Characterization Of Protein-protein Interactions Research Articles

Assessing the safety of bedaquiline: insight from adverse event reporting system analysis.

The development and marketing of Bedaquiline (BDQ) represent significant advancements in treating tuberculosis, particularly multidrug-resistant forms. However, comprehensive research into BDQ's real-world safety remains limited. We obtained BDQ related adverse event (AE) information from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to assess its safety and inform drug usage. The AE data for BDQ from 2012 Q4 to 2023 Q3 was collected and standardized. Disproportionality analysis, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagation Neural Network (BCPNN) was used to quantify signals of BDQ-related AEs. Logistic regression was used to analyze the individual data of hepatotoxicity and drug-induced liver injury, and multiple linear regression models were established. Additionally, network pharmacology was employed to identify the potential biological mechanisms of BDQ-induced liver injury. We identified 2017 case reports directly related to BDQ. Our analysis identified 341 Preferred Terms (PTs) characterizing these AEs across 27 System Organ Classes (SOC). An important discovery was the identification of AEs associated with ear and labyrinth disorders, which had not been documented in the drug's official leaflet before. Subgroup analysis revealed a negative correlation between BDQ-related liver injury and females (OR: 0.4, 95%CI: 0.3-0.6). In addition, via network pharmacology approach, a total of 76 potential targets for BDQ related liver injury were predicted, and 11 core target genes were selected based on the characterization of protein-protein interactions. The pathway linked to BDQ-induced liver injury was identified, and it was determined that the PI3K-Akt signaling pathway contained the highest number of associated genes. The analysis of the FAERS database revealed adverse events linked to BDQ, prompting the use of a network pharmacology approach to study the potential molecular mechanism of BDQ-induced liver injury. These findings emphasized the significance of drug safety and offered understanding into the mechanisms behind BDQ-induced liver injury. BDQ demonstrated distinct advantages, including reduced incidence of certain adverse events compared to traditional treatments such as injectable agents and second-line drugs. However, it is important to acknowledge the limitations of this analysis, including potential underreporting and confounding factors. This study provides valuable insights into the safety of BDQ and its role in the management of MDR-TB, emphasizing the need for continued surveillance and monitoring to ensure its safe and effective use.

ReLo is a simple and rapid colocalization assay to identify and characterize direct protein–protein interactions

The characterization of protein-protein interactions (PPIs) is fundamental to the understanding of biochemical processes. Many methods have been established to identify and study direct PPIs; however, screening and investigating PPIs involving large or poorly soluble proteins remains challenging. Here, we introduce ReLo, a simple, rapid, and versatile cell culture-based method for detecting and investigating interactions in a cellular context. Our experiments demonstrate that ReLo specifically detects direct binary PPIs. Furthermore, we show that ReLo bridging experiments can also be used to determine the binding topology of subunits within multiprotein complexes. In addition, ReLo facilitates the identification of protein domains that mediate complex formation, allows screening for interfering point mutations, and it is sensitive to drugs that mediate or disrupt an interaction. In summary, ReLo is a simple and rapid alternative for the study of PPIs, especially when studying structurally complex proteins or when established methods fail.

Exploring single-molecule interactions: heparin and FGF-1 proteins through solid-state nanopores.

Detection and characterization of protein-protein interactions are essential for many cellular processes, such as cell growth, tissue repair, drug delivery, and other physiological functions. In our research, we have utilized emerging solid-state nanopore sensing technology, which is highly sensitive to better understand heparin and fibroblast growth factor 1 (FGF-1) protein interactions at a single-molecule level without any modifications. Understanding the structure and behavior of heparin-FGF-1 complexes at the single-molecule level is very important. An abnormality in their formation can lead to life-threatening conditions like tumor growth, fibrosis, and neurological disorders. Using a controlled dielectric breakdown pore fabrication approach, we have characterized individual heparin and FGF-1 (one of the 22 known FGFs in humans) proteins through the fabrication of 17 ± 1 nm nanopores. Compared to heparin, the positively charged heparin-binding domains of some FGF-1 proteins translocationally react with the pore walls, giving rise to a distinguishable second peak with higher current blockade. Additionally, we have confirmed that the dynamic FGF-1 is stabilized upon binding with heparin-FGF-1 at the single-molecule level. The larger current blockades from the complexes relative to individual heparin and the FGF-1 recorded during the translocation ensure the binding of heparin-FGF-1 proteins, forming binding complexes with higher excluded volumes. Taken together, we demonstrate that solid-state nanopores can be employed to investigate the properties of individual proteins and their complex interactions, potentially paving the way for innovative medical therapies and advancements.

Interfacial residues in protein-protein complexes are in the eyes of the beholder.

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

Extract2Chip-Bypassing Protein Purification in Drug Discovery Using Surface Plasmon Resonance.

