Showing papers on "Protein–protein interaction published in 2019"

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation.

Abstract: The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Real-time measurement of protein-protein interactions at single-molecule resolution using a biological nanopore.

Abstract: Protein-protein interactions (PPIs) are essential for many cellular processes. However, transient PPIs are difficult to measure at high throughput or in complex biological fluids using existing methods. We engineered a genetically encoded sensor for real-time sampling of transient PPIs at single-molecule resolution. Our sensor comprises a truncated outer membrane protein pore, a flexible tether, a protein receptor and a peptide adaptor. When a protein ligand present in solution binds to the receptor, reversible capture and release events of the receptor can be measured as current transitions between two open substates of the pore. Notably, the binding and release of the receptor by a protein ligand can be unambiguously discriminated in a complex sample containing fetal bovine serum. Our selective nanopore sensor could be applied for single-molecule protein detection, could form the basis for a nanoproteomics platform or might be adapted to build tools for protein profiling and biomarker discovery.

Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains.

Abstract: Proteins interact with a variety of molecules including proteins and nucleic acids. We review a comprehensive collection of over 50 studies that analyze and/or predict these interactions. While majority of these studies address either solely protein-DNA or protein-RNA binding, only a few have a wider scope that covers both protein-protein and protein-nucleic acid binding. Our analysis reveals that binding residues are typically characterized with three hallmarks: relative solvent accessibility (RSA), evolutionary conservation and propensity of amino acids (AAs) for binding. Motivated by drawbacks of the prior studies, we perform a large-scale analysis to quantify and contrast the three hallmarks for residues that bind DNA-, RNA-, protein- and (for the first time) multi-ligand-binding residues that interact with DNA and proteins, and with RNA and proteins. Results generated on a well-annotated data set of over 23 000 proteins show that conservation of binding residues is higher for nucleic acid- than protein-binding residues. Multi-ligand-binding residues are more conserved and have higher RSA than single-ligand-binding residues. We empirically show that each hallmark discriminates between binding and nonbinding residues, even predicted RSA, and that combining them improves discriminatory power for each of the five types of interactions. Linear scoring functions that combine these hallmarks offer good predictive performance of residue-level propensity for binding and provide intuitive interpretation of predictions. Better understanding of these residue-level interactions will facilitate development of methods that accurately predict binding in the exponentially growing databases of protein sequences.

Mechanistic Insights into Specific G Protein Interactions with Adenosine Receptors

Abstract: Coupling between G-protein-coupled receptors (GPCRs) and the G proteins is a key step in cellular signaling. Despite extensive experimental and computational studies, the mechanism of specific GPCR-G protein coupling remains poorly understood. This has greatly hindered effective drug design of GPCRs that are primary targets of ∼1/3 of currently marketed drugs. Here, we have employed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method to decipher the mechanism of the GPCR-G protein interactions. Adenosine receptors (ARs) were used as model systems based on very recently determined cryo-EM structures of the A1AR and A2AAR coupled with the Gi and Gs proteins, respectively. Changing the Gi protein to the Gs led to increased fluctuations in the A1AR and agonist adenosine (ADO), while agonist 5'-N-ethylcarboxamidoadenosine (NECA) binding in the A2AAR could be still stabilized upon changing the Gs protein to the Gi. Free energy calculations identified one stable low-energy conformation for each of the A1AR-Gi and A2AAR-Gs complexes as in the cryo-EM structures, similarly for the A2AAR-Gi complex. In contrast, the ADO agonist and Gs protein sampled multiple conformations in the A1AR-Gs system. GaMD simulations thus indicated that the A1AR preferred to couple with the Gi protein to the Gs, while the A2AAR could couple with both the Gs and Gi proteins, being highly consistent with experimental findings of the ARs. More importantly, detailed analysis of the atomic simulations showed that the specific AR-G protein coupling resulted from remarkably complementary residue interactions at the protein interface, involving mainly the receptor transmembrane 6 helix and the Gα α5 helix and α4-β6 loop. In summary, the GaMD simulations have provided unprecedented insights into the dynamic mechanism of specific GPCR-G protein interactions at an atomistic level.

Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein–protein interactions ready for it?

