Mechanisms of noncanonical binding dynamics in multivalent protein-protein interactions

A High-Avidity, Thermostable, and Low-Cost Synthetic Capture for Ultrasensitive Detection and Quantification of Viral Antigens and Aerosols

Lateral flow assays (LFAs) are currently the most popular point-of-care diagnostics, rapidly transforming disease diagnosis from expensive doctor checkups and laboratory-based tests to potential on-the-shelf commodities. Yet, their sensitive element, a monoclonal antibody, is expensive to formulate, and their long-term storage depends on refrigeration technology that cannot be met in resource-limited areas. In this work, LCB1 affibodies (antibody mimetic miniproteins) were conjugated to bovine serum albumin (BSA) to afford a high-avidity synthetic capture (LCB1-BSA) capable of detecting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and virus like particles (VLPs). Substituting the monoclonal antibody 2B04 for LCB1-BSA (stable up to 60 °C) significantly improved the thermal stability, shelf life, and affordability of plasmonic-fluor-based LFAs (p-LFAs). Furthermore, this substitution significantly improved the sensitivity of p-LFAs toward the spike protein and VLPs with precise quantitative ability over 2 and 3 orders of magnitude, respectively. LCB1-BSA sensors could detect VLPs at 100-fold lower concentrations, and this improvement, combined with their robust nature, enabled us to develop an aerosol sampling technology to detect aerosolized viral particles. Synthetic captures like LCB1-BSA can increase the ultrasensitivity, availability, sustainability, and long-term accuracy of LFAs while also decreasing their manufacturing costs.

An AAV capsid reprogrammed to bind human transferrin receptor mediates brain-wide gene delivery

Developing vehicles that efficiently deliver genes throughout the human central nervous system (CNS) will broaden the range of treatable genetic diseases. We engineered an adeno-associated virus (AAV) capsid, BI-hTFR1, that binds human transferrin receptor (TfR1), a protein expressed on the blood-brain barrier. BI-hTFR1 was actively transported across human brain endothelial cells and, relative to AAV9, provided 40 to 50 times greater reporter expression in the CNS of human TFRC knockin mice. The enhanced tropism was CNS-specific and absent in wild-type mice. When used to deliver GBA1, mutations of which cause Gaucher disease and are linked to Parkinson's disease, BI-hTFR1 substantially increased brain and cerebrospinal fluid glucocerebrosidase activity compared with AAV9. These findings establish BI-hTFR1 as a potential vector for human CNS gene therapy.

NCOA4 initiates ferritinophagy by binding GATE16 using two highly avid short linear interaction motifs

Cells carefully regulate cytosolic iron, which is a vital enzymatic cofactor, yet is toxic in excess. In mammalian cells, surplus iron is sequestered in ferritin cages that, in iron limiting conditions, are degraded through the selective autophagy pathway ferritinophagy to liberate free iron. Prior work identified the ferritinophagy receptor protein NCOA4, which links ferritin and LC3/GABARAP-family member GATE16, effectively tethering ferritin to the autophagic machinery. Here, we elucidate the molecular mechanism underlying this interaction, discovering two short linear motifs in NCOA4 that each bind GATE16 with weak affinity. These binding motifs are highly avid and, in concert, support high-affinity NCOA4•GATE16 complex formation. We further find the minimal NCOA4383-522 fragment bearing these motifs is sufficient for ferritinophagy and that both motifs are necessary for this activity. This work suggests a general mechanism wherein selective autophagy receptors can distinguish between the inactive soluble pools of LC3/GABARAPs and the active membrane-conjugated forms that drive autophagy. Finally, we find that iron decreases NCOA4383-522's affinity for GATE16, providing a plausible mechanism for iron-dependent regulation of ferritinophagy.

