-receptor binding in which binding sites are assumed to be equivalent and ligand-induced receptor aggregates are assumed to be acyclic. However, this model predicts extensive receptor aggregation at antigen concentrations that yield strong cellular secretory responses, which is inconsistent with the expectation that large receptor aggregates should inhibit such responses. To investigate possible explanations for this discrepancy, we evaluate four rule-based models for interaction of a trivalent ligand with a bivalent cell-surface receptor that relax simplifying assumptions of the equilibrium model. These models are simulated using a rule-based kinetic Monte Carlo approach to investigate the kinetics of ligand-induced receptor aggregation and to study how the kinetics and equilibria of ligand-receptor interaction are affected by steric constraints on receptor aggregate configurations and by the formation of cyclic receptor aggregates. The results suggest that formation of linear chains of cyclic receptor dimers may be important for generating secretory signals. Steric effects that limit receptor aggregation and transient formation of small receptor aggregates may also be important.

The SCHOOL of nature: I. Transmembrane signaling

Receptor-mediated transmembrane signaling plays an important role in health and disease. Recent significant advances in our understanding of the molecular mechanisms linking ligand binding to receptor activation revealed previously unrecognized striking similarities in the basic structural principles of function of numerous cell surface receptors. In this work, I demonstrate that the Signaling Chain Homooligomerization (SCHOOL)-based mechanism represents a general biological mechanism of transmembrane signal transduction mediated by a variety of functionally unrelated single- and multichain activating receptors. within the SCHOOL platform, ligand binding-induced receptor clustering is translated across the membrane into protein oligomerization in cytoplasmic milieu. This platform resolves a long-standing puzzle in transmembrane signal transduction and reveals the major driving forces coupling recognition and activation functions at the level of protein-protein interactions-biochemical processes that can be influenced and controlled. The basic principles of transmembrane signaling learned from the SCHOOL model can be used in different fields of immunology, virology, molecular and cell biology and others to describe, explain and predict various phenomena and processes mediated by a variety of functionally diverse and unrelated receptors. Beyond providing novel perspectives for fundamental research, the platform opens new avenues for drug discovery and development.

Quantitative mechanics of endothelial phagocytosis of silicon microparticles

Endothelia, once thought of as a barrier to the delivery of therapeutics, is now a major target for tissue-specific drug delivery. Tissue- and disease-specific molecular presentations on endothelial cells provide targets for anchoring or internalizing delivery vectors. Porous silicon delivery vectors are phagocytosed by vascular endothelial cells. The rapidity and efficiency of silicon microparticle uptake lead us to delineate the kinetics of internalization. To discriminate between surface-attached and -internalized microparticles, we developed a double fluorescent/FRET flow cytometric approach. The approach relies on quenching of antibody-conjugated fluorescein isothiocyanate covalently attached to the microparticle surface by attachment of a secondary antibody labeled with an acceptor fluorophore, phycoerythrin. The resulting half-time for microparticle internalization was 15.7 min, with confirmation provided by live confocal imaging as well as transmission electron microscopy.

Simulation of large-scale rule-based models

MOTIVATION

Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models.

RESULTS

DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein-protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of StochSim. DYNSTOC differs from StochSim by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions.

AVAILABILITY

DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at http://public.tgen.org/dynstoc/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Kinetic Monte Carlo method for rule-based modeling of biochemical networks

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.

Trivalent antigens for degranulation of mast cells

Degranulation of basophils and mast cells plays a central role in allergic reactions. Degranulation is a response to cell surface receptor aggregation caused by association of receptors with antibodies bound to multivalent antigens. Tools used in studying this process have included small-molecule divalent antigens, but they suffer from weak signaling apparently due to small aggregate size. We have prepared trivalent antigens that allow formation of larger aggregates and potent responses from mast cells.