Abstract: Predicting the structure and thermodynamics of protein–protein interactions (PPIs) are key to a proper understanding and modulation of their function. Since experimental methods might not be able to catch up with the fast growth of genomic data, computational alternatives are therefore required. We present here a review dealing with various aspects of predicting binding affinity changes upon mutations (ΔΔG). We focus on predictors that consider three‐dimensional structure information to estimate the impact of mutations on the binding affinity of a protein–protein complex, excluding the rigorous free energy perturbation methods. Training and evaluation, ΔΔG databases, data selection, and existing ΔΔG predictors are specially emphasized. We also establish the parallel with scoring functions used in docking since those share many similar PPI features with ΔΔG predictors. The field has seen a common evolution of ΔΔG predictors and scoring functions over time, transforming from purely energetic functions to statistical energy‐based and further to machine learning‐based functions. As machine learning has come to age, limitations in terms of quantity, quality and variety of the available data become the bottlenecks for the future development of these computational methods. This can be alleviated by building infrastructures for data generation, collection and sharing. Further developments can be catalyzed by conducting community‐wide blind challenges for method assessment.

Human cytomegalovirus interactome analysis identifies degradation hubs, domain associations and viral protein functions

Abstract: Human cytomegalovirus (HCMV) extensively modulates host cells, downregulating >900 human proteins during viral replication and degrading ≥133 proteins shortly after infection. The mechanism of degradation of most host proteins remains unresolved, and the functions of many viral proteins are incompletely characterised. We performed a mass spectrometry-based interactome analysis of 169 tagged, stably-expressed canonical strain Merlin HCMV proteins, and two non-canonical HCMV proteins, in infected cells. This identified a network of >3,400 virus-host and >150 virus-virus protein interactions, providing insights into functions for multiple viral genes. Domain analysis predicted binding of the viral UL25 protein to SH3 domains of NCK Adaptor Protein-1. Viral interacting proteins were identified for 31/133 degraded host targets. Finally, the uncharacterised, non-canonical ORFL147C protein was found to interact with elements of the mRNA splicing machinery, and a mutational study suggested its importance in viral replication. The interactome data will be important for future studies of herpesvirus infection.

Site-Directed Fragment-Based Screening for the Discovery of Protein-Protein Interaction Stabilizers.

Abstract: Modulation of protein–protein interactions (PPIs) by small molecules has emerged as a valuable approach in drug discovery. Compared to direct inhibition, PPI stabilization is vastly underexplored but has strong advantages, including the ability to gain selectivity by targeting an interface formed only upon association of proteins. Here, we present the application of a site-directed screening technique based on disulfide trapping (tethering) to select for fragments that enhance the affinity between protein partners. We target the phosphorylation-dependent interaction between the hub protein 14-3-3σ and a peptide derived from Estrogen Receptor α (ERα), an important breast cancer target that is negatively regulated by 14-3-3σ. We identify orthosteric stabilizers that increase 14-3-3/ERα affinity up to 40-fold and propose the mechanism of stabilization based on X-ray crystal structures. These fragments already display partial selectivity toward ERα-like motifs over other representative 14-3-3 clients. This fi...

A Comparative Assessment Study of Known Small-Molecule Keap1-Nrf2 Protein-Protein Interaction Inhibitors: Chemical Synthesis, Binding Properties, and Cellular Activity.

Abstract: Inhibiting the protein–protein interaction (PPI) between the transcription factor Nrf2 and its repressor protein Keap1 has emerged as a promising strategy to target oxidative stress in diseases, including central nervous system (CNS) disorders. Numerous non-covalent small-molecule Keap1−Nrf2 PPI inhibitors have been reported to date, but many feature suboptimal physicochemical properties for permeating the blood–brain barrier, while others contain problematic structural moieties. Here, we present the first side-by-side assessment of all reported Keap1−Nrf2 PPI inhibitor classes using fluorescence polarization, thermal shift assay, and surface plasmon resonance—and further evaluate the compounds in an NQO1 induction cell assay and in counter tests for nonspecific activities. Surprisingly, half of the compounds were inactive or deviated substantially from reported activities, while we confirm the cross-assay activities for others. Through this study, we have identified the most promising Keap1−Nrf2 inhibito...