Coiled-coil domains are sufficient to drive liquid-liquid phase separation in protein models

Liquid-liquid phase separation (LLPS) is thought to be a main driving force in the formation of membraneless organelles. Examples of such organelles include the centrosome, central spindle, and stress granules. Recently, it has been shown that coiled-coil (CC) proteins, such as the centrosomal proteins pericentrin, spd-5, and centrosomin, might be capable of LLPS. CC domains have physical features that could make them the drivers of LLPS, but it is unknown if they play a direct role in the process. We developed a coarse-grained simulation framework for investigating the LLPS propensity of CC proteins, in which interactions that support LLPS arise solely from CC domains. We show, using this framework, that the physical features of CC domains are sufficient to drive LLPS of proteins. The framework is specifically designed to investigate how the number of CC domains, as well as the multimerization state of CC domains, can affect LLPS. We show that small model proteins with as few as two CC domains can phase separate. Increasing the number of CC domains up to four per protein can somewhat increase LLPS propensity. We demonstrate that trimer-forming and tetramer-forming CC domains have a dramatically higher LLPS propensity than dimer-forming coils, which shows that multimerization state has a greater effect on LLPS than the number of CC domains per protein. These data support the hypothesis of CC domains as drivers of protein LLPS, and have implications in future studies to identify the LLPS-driving regions of centrosomal and central spindle proteins.

Quantitative description of the phase-separation behavior of the multivalent SLP65-CIN85 complex

Biomolecular condensates play a major role in cell compartmentalization, besides membrane-enclosed organelles. The multivalent SLP65 and CIN85 proteins are proximal B-cell antigen receptor (BCR) signal effectors and critical for proper immune responses. In association with intracellular vesicles, the two effector proteins form phase separated condensates prior to antigen stimulation, thereby preparing B lymphocytes for rapid and effective activation upon BCR ligation. Within this tripartite system, 6 proline-rich motifs (PRMs) of SLP65 interact promiscuously with 3 SH3 domains of the CIN85 monomer, establishing 18 individual SH3-PRM interactions whose individual dissociation constants we determined. Based on these 18 dissociation constants, we measured the phase-separation properties of the natural SLP65/CIN85 system as well as designer constructs that emphasize the strongest SH3/PRM interactions. By modeling these various SLP65/CIN85 constructs with the program LASSI (LAttice simulation engine for Sticker and Spacer Interactions), we reproduced the observed phase-separation properties. In addition, LASSI revealed a deviation in the experimental measurement, which was independently identified as a previously unknown intramolecular interaction. Thus, thermodynamic properties of the individual PRM/SH3 interactions allow us to model the phase-separation behavior of the SLP65/CIN85 system faithfully.

An AAV capsid reprogrammed to bind human Transferrin Receptor mediates brain-wide gene delivery

Developing vehicles that efficiently deliver genes throughout the human central nervous system (CNS) will broaden the range of treatable genetic diseases. We engineered an AAV capsid, BI-hTFR1, that binds human Transferrin Receptor (TfR1), a protein expressed on the blood-brain barrier (BBB). BI-hTFR1 was actively transported across a human brain endothelial cell layer and, relative to AAV9, provided 40-50 times greater reporter expression in the CNS of human TFRC knock-in mice. The enhanced tropism was CNS-specific and absent in wild type mice. When used to deliver GBA1, mutations of which cause Gaucher disease and are linked to Parkinson's disease, BI-hTFR1 substantially increased brain and cerebrospinal fluid glucocerebrosidase activity compared to AAV9. These findings establish BI-hTFR1 as a promising vector for human CNS gene therapy.

Designing Multivalent and Multispecific Biologics

In the era of precision medicine, multivalent and multispecific therapeutics present a promising approach for targeted disease intervention. These therapeutics are designed to interact with multiple targets simultaneously, promising enhanced efficacy, reduced side effects, and resilience against drug resistance. We dissect the principles guiding the design of multivalent biologics, highlighting challenges and strategies that must be considered to maximize therapeutic effect. Engineerable elements in multivalent and multispecific biologic design-domain affinities, valency, and spatial presentation-must be considered in the context of the molecular targets as well as the balance of important properties such as target avidity and specificity. We illuminate recent applications of these principles in designing protein and cell therapies and identify exciting future directions in this field, underscored by advances in biomolecular and cellular engineering and computational approaches. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A general model for the motion of multivalent cargo interacting with substrates

Multivalent interactions are common in biology at many different length scales, and can result in the directional motion of multivalent cargo along substrates. Here, a general analytical model has been developed that can describe the directional motion of multivalent cargo as a response to position dependence in the binding and unbinding rates exhibited by their interaction sites. Cargo exhibit both an effective velocity, which acts in the direction of increasing cargo-substrate binding rate and decreasing cargo-substrate unbinding rate, and an effective diffusivity. This model can reproduce previously published experimental findings using only the binding and unbinding rate distributions of cargo interaction sites, and without any further parameter fitting. Extension of the cargo binding model to two dimensions reveals an effective velocity with the same properties as that derived for the one-dimensional case.