Anti-IgE antibodies for the treatment of IgE-mediated allergic diseases

The pharmacological purposes of the anti-IgE therapy are to neutralize IgE and to inhibit its production to attenuate type I hypersensitivity reactions. The therapy is based on humanized IgG1 antibodies that bind to free IgE and to membrane-bound IgE on B cells, but not to IgE bound by the high-affinity IgE.Fc receptors on basophils and mast cells or by the low-affinity IgE.Fc receptors on B cells. After nearly 20 years since inception, therapeutic anti-IgE antibodies (anti-IgE) have been studied in about 30 Phase II and III clinical trials in many allergy indications, and a lead antibody, omalizumab, has been approved for treating patients (12 years and older) with moderate-to-severe allergic asthma. Anti-IgE has confirmed the roles of IgE in the pathogenesis of asthma and helped define the concept "allergic asthma" in clinical practice. It has been shown to be safe and efficacious in treating pediatric allergic asthma and treating allergic rhinitis and is being investigated for treating peanut allergy, atopic dermatitis, latex allergy, and others. It has potential for use to combine with specific and rush immunotherapy for increased safety and efficacy. Anti-IgE thus appears to provide a prophylactic and therapeutic option for moderate to severe cases of many allergic diseases and conditions in which IgE plays a significant role. This chapter reviews the evolution of the anti-IgE concept and the clinical studies of anti-IgE on various disease indications, and presents a comprehensive analysis on the multiple intricate immunoregulatory pharmacological effects of anti-IgE. Finally, it reviews other approaches that target IgE or IgE-expressing B cells.

A synthetic trivalent hapten that aggregates anti-2,4-DNP IgG into bicyclic trimers

This paper describes the synthesis of the trivalent hapten molecule 1, containing three 2,4-dinitrophenyl (2,4-DNP) groups, and the use of this molecule to aggregate three molecules of anti-2,4-DNP IgG into a complex with 3:2 stoichiometry (IgG312). The equilibrium product IgG312 was generated in approximately 90% yield upon mixing IgG and 1; during incubation, thermodynamically unstable, high-molecular-weight aggregates (>104 nm in diameter) form first and convert subsequently to IgG312. The thermodynamics and the kinetics of the formation of aggregates were studied using size-exclusion high-performance liquid chromatography (SE-HPLC), dynamic light scattering (DLS), and analytical ultracentrifugation (AUC). An analytical model based on multiple species in equilibrium was developed and used to interpret the SE-HPLC data. The aggregate IgG312 was more stable thermodynamically and kinetically than monomeric aggregates of this IgG with monomeric derivatives of 2,4-DNP; this stability suggests potential applications of these aggregates in biotechnology.

Rules for modeling signal-transduction systems

Formalized rules for protein-protein interactions have recently been introduced to represent the binding and enzymatic activities of proteins in cellular signaling. Rules encode an understanding of how a system works in terms of the biomolecules in the system and their possible states and interactions. A set of rules can be as easy to read as a diagrammatic interaction map, but unlike most such maps, rules have precise interpretations. Rules can be processed to automatically generate a mathematical or computational model for a system, which enables explanatory and predictive insights into the system's behavior. Rules are independent units of a model specification that facilitate model revision. Instead of changing a large number of equations or lines of code, as may be required in the case of a conventional mathematical model, a protein interaction can be introduced or modified simply by adding or changing a single rule that represents the interaction of interest. Rules can be defined and visualized by using graphs, so no specialized training in mathematics or computer science is necessary to create models or to take advantage of the representational precision of rules. Rules can be encoded in a machine-readable format to enable electronic storage and exchange of models, as well as basic knowledge about protein-protein interactions. Here, we review the motivation for rule-based modeling; applications of the approach; and issues that arise in model specification, simulation, and testing. We also discuss rule visualization and exchange and the software available for rule-based modeling.

Receptor aggregation by intermembrane interactions: a Monte Carlo study

The lateral organization of receptors on cell surfaces is critically important to their function; many receptors transmit transmembrane signals when redistributed into clusters, while the response of others is potentiated by their aggregation. Cell-cell contact can play a crucial role in receptor aggregation, even when the bonds between receptors on one cell and ligands on the other are monovalent. Monte Carlo simulations on a two-membrane model were carried out to determine whether weak enthalpic interactions among receptors in one membrane, and among ligands in another, can work synergistically to give large-scale clustering when the two membranes are brought into contact. The simulations give support to such a clustering mechanism. In addition, because clustering is a cooperative process akin to a phase separation, individual receptors and ligands may undergo repeated binding and unbinding while in a clustered "phase," and a single ligand could interact with multiple different receptor partners. The results suggest a resolution of the dichotomy between serial triggering and aggregation models of T cell activation.