Inhibition of β-catenin/B cell lymphoma 9 protein−protein interaction using α-helix–mimicking sulfono-γ-AApeptide inhibitors

Abstract: The rational design of α-helix–mimicking peptidomimetics provides a streamlined approach to discover potent inhibitors for protein−protein interactions (PPIs). However, designing cell-penetrating long peptidomimetic scaffolds equipped with various functional groups necessary for interacting with large protein-binding interfaces remains challenging. This is particularly true for targeting β-catenin/BCL9 PPIs. Here we designed a series of unprecedented helical sulfono-γ-AApeptides that mimic the binding mode of the α-helical HD2 domain of B Cell Lymphoma 9 (BCL9). Our studies show that sulfono-γ-AApeptides can structurally and functionally mimic the α-helical domain of BCL9 and selectively disrupt β-catenin/BCL9 PPIs with even higher potency. More intriguingly, these sulfono-γ-AApeptides can enter cancer cells, bind with β-catenin and disrupt β-catenin/BCL9 PPIs, and exhibit excellent cellular activity, which is much more potent than the BCL9 peptide. Furthermore, our enzymatic stability studies demonstrate the remarkable stability of the helical sulfono-γ-AApeptides, with no degradation in the presence of pronase for 24 h, augmenting their biological potential. This work represents not only an example of helical sulfono-γ-AApeptides that mimic α-helix and disrupt protein–protein interactions, but also an excellent example of potent, selective, and cell-permeable unnatural foldameric peptidomimetics that disrupt the β-catenin/BCL9 PPI. The design of helical sulfono-γ-AApeptides may lead to a new strategy to modulate a myriad of protein–protein interactions.

Relative interfacial cleavage energetics of protein complexes revealed by surface collisions.

Abstract: To fulfill their biological functions, proteins must interact with their specific binding partners and often function as large assemblies composed of multiple proteins or proteins plus other biomolecules. Structural characterization of these complexes, including identification of all binding partners, their relative binding affinities, and complex topology, is integral for understanding function. Understanding how proteins assemble and how subunits in a complex interact is a cornerstone of structural biology. Here we report a native mass spectrometry (MS)-based method to characterize subunit interactions in globular protein complexes. We demonstrate that dissociation of protein complexes by surface collisions, at the lower end of the typical surface-induced dissociation (SID) collision energy range, consistently cleaves the weakest protein:protein interfaces, producing products that are reflective of the known structure. We present here combined results for multiple complexes as a training set, two validation cases, and four computational models. We show that SID appearance energies can be predicted from structures via a computationally derived expression containing three terms (number of residues in a given interface, unsatisfied hydrogen bonds, and a rigidity factor).

In-solution enrichment identifies peptide inhibitors of protein-protein interactions.

Abstract: The use of competitive inhibitors to disrupt protein–protein interactions (PPIs) holds great promise for the treatment of disease. However, the discovery of high-affinity inhibitors can be a challenge. Here we report a platform for improving the affinity of peptide-based PPI inhibitors using non-canonical amino acids. The platform utilizes size exclusion-based enrichment from pools of synthetic peptides (1.5–4 kDa) and liquid chromatography-tandem mass spectrometry-based peptide sequencing to identify high-affinity binders to protein targets, without the need for ‘reporter’ or ‘encoding’ tags. Using this approach—which is inherently selective for high-affinity binders—we realized gains in affinity of up to ~100- or ~30-fold for binders to the oncogenic ubiquitin ligase MDM2 or HIV capsid protein C-terminal domain, which inhibit MDM2–p53 interaction or HIV capsid protein C-terminal domain dimerization, respectively. Subsequent macrocyclization of select MDM2 inhibitors rendered them cell permeable and cytotoxic toward cancer cells, demonstrating the utility of the identified compounds as functional PPI inhibitors. Affinity-based selection in solution enables the identification of high-affinity ligands for disrupting the MDM2–p53 interaction and binding to the HIV capsid protein from libraries of both linear and cyclic peptides containing non-canonical amino acids.

Structure-Activity and Structure-Conformation Relationships of Aryl Propionic Acid Inhibitors of the Kelch-like ECH-Associated Protein 1/Nuclear Factor Erythroid 2-Related Factor 2 (KEAP1/NRF2) Protein-Protein Interaction.

Abstract: The KEAP1-NRF2-mediated cytoprotective response plays a key role in cellular homoeostasis. Insufficient NRF2 signaling during chronic oxidative stress may be associated with the pathophysiology of several diseases with an inflammatory component, and pathway activation through direct modulation of the KEAP1-NRF2 protein-protein interaction is being increasingly explored as a potential therapeutic strategy. Nevertheless, the physicochemical nature of the KEAP1-NRF2 interface suggests that achieving high affinity for a cell-penetrant druglike inhibitor might be challenging. We recently reported the discovery of a highly potent tool compound which was used to probe the biology associated with directly disrupting the interaction of NRF2 with the KEAP1 Kelch domain. We now present a detailed account of the medicinal chemistry campaign leading to this molecule, which included exploration and optimization of protein-ligand interactions in three energetic "hot spots" identified by fragment screening. In particular, we also discuss how consideration of ligand conformational stabilization was important to its development and present evidence for preorganization of the lead compound which may contribute to its high affinity and cellular activity.