Programing Chemical Communication: Allostery vs Multivalent Mechanism

The emergence of life has relied on chemical communication and the ability to integrate multiple chemical inputs into a specific output. Two mechanisms are typically employed by nature to do so: allostery and multivalent activation. Although a better understanding of allostery has recently provided a variety of strategies to optimize the binding affinity, sensitivity, and specificity of molecular switches, mechanisms relying on multivalent activation remain poorly understood. As a proof of concept to compare the thermodynamic basis and design principles of both mechanisms, we have engineered a highly programmable DNA-based switch that can be triggered by either a multivalent or an allosteric DNA activator. By precisely designing the binding interface of the multivalent activator, we show that the affinity, dynamic range, and activated half-life of the molecular switch can be programed with even more versatility than when using an allosteric activator. The simplicity by which the activation properties of molecular switches can be rationally tuned using multivalent assembly suggests that it may find many applications in biosensing, drug delivery, synthetic biology, and molecular computation fields, where precise control over the transduction of binding events into a specific output is key.

The tandem EH domains of End3 cooperate to interact with dual XPF motifs of Sla1 for the connection of early and late stages in fungal endocytosis

Clathrin-mediated endocytosis (CME) is imperative for physiological processes in eukaryotic cells. In fungi, the Pan1/End3/Sla1 complex controls the transition between early and late stages of CME. Although it is acknowledged that End3 uses its N-terminal to interact with the C-terminal of Sla1, detailed mechanism remains obscure. Magnaporthe oryzae, the pathogenic fungus of rice, cause blast disease that threatens rice production worldwide. Here we report the detailed interaction mechanism between End3 and Sla1 of M. oryzae, i.e. MoEnd3 and MoSla1. The two EH domains of MoEnd3 (MoEnd3-EH1 and MoEnd3-EH2) is different both in evolution and calcium binding, but are indispensable for conformational stability of each other, an unreported effect of tandem-arranged EH domains. MoEnd3-EH1 and MoEnd3-EH2 interact with peptide MoSla1^1145-1155 containing a NPF motif with a conserved mode, and MoEnd3-EHs (containing both EH1 and EH2 domains) binds MoSla1^1145-1155 with a higher affinity, supporting the synergetic effect of EH domains. In addition, MoEnd3-EHs also recognize peptide MoSla1^971-981 with a new MPF motif that has not been reported before, while Sla1 of yeast contains a DPF motif that bears EH domain interaction ability. Collectively, our research shows that the two EH domains of End3 synergize to interact with dual XPF motifs of Sla1, which conforms to a bivalent receptor-bivalent ligand model to improve both affinity and specificity.

Facile Display of Homomultivalent Proteins for In Vitro Selections

Low-affinity protein binders are emerging as valuable domains for therapeutic applications because of their higher specificity when presented in multivalent ligands that increase the overall strength and selectivity of receptor binding. De novo discovery of low-affinity binders would be enhanced by the large library sizes attainable with in vitro selection systems, but these platforms generally maximize recovery of high-affinity monovalent binders. Here, we present a facile technology that uses rolling circle amplification to create homomultivalent libraries. We show proof of principle of this approach in ribosome display with off-rate selections of a bivalent ligand against monovalent and bivalent targets, thereby demonstrating high enrichment (up to 166-fold) against a low-affinity target that is bivalent but not monovalent. This approach to homomultivalent library construction can be applied to any binder tolerant of N- and C-terminal fusions and provides a platform for performing in vitro display selections with controlled protein valency and orientation.

Multivalent forms of the ribonuclease H1 hybrid binding domain are high-affinity binders of RNA-DNA hybrids

The hybrid binding domain (HBD) is a conserved fold present in ribonucleases H1 that selectively recognizes RNA-DNA hybrids, which are structures present in cellular R-loops and participate in diverse biological processes. We engineered multivalent HBD proteins to create high-affinity hybrid binders. Using EMSA- and SPR-based analyses, we showed that the triple-HBD protein exhibits a ~ 22 000-fold increase in hybrid affinity (K_D 370 pm) relative to the single HBD (K_D 8.29 μm), with the length and sequence of the linkers enabling optimal function. These findings provide a framework for testing models that correlate multivalency and affinity to understand how multivalent proteins function and also can serve to guide applications that exploit multivalency as a strategy to enhance binding affinity.

Multivalent binding kinetics resolved by fluorescence proximity sensing

Multivalent protein interactors are an attractive modality for probing protein function and exploring novel pharmaceutical strategies. The throughput and precision of state-of-the-art methodologies and workflows for the effective development of multivalent binders is currently limited by surface immobilization, fluorescent labelling and sample consumption. Using the gephyrin protein, the master regulator of the inhibitory synapse, as benchmark, we exemplify the application of Fluorescence proximity sensing (FPS) for the systematic kinetic and thermodynamic optimization of multivalent peptide architectures. High throughput synthesis of +100 peptides with varying combinatorial dimeric, tetrameric, and octameric architectures combined with direct FPS measurements resolved on-rates, off-rates, and dissociation constants with high accuracy and low sample consumption compared to three complementary technologies. The dataset and its machine learning-based analysis deciphered the relationship of specific architectural features and binding kinetics and thereby identified binders with unprecedented protein inhibition capacity; thus, highlighting the value of FPS for the rational engineering of multivalent inhibitors.

Fluorescence proximity sensing enables high throughput determination of binding affinities and kinetics of peptide inhibitors with varying valency and multivalent architecture.

MVsim is a toolset for quantifying and designing multivalent interactions

Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim, an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim, we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. Further, to illustrate the conceptual insights into multivalent systems that MVsim can provide, we apply it to quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim and instructional tutorials are freely available at https://sarkarlab.github.io/MVsim/ .

Multivalent protein-protein interactions are pivotal regulators of eukaryotic Hsp70 complexes

Heat shock protein 70 (Hsp70) is a molecular chaperone and central regulator of protein homeostasis (proteostasis). Paramount to this role is Hsp70's binding to client proteins and co-chaperones to produce distinct complexes, such that understanding the protein-protein interactions (PPIs) of Hsp70 is foundational to describing its function and dysfunction in disease. Mounting evidence suggests that these PPIs include both "canonical" interactions, which are universally conserved, and "non-canonical" (or "secondary") contacts that seem to have emerged in eukaryotes. These two categories of interactions involve discrete binding surfaces, such that some clients and co-chaperones engage Hsp70 with at least two points of contact. While the contributions of canonical interactions to chaperone function are becoming increasingly clear, it can be challenging to deconvolute the roles of secondary interactions. Here, we review what is known about non-canonical contacts and highlight examples where their contributions have been parsed, giving rise to a model in which Hsp70's secondary contacts are not simply sites of additional avidity but are necessary and sufficient to impart unique functions. From this perspective, we propose that further exploration of non-canonical contacts will generate important insights into the evolution of Hsp70 systems and inspire new approaches for developing small molecules that tune Hsp70-mediated proteostasis.

SRC homology 3 domains: multifaceted binding modules

The assembly of complexes following the detection of extracellular signals is often controlled by signaling proteins comprising multiple peptide binding modules. The SRC homology (SH)3 family represents the archetypical modular protein interaction module, with ~300 annotated SH3 domains in humans that regulate an impressive array of signaling processes. We review recent findings regarding the allosteric contributions of SH3 domains host protein context, their phosphoregulation, and their roles in phase separation that challenge the simple model in which SH3s are considered to be portable domains binding to specific proline-rich peptide motifs.