Multi-functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder-based proteoforms

Abstract: GPCR-G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signaling cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand-GPCR and GPCR-G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defines an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR-G protein system represents an illustrative example of the protein structure-function continuum, where structures of the involved proteins represent a complex mosaic of differently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fine-tuned by various post-translational modifications and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specific partners. In other words, GPCRs and G proteins exist as sets of conformational/basic, inducible/modified, and functioning proteoforms characterized by a broad spectrum of structural features and possessing various functional potentials.

Proximity-dependent biotinylation mediated by TurboID to identify protein–protein interaction networks in yeast

Abstract: The use of proximity-dependent biotinylation assays coupled to mass spectrometry (PDB-MS) has changed the field of protein-protein interaction studies. However, despite the recurrent and successful use of BioID-based protein-protein interactions screening in mammalian cells, the implementation of PDB-MS in yeast has not been effective. Here, we report a simple and rapid approach in yeast to effectively screen for proximal and interacting proteins in their natural cellular environment by using TurboID, a recently described version of the BirA biotin ligase. Using the protein arginine methyltransferase Rmt3 and the RNA exosome subunits, Rrp6 and Dis3, the application of PDB-MS in yeast by using TurboID was able to recover protein-protein interactions previously identified using other biochemical approaches and provided new complementary information for a given protein bait. The development of a rapid and effective PDB assay that can systematically analyze protein-protein interactions in living yeast cells opens the way for large-scale proteomics studies in this powerful model organism.

LYK4 is a component of a tripartite chitin receptor complex in Arabidopsis thaliana

Abstract: LysM receptor-like kinases (LYKs) of Arabidopsis thaliana (namely LYK1, LYK4 and LYK5) play a major role in chitin perception and immunity against pathogenic fungi. Chitin-induced heterodimerization of LYK1 and LYK5 has been previously reported, but protein interaction partners of LYK4 have not yet been identified. In this study, by analysing mutants we confirmed a role of LYK4 in chitin perception, and found that the ectodomain of LYK4 homodimerizes and also interacts with the ectodomain of LYK5 in vitro. Pull-down experiments with proteins expressed in protoplasts indicated LYK4-LYK4 and LY4-LYK5 interactions in planta. When protoplasts were treated with chitoheptaose or chitin, a protein complex was immunoprecipitated that appeared to be composed of LYK1, LYK4, and LYK5. Similar experiments with proteins expressed in lyk mutant plants suggested that elicitor treatment induced a physical interaction between LYK1 and LYK5 but not between LYK1 and LYK4. Bimolecular fluorescence complementation experiments substantiated these findings. Overall, our data suggest that LYK4 functions as a LYK5-associated co-receptor or scaffold protein that enhances chitin-induced signaling in Arabidopsis.

N-terminal β-strand underpins biochemical specialization of an ATG8 isoform.

Abstract: Autophagy-related protein 8 (ATG8) is a highly conserved ubiquitin-like protein that modulates autophagy pathways by binding autophagic membranes and a number of proteins, including cargo receptors and core autophagy components. Throughout plant evolution, ATG8 has expanded from a single protein in algae to multiple isoforms in higher plants. However, the degree to which ATG8 isoforms have functionally specialized to bind distinct proteins remains unclear. Here, we describe a comprehensive protein-protein interaction resource, obtained using in planta immunoprecipitation (IP) followed by mass spectrometry (MS), to define the potato ATG8 interactome. We discovered that ATG8 isoforms bind distinct sets of plant proteins with varying degrees of overlap. This prompted us to define the biochemical basis of ATG8 specialization by comparing two potato ATG8 isoforms using both in vivo protein interaction assays and in vitro quantitative binding affinity analyses. These experiments revealed that the N-terminal β-strand-and, in particular, a single amino acid polymorphism-underpins binding specificity to the substrate PexRD54 by shaping the hydrophobic pocket that accommodates this protein's ATG8-interacting motif (AIM). Additional proteomics experiments indicated that the N-terminal β-strand shapes the broader ATG8 interactor profiles, defining interaction specificity with about 80 plant proteins. Our findings are consistent with the view that ATG8 isoforms comprise a layer of specificity in the regulation of selective autophagy pathways in plants.