Modulating binding affinity, specificity and configurations by multivalent interactions

Biological functions of proteins rely on their specific interactions with binding partners. Many proteins contain multiple domains, which can bind to their targets that often have more than one binding site, resulting in multivalent interactions. While it has been shown that multivalent interactions play an crucial role in modulating binding affinity and specificity, other potential effects of multivalent interactions are less explored. Here, we developed a broadly applicable transfer matrix formalism and used it to investigate the binding of two-domain ligands to targets with multiple binding sites. We show that 1) ligands with two specific binding domains can drastically boost both the binding affinity and specificity and down-shift the working concentration range, compared to single-domain ligands, 2) the presence of a positive domain-domain cooperativity or containing a non-specific binding domain can down-shift the working concentration range of ligands by increasing the binding affinity without compromising the binding specificity, 3) the configuration of the bound ligands has a strong concentration dependence, providing important insights into the physical origin of phase-separation processes taking place in living cells. In line with previous studies, our results suggest that multivalent interactions are utilized by cells for highly efficient regulation of target binding involved in a diverse range of cellular processes such as signal transduction, gene transcription, antibody-antigen recognition.

Membrane nanodomains modulate formin condensation for actin remodeling in Arabidopsis innate immune responses

The assembly of macromolecules on the plasma membrane concentrates cell surface biomolecules into nanometer- to micrometer-scale clusters (nano- or microdomains) that help the cell initiate or respond to signals. In plant-microbe interactions, the actin cytoskeleton undergoes rapid remodeling during pathogen-associated molecular pattern-triggered immunity (PTI). The nanoclustering of formin-actin nucleator proteins at the cell surface has been identified as underlying actin nucleation during plant innate immune responses. Here, we show that the condensation of nanodomain constituents and the self-assembly of remorin proteins enables this mechanism of controlling formin condensation and activity during innate immunity in Arabidopsis thaliana. Through intrinsically disordered region-mediated remorin oligomerization and formin interaction, remorin gradually recruits and condenses formins upon PTI activation in lipid bilayers, consequently increasing actin nucleation in a time-dependent manner postinfection. Such nanodomain- and remorin-mediated regulation of plant surface biomolecules is expected to be a general feature of plant innate immune responses that creates spatially separated biochemical compartments and fine tunes membrane physicochemical properties for transduction of immune signals in the host.

A quantitative view of strategies to engineer cell-selective ligand binding

A critical property of many therapies is their selective binding to target populations. Exceptional specificity can arise from high-affinity binding to surface targets expressed exclusively on target cell types. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding strategies for developing cell-specific binding are critical to employ these tools. Here, we employ a uniquely general multivalent binding model to dissect multi-ligand and multi-receptor interactions. This model allows us to analyze and explore a series of mechanisms to engineer cell selectivity, including mixtures of molecules, affinity adjustments, valency changes, multi-specific molecules and ligand competition. Each of these strategies can optimize selectivity in distinct cases, leading to enhanced selectivity when employed together. The proposed model, therefore, provides a comprehensive toolkit for the model-driven design of selectively binding therapies.

A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors

Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model. This model predicts the behavior of a mixture of different multivalent ligand complexes binding to cells expressing various types of receptors. It accounts for the combinatorially large number of interactions between multiple ligands and receptors, optionally allowing a mixture of complexes with different valencies and complexes that contain heterogeneous ligand units. We derive the macroscopic predictions and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model thus provides an elegant and computationally efficient framework for analyzing multivalent binding.

Addition of an Fc-IgG induces receptor clustering and increases the in vitro efficacy and in vivo anti-tumor properties of the thrombospondin-1 type I repeats (3TSR) in a mouse model of advanced stage ovarian cancer

OBJECTIVES

Tumor vasculature is structurally abnormal, with anatomical deformities, reduced pericyte coverage and low tissue perfusion. As a result of this vascular dysfunction, tumors are often hypoxic, which is associated with an aggressive tumor phenotype, and reduced delivery of therapeutic compounds to the tumor. We have previously shown that a peptide containing the thrombospondin-1 type I repeats (3TSR) specifically targets tumor vessels and induces vascular normalization in a mouse model of epithelial ovarian cancer (EOC). However, due to its small size, 3TSR is rapidly cleared from circulation. We now introduce a novel construct with the 3TSR peptide fused to the C-terminus of each of the two heavy chains of the Fc region of human IgG1 (Fc3TSR). We hypothesize that Fc3TSR will have greater anti-tumor activity in vitro and in vivo compared to the native compound.

METHODS

Fc3TSR was evaluated in vitro using proliferation and apoptosis assays to investigate differences in efficacy compared to native 3TSR. In light of the multivalency of Fc3TSR, we also investigate whether it induces greater clustering of its functional receptor, CD36. We also compare the compounds in vivo using an orthotopic, syngeneic mouse model of advanced stage EOC. The impact of the two compounds on changes to tumor vasculature morphology was also investigated.

RESULTS

Fc3TSR significantly decreased the viability and proliferative potential of EOC cells and endothelial cells in vitro compared to native 3TSR. High-resolution imaging followed by image correlation spectroscopy demonstrated enhanced clustering of the CD36 receptor in cells treated with Fc3TSR. This was associated with enhanced downstream signaling and greater in vitro and in vivo cellular responses. Fc3TSR induced greater vascular normalization and disease regression compared to native 3TSR in an orthotopic, syngeneic mouse model of advanced stage ovarian cancer.

CONCLUSION

The development of Fc3TSR which is greater in size, stable in circulation and enhances receptor activation compared to 3TSR, facilitates its translational potential as a therapy in the treatment of metastatic advanced stage ovarian cancer.

Quantification of natural abundance NMR data differentiates the solution behavior of monoclonal antibodies and their fragments

Biotherapeutics are an important class of molecules for the treatment of a wide range of diseases. They include low molecular weight peptides, highly engineered protein scaffolds and monoclonal antibodies. During their discovery and development, assessments of the biophysical attributes is critical to understanding the solution behavior of therapeutic proteins and for de-risking liabilities. Thus, methods that can quantify, characterize, and provide a basis to inform risks and drive the selection of more optimal antibody and alternative scaffolds are needed. Nuclear Magnetic Resonance (NMR) spectroscopy is a technique that provides a means to probe antibody and antibody-like molecules in solution, at atomic resolution, under any formulated conditions. Here, all samples were profiled at natural abundance requiring no isotope enrichment. We present a numerical approach that quantitates two-dimensional methyl spectra. The approach was tested with a reference dataset that contained different types of antibody and antibody-like molecules. This dataset was processed through a procedure we call a Random Sampling of NMR Peaks for Covariance Analysis. This analysis revealed that the first two components were well correlated with the hydrodynamic radius of the molecules included in the reference set. Higher-order principal components were also linked to dynamic features between different tethered antibody-like molecules and contributed to decisions around candidate selection. The reference set provides a basis to characterize molecules with unknown solution behavior and is sensitive to the behavior of a molecule formulated under different conditions. The approach is independent of protein design, scaffold, formulation and provides a facile method to quantify solution behavior.

Phosphorylation-Mediated Molecular Pathway Changes in Human Pituitary Neuroendocrine Tumors Identified by Quantitative Phosphoproteomics

To investigate the biological role of protein phosphorylation in human nonfunctional pituitary neuroendocrine tumors (NF-PitNETs), proteins extracted from NF-PitNET and control tissues were analyzed with tandem mass tag (TMT)-based quantitative proteomics coupled with TiO₂ enrichment of phosphopeptides. A total of 595 differentially phosphorylated proteins (DPPs) with 1412 phosphosites were identified in NF-PitNETs compared to controls (p < 0.05). KEGG pathway network analysis of 595 DPPs identified nine statistically significant signaling pathways, including the spliceosome pathway, the RNA transport pathway, proteoglycans in cancer, SNARE interactions in vesicular transport, platelet activation, bacterial invasion of epithelial cells, tight junctions, vascular smooth muscle contraction, and protein processing in the endoplasmic reticulum. GO analysis revealed that these DPPs were involved in multiple cellular components (CCs), biological processes (BPs), and molecule functions (MFs). The kinase analysis of 595 DPPs identified seven kinases, including GRP78, WSTF, PKN2, PRP4, LOK, NEK1, and AMPKA1, and the substrate of these kinases could provide new ideas for seeking drug targets for NF-PitNETs. The randomly selected DPP calnexin was further confirmed with immunoprecipitation (IP) and Western blot (WB). These findings provide the first DPP profiling, phosphorylation-mediated molecular network alterations, and the key kinase profiling in NF-PitNET pathogenesis, which are a precious resource for understanding the biological roles of protein phosphorylation in NF-PitNET pathogenesis and discovering effective phosphoprotein biomarkers and therapeutic targets and drugs for the management of NF-PitNETs.