Yeast Two-Hybrid Assay to Identify Interacting Proteins.

Abstract: This article describes the general method to perform the classical two-hybrid system. Although it has already been more than 25 years since this technique was developed, it still represents one of the best and most inexpensive, time saving, and straightforward methods to identify and study protein-protein interactions. Indeed, this system can be easily used to identify interacting proteins for a given protein, to check interactions between two known proteins, or to map interacting domains. Most of the interactions revealed using the two-hybrid assay have been proven to be binary direct interactions. Data comparison with other systems, such as mass spectrometry, have demonstrated that this system is at least as reliable. In fact, its use is increasing with time, and at present numerous variants of the yeast two-hybrid assay have been developed, including high-throughput systems that promote the generation of a proteome-scale map of protein-protein interactions in specific system. © 2018 by John Wiley & Sons, Inc.

Intrinsic disorder associated with 14-3-3 proteins and their partners.

Abstract: Protein-protein interactions (PPIs) mediate a variety of cellular processes and form complex networks, where connectivity is achieved owing to the "hub" proteins whose interaction with multiple protein partners is facilitated by the intrinsically disordered protein regions (IDPRs) and posttranslational modifications (PTMs). Universal regulatory proteins of the eukaryotic 14-3-3 family nicely exemplify these concepts and are the focus of this chapter. The extremely wide interactome of 14-3-3 proteins is characterized by high levels of intrinsic disorder (ID) enabling protein phosphorylation and consequent specific binding to the well-structured 14-3-3 dimers, one of the first phosphoserine/phosphothreonine binding modules discovered. However, high ID enrichment also challenges structural studies, thereby limiting the progress in the development of small molecule modulators of the key 14-3-3 PPIs of increased medical importance. Besides the well-known structural flexibility of their variable C-terminal tails, recent studies revealed the strong and conserved ID propensity hidden in the N-terminal segment of 14-3-3 proteins (~40 residues), normally forming the α-helical dimerization region, that may have a potential role for the dimer/monomer dynamics and recently reported moonlighting chaperone-like activity of these proteins. We review the role of ID in the 14-3-3 structure, their interactome, and also in selected 14-3-3 complexes. In addition, we discuss approaches that, in the future, may help minimize the disproportion between the large amount of known 14-3-3 partners and the small number of 14-3-3 complexes characterized with atomic precision, to unleash the whole potential of 14-3-3 PPIs as drug targets.

Effect of protein–protein interactions and solvent viscosity on the rotational diffusion of proteins in crowded environments

Abstract: The rotational diffusion of a protein in the presence of protein crowder molecules was analyzed via computer simulations. Cluster formation as a result of transient intermolecular contacts was identified as the dominant effect for reduced rotational diffusion upon crowding. The slow-down in diffusion was primarily correlated with direct protein–protein contacts rather than indirect interactions via shared hydration layers. But increased solvent viscosity due to crowding contributed to a lesser extent. Key protein–protein contacts correlated with a slow-down in diffusion involve largely interactions between charged and polar groups suggesting that the surface composition of a given protein and the resulting propensity for forming interactions with surrounding proteins in a crowded cellular environment may be the major determinant of its diffusive properties.

Alterations of the interactome of Bcl-2 proteins in breast cancer at the transcriptional, mutational and structural level.