Label-free methods for optical in vitro characterization of protein-protein interactions

Protein-protein interactions are involved in the regulation and function of the majority of cellular processes. As a result, much effort has been aimed at the development of methodologies capable of quantifying protein-protein interactions, with label-free methods being of particular interest due to the associated simplified workflows and minimisation of label-induced perturbations. Here, we review recent advances in optical technologies providing label-free in vitro measurements of affinities and kinetics. We provide an overview and comparison of existing techniques and their principles, discussing advantages, limitations, and recent applications.

MVsim : a toolset for quantifying and designing multivalent interactions

Arising through multiple binding elements, multivalency can specify the avidity, duration, cooperativity, and selectivity of biomolecular interactions, but quantitative prediction and design of these properties has remained challenging. Here we present MVsim , an application suite built around a configurational network model of multivalency to facilitate the quantification, design, and mechanistic evaluation of multivalent binding phenomena through a simple graphical user interface. To demonstrate the utility and versatility of MVsim , we first show that both monospecific and multispecific multivalent ligand-receptor interactions, with their noncanonical binding kinetics, can be accurately simulated. We then quantitatively predict the ultrasensitivity and performance of multivalent-encoded protein logic gates, evaluate the inherent programmability of multispecificity for selective receptor targeting, and extract rate constants of conformational switching for the SARS-CoV-2 spike protein and model its binding to ACE2 as well as multivalent inhibitors of this interaction. MVsim is freely available at https://sarkarlab.github.io/MVsim/ .

Xanthomonas effector XopR hijacks host actin cytoskeleton via complex coacervation

The intrinsically disordered region (IDR) is a preserved signature of phytobacterial type III effectors (T3Es). The T3E IDR is thought to mediate unfolding during translocation into the host cell and to avoid host defense by sequence diversification. Here, we demonstrate a mechanism of host subversion via the T3E IDR. We report that the Xanthomonas campestris T3E XopR undergoes liquid-liquid phase separation (LLPS) via multivalent IDR-mediated interactions that hijack the Arabidopsis actin cytoskeleton. XopR is gradually translocated into host cells during infection and forms a macromolecular complex with actin-binding proteins at the cell cortex. By tuning the physical-chemical properties of XopR-complex coacervates, XopR progressively manipulates multiple steps of actin assembly, including formin-mediated nucleation, crosslinking of F-actin, and actin depolymerization, which occurs through competition for actin-depolymerizing factor and depends on constituent stoichiometry. Our findings unravel a sophisticated strategy in which bacterial T3E subverts the host actin cytoskeleton via protein complex coacervation.

On the specificity of protein-protein interactions in the context of disorder

With the increased focus on intrinsically disordered proteins (IDPs) and their large interactomes, the question about their specificity — or more so on their multispecificity — arise. Here we recapitulate how specificity and multispecificity are quantified and address through examples if IDPs in this respect differ from globular proteins. The conclusion is that quantitatively, globular proteins and IDPs are similar when it comes to specificity. However, compared with globular proteins, IDPs have larger interactome sizes, a phenomenon that is further enabled by their flexibility, repetitive binding motifs and propensity to adapt to different binding partners. For IDPs, this adaptability, interactome size and a higher degree of multivalency opens for new interaction mechanisms such as facilitated exchange through trimer formation and ultra-sensitivity via threshold effects and ensemble redistribution. IDPs and their interactions, thus, do not compromise the definition of specificity. Instead, it is the sheer size of their interactomes that complicates its calculation. More importantly, it is this size that challenges how we conceptually envision, interpret and speak about their specificity.

Multivalent Probes in Molecular Imaging: Reality or Future?

The rapidly developing field of molecular medical imaging focuses on specific visualization of (patho)physiological processes through the application of imaging agents (IAs) in multiple clinical modalities. Although our understanding of the principles underlying efficient IAs design has increased tremendously, many IAs still show poor in vivo imaging performance because of low binding affinity and/or specificity. These limitations can be addressed by taking advantage of multivalency, in which multiple copies of a ligand are employed to strengthen the interaction. We critically address specific challenges associated with the application of multivalent compounds in molecular imaging, and we give directions for a stepwise approach to the design of multivalent imaging probes to improve their target binding and pharmacokinetics (PK) for improved diagnostic potential.

Formin nanoclustering-mediated actin assembly during plant flagellin and DSF signaling

Plants respond to bacterial infection acutely with actin remodeling during plant immune responses. The mechanisms by which bacterial virulence factors (VFs) modulate plant actin polymerization remain enigmatic. Here, we show that plant-type-I formin serves as the molecular sensor for actin remodeling in response to two bacterial VFs: Xanthomonas campestris pv. campestris (Xcc) diffusible signal factor (DSF), and pathogen-associated molecular pattern (PAMP) flagellin in pattern-triggered immunity (PTI). Both VFs regulate actin assembly by tuning the clustering and nucleation activity of formin on the plasma membrane (PM) at the nano-sized scale. By being integrated within the cell-wall-PM-actin cytoskeleton (CW-PM-AC) continuum, the dynamic behavior and function of formins are highly dependent on each scaffold layer's composition within the CW-PM-AC continuum during both DSF and PTI signaling. Our results reveal a central mechanism for rapid actin remodeling during plant-bacteria interactions, in which bacterial signaling molecules fine tune plant formin nanoclustering in a host mechanical-structure-dependent manner.

Different phosphorylation and farnesylation patterns tune Rnd3-14-3-3 interaction in distinct mechanisms

Protein posttranslational modifications (PTMs) are often involved in the mediation or inhibition of protein-protein interactions (PPIs) within many cellular signaling pathways. Uncovering the molecular mechanism of PTM-induced multivalent PPIs is vital to understand the regulatory factors to promote inhibitor development. Herein, Rnd3 peptides with different PTM patterns as the binding epitopes and 14-3-3ζ protein were used as models to elucidate the influences of phosphorylation and farnesylation on binding thermodynamics and kinetics and their molecular mechanism. The quantitative thermodynamic results indicate that phosphorylated residues S210 and S218 (pS210 and pS218) and farnesylated C241 (fC241) enhance Rnd3-14-3-3ζ interactions in the presence of the essential pS240. However, distinct PTM patterns greatly affect the binding process. Initial association of pS240 with the phosphate-binding pocket of one monomer of the 14-3-3ζ dimer triggers the binding of pS210 or pS218 to another monomer, whereas the binding of fC241 to the hydrophobic groove on one 14-3-3ζ monomer induces the subsequent binding of pS240 to the adjacent pocket on the same monomer. Based on the experimental and molecular simulation results, we estimate that pS210/pS218 and pS240 mediate the multivalent interaction through an additive mechanism, whereas fC241 and pS240 follow an induced fit mechanism, in which the cooperativity of these two adjacent PTMs is reflected by the index ε described in our established thermodynamic binding model. Besides, these proposed binding models have been further used for describing the interaction between 14-3-3ζ and other substrates containing adjacent phosphorylation and lipidation groups, indicating their potential in general applications. These mechanistic insights are significant for understanding the regulatory factors and the design of PPI modulators.

Binding Revisited-Avidity in Cellular Function and Signaling

When characterizing biomolecular interactions, avidity, is an umbrella term used to describe the accumulated strength of multiple specific and unspecific interactions between two or more interaction partners. In contrast to the affinity, which is often sufficient to describe monovalent interactions in solution and where the binding strength can be accurately determined by considering only the relationship between the microscopic association and dissociation rates, the avidity is a phenomenological macroscopic parameter linked to several microscopic events. Avidity also covers potential effects of reduced dimensionality and/or hindered diffusion observed at or near surfaces e.g., at the cell membrane. Avidity is often used to describe the discrepancy or the "extra on top" when cellular interactions display binding that are several orders of magnitude stronger than those estimated in vitro. Here we review the principles and theoretical frameworks governing avidity in biological systems and the methods for predicting and simulating avidity. While the avidity and effects thereof are well-understood for extracellular biomolecular interactions, we present here examples of, and discuss how, avidity and the underlying kinetics influences intracellular signaling processes.