Abstract: Apoptosis is an essential defensive mechanism against tumorigenesis. Proteins of the B-cell lymphoma-2 (Bcl-2) family regulate programmed cell death by the mitochondrial apoptosis pathway. In response to intracellular stress, the apoptotic balance is governed by interactions of three distinct subgroups of proteins; the activator/sensitizer BH3 (Bcl-2 homology 3)-only proteins, the pro-survival, and the pro-apoptotic executioner proteins. Changes in expression levels, stability, and functional impairment of pro-survival proteins can lead to an imbalance in tissue homeostasis. Their overexpression or hyperactivation can result in oncogenic effects. Pro-survival Bcl-2 family members carry out their function by binding the BH3 short linear motif of pro-apoptotic proteins in a modular way, creating a complex network of protein-protein interactions. Their dysfunction enables cancer cells to evade cell death. The critical role of Bcl-2 proteins in homeostasis and tumorigenesis, coupled with mounting insight in their structural properties, make them therapeutic targets of interest. A better understanding of gene expression, mutational profile, and molecular mechanisms of pro-survival Bcl-2 proteins in different cancer types, could help to clarify their role in cancer development and may guide advancement in drug discovery. Here, we shed light on the pro-survival Bcl-2 proteins in breast cancer using different bioinformatic approaches, linking -omics with structural data. We analyzed the changes in the expression of the Bcl-2 proteins and their BH3-containing interactors in breast cancer samples. We then studied, at the structural level, a selection of interactions, accounting for effects induced by mutations found in the breast cancer samples. We find two complexes between the up-regulated Bcl2A1 and two down-regulated BH3-only candidates (i.e., Hrk and Nr4a1) as targets associated with reduced apoptosis in breast cancer samples for future experimental validation. Furthermore, we predict L99R, M75R as damaging mutations altering protein stability, and Y120C as a possible allosteric mutation from an exposed surface to the BH3-binding site.

Guiding Biomolecular Interactions in Cells Using de Novo Protein-Protein Interfaces

Abstract: An improved ability to direct and control biomolecular interactions in living cells would have an impact on synthetic biology. A key issue is the need to introduce interacting components that act orthogonally to endogenous proteomes and interactomes. Here, we show that low-complexity, de novo designed protein-protein interaction (PPI) domains can substitute for natural PPIs and guide engineered protein-DNA interactions in Escherichia coli. Specifically, we use de novo homo- and heterodimeric coiled coils to reconstitute a cytoplasmic split adenylate cyclase, recruit RNA polymerase to a promoter and activate gene expression, and oligomerize both natural and designed DNA-binding domains to repress transcription. Moreover, the stabilities of the heterodimeric coiled coils can be modulated by rational design and, thus, adjust the levels of gene activation and repression in vivo. These experiments demonstrate the possibilities for using designed proteins and interactions to control biomolecular systems such as enzyme cascades and circuits in cells.

Mechanisms of noncanonical binding dynamics in multivalent protein-protein interactions.

Abstract: Protein multivalency can provide increased affinity and specificity relative to monovalent counterparts, but these emergent biochemical properties and their mechanistic underpinnings are difficult to predict as a function of the biophysical properties of the multivalent binding partners. Here, we present a mathematical model that accurately simulates binding kinetics and equilibria of multivalent protein–protein interactions as a function of the kinetics of monomer–monomer binding, the structure and topology of the multidomain interacting partners, and the valency of each partner. These properties are all experimentally or computationally estimated a priori, including approximating topology with a worm-like chain model applicable to a variety of structurally disparate systems, thus making the model predictive without parameter fitting. We conceptualize multivalent binding as a protein–protein interaction network: ligand and receptor valencies determine the number of interacting species in the network, with monomer kinetics and structural properties dictating the dynamics of each species. As predicted by the model and validated by surface plasmon resonance experiments, multivalent interactions can generate several noncanonical macroscopic binding dynamics, including a transient burst of high-energy configurations during association, biphasic equilibria resulting from interligand competition at high concentrations, and multiexponential dissociation arising from differential lifetimes of distinct network species. The transient burst was only uncovered when extending our analysis to trivalent interactions due to the significantly larger network, and we were able to predictably tune burst magnitude by altering linker rigidity. This study elucidates mechanisms of multivalent binding and establishes a framework for model-guided analysis and engineering of such interactions.

Topological Scoring of Protein Interaction Networks

Abstract: It remains a significant challenge to define individual protein associations within networks where an individual protein can directly interact with other proteins and/or be part of large complexes, which contain functional modules. Here we demonstrate the topological scoring (TopS) algorithm for the analysis of quantitative proteomic datasets from affinity purifications. Data is analyzed in a parallel fashion where a prey protein is scored in an individual affinity purification by aggregating information from the entire dataset. Topological scores span a broad range of values indicating the enrichment of an individual protein in every bait protein purification. TopS is applied to interaction networks derived from human DNA repair proteins and yeast chromatin remodeling complexes. TopS highlights potential direct protein interactions and modules within complexes. TopS is a rapid method for the efficient and informative computational analysis of datasets, is complementary to existing analysis pipelines, and provides important insights into protein interaction networks. Inferring direct protein−protein interactions (PPIs) and modules in PPI networks remains a challenge. Here, the authors introduce an algorithm to infer potential direct PPIs from quantitative proteomic AP-MS data by identifying enriched interactions of each bait relative to the other baits.

Intramolecular domain dynamics regulate synaptic MAGUK protein interactions.

Abstract: PSD-95 MAGUK family scaffold proteins are multi-domain organisers of synaptic transmission that contain three PDZ domains followed by an SH3-GK domain tandem. This domain architecture allows coordinated assembly of protein complexes composed of neurotransmitter receptors, synaptic adhesion molecules and downstream signalling effectors. Here we show that binding of monomeric CRIPT-derived PDZ3 ligands to the third PDZ domain of PSD-95 induces functional changes in the intramolecular SH3-GK domain assembly that influence subsequent homotypic and heterotypic complex formation. We identify PSD-95 interactors that differentially bind to the SH3-GK domain tandem depending on its conformational state. Among these interactors, we further establish the heterotrimeric G protein subunit Gnb5 as a PSD-95 complex partner at dendritic spines of rat hippocampal neurons. The PSD-95 GK domain binds to Gnb5, and this interaction is triggered by CRIPT-derived PDZ3 ligands binding to the third PDZ domain of PSD-95, unraveling a hierarchical binding mechanism of PSD-95 complex formation.

Analysis of Protein-Protein Interaction in a Single Live Cell by Using a FRET System Based on Genetic Code Expansion Technology.

Abstract: Hsp70 is known to directly bind to Bax for suppression of apoptosis. However, mechanisms on how Bax is dissociated from its complex with Hsp70 during apoptosis remain largely unknown. In the current study, we developed the efficient fluorescence resonance energy transfer (FRET) system which consisted of Hsp70-YFP and fluorescent amino acid (ANAP)-incorporated Bax, which was generated by using genetic code expansion technology, and applied the FRET system to elucidate mechanisms on how apoptosis-inducing substances dissociate Bax from Hsp70. Time-dependent analysis of single live cell images showed that Bax activators binding to Bax trigger sites inhibited the Bax-Hsp70 interaction but a Bax activator, which blocks phosphorylation of S184 via binding to the C-terminal S184 site, did not affect this interaction. Additionally, an inhibitor for Hsp70-Hsp40 interaction blocked the Bax-Hsp70 interaction. Furthermore, p53 activators promoted the dissociation of Bax from Hsp70 by reactivating p53 which disrupted the Bax-Hsp70 interaction. We also found that death ligands and a Bcl-2 inhibitor enhanced the dissociation of Bax from Hsp70 by activating activator BH3-only proteins. Results from this effort suggest that FRET systems consisting of the ANAP-incorporated protein and the YFP fusion protein will be valuable tools to gain an understanding of other types of protein-protein interactions.

Isothermal Titration Calorimetry Assays to Measure Binding Affinities In Vitro.

Abstract: In the study of the Hippo signal transduction pathway, protein-protein interactions are often explored, because various proteins such as MOB1, NDR1/NDR2, and LATS1/LATS2 are very important members in this complicated signaling pathway. The transduction of signals from upstream to downstream is largely dependent on the mutual recognition of proteins and the formation of specific non-covalent complexes between them. In general, protein-protein associations, protein-DNA associations, or protein-small molecule associations cause the release or absorption of heat during the association reaction. The isothermal titration calorimetry (ITC) assay is a convenient and widely used approach to directly measure the amount of heat released or absorbed during association processes of biomolecules (such as protein-protein, protein-DNA, or protein-small molecules) in solution and to quantitatively estimate the interaction affinity.

Dissecting FOXP2 Oligomerization and DNA Binding.

Abstract: Protein-protein and protein-substrate interactions are critical to function and often depend on factors that are difficult to disentangle. Herein, a combined biochemical and biophysical approach, based on electrically switchable DNA biochips and single-molecule mass analysis, was used to characterize the DNA binding and protein oligomerization of the transcription factor, forkhead box protein P2 (FOXP2). FOXP2 contains domains commonly involved in nucleic-acid binding and protein oligomerization, such as a C2 H2 -zinc finger (ZF), and a leucine zipper (LZ), whose roles in FOXP2 remain largely unknown. We found that the LZ mediates FOXP2 dimerization via coiled-coil formation but also contributes to DNA binding. The ZF contributes to protein dimerization when the LZ coiled-coil is intact, but it is not involved in DNA binding. The forkhead domain (FHD) is the key driver of DNA binding. Our data contributes to understanding the mechanisms behind the transcriptional activity of FOXP2.