Modern drug discovery relies on combinatorial screening campaigns to find drug molecules targeting specific disease-associated proteins. The success of such campaigns often relies on functional and structural information of the selected therapeutic target, only achievable once its purification is mastered. With the aim of bypassing the protein purification process to gain insights on the druggability, ligand binding, and/or characterization of protein-protein interactions, herein, we describe the Extract2Chip method. This approach builds on the immobilization of site-specific biotinylated proteins of interest, directly from cellular extracts, on avidin-coated sensor chips to allow for the characterization of molecular interactions via surface plasmon resonance (SPR). The developed method was initially validated using Cyclophilin D (CypD) and subsequently applied to other drug discovery projects in which the targets of interest were difficult to express, purify, and crystallize. Extract2Chip was successfully applied to the characterization of Yes-associated protein (YAP): Transcriptional enhancer factor TEF (TEAD1) protein-protein interaction inhibitors, in the validation of a ternary complex assembly composed of Dyskerin pseudouridine synthase 1 (DKC1) and RuvBL1/RuvBL2, and in the establishment of a fast-screening platform to select the most suitable NUAK family SNF1-like kinase 2 (NUAK2) surrogate for binding and structural studies. The described method paves the way for a potential revival of the many drug discovery campaigns that have failed to deliver due to the lack of suitable and sufficient protein supply.

Chemical and Biological Strategies for Profiling Protein-Protein Interactions in Living Cells.

Protein-protein interactions (PPIs) play critical roles in almost all cellular signal transduction events. Characterization of PPIs without interfering with the functions of intact cells is very important for basic biology study and drug developments. However, the ability to profile PPIs especially those weak/transient interactions in their native states remains quite challenging. To this end, many endeavors are being made in developing new methods with high efficiency and strong operability. By coupling with advanced fluorescent microscopy and mass spectroscopy techniques, these strategies not only allow us to visualize the subcellular locations and monitor the functions of protein of interest (POI) in real time, but also enable the profiling and identification of potential unknown interacting partners in high-throughput manner, which greatly facilitates the elucidation of molecular mechanisms underlying numerous pathophysiological processes. In this review, we will summarize the typical methods for PPIs identification in living cells and their principles, advantages and limitations will also be discussed in detail.

Impact of inherent biases built into proteomic techniques: Proximity labeling and affinity capture compared

The characterization of protein-protein interactions (PPIs) is of high value for understanding protein function. Two strategies are popular for identification of PPIs direct from the cellular environment: affinity capture (pulldown) isolates the protein of interest with an immobilized matrix that specifically captures the target and potential partners, whereas in BioID, genetic fusion of biotin ligase facilitates proximity biotinylation, and labeled proteins are isolated with streptavidin. Whilst both methods provide valuable insights, they can reveal distinct PPIs, but the basis for these differences is less obvious. Here, we compare both methods using four different trypanosome proteins as baits: poly(A)-binding proteins PABP1 and PABP2, mRNA export receptor MEX67, and the nucleoporin NUP158. With BioID, we found that the population of candidate interacting proteins decreases with more confined bait protein localization, but the candidate population is less variable with affinity capture. BioID returned more likely false positives, in particular for proteins with less confined localization, and identified low molecular weight proteins less efficiently. Surprisingly, BioID for MEX67 identified exclusively proteins lining the inner channel of the nuclear pore complex (NPC), consistent with the function of MEX67, whereas the entire NPC was isolated by pulldown. Similarly, for NUP158, BioID returned surprisingly few PPIs within NPC outer rings that were by contrast detected with pulldown but instead returned a larger cohort of nuclear proteins. These rather significant differences highlight a clear issue with reliance on a single method to identify PPIs and suggest that BioID and affinity capture are complementary rather than alternative approaches.

Computational Network Inference for Bacterial Interactomics.

ABSTRACTSince the large-scale experimental characterization of protein–protein interactions (PPIs) is not possible for all species, several computational PPI prediction methods have been developed that harness existing data from other species. While PPI network prediction has been extensively used in eukaryotes, microbial network inference has lagged behind. However, bacterial interactomes can be built using the same principles and techniques; in fact, several methods are better suited to bacterial genomes. These predicted networks allow systems-level analyses in species that lack experimental interaction data. This review describes the current network inference and analysis techniques and summarizes the use of computationally-predicted microbial interactomes to date.

Proteomic Characterization of Protein-Protein Interactions

Identifying all the molecular components within a living cell is the first step into understanding how it functions. To further understand how a cell functions requires identifying the interactions that occur between these components. This fact is especially relevant for proteins. No protein within a human cell functions on its own without interacting with another biomolecule - usually another protein. While Protein-Protein Interactions (PPI) have historically been determined by examining a single protein per study, novel technologies developed over the past couple of decades are enabling high-throughput methods that aim to describe entire protein networks within cells. In this review, some of the technologies that have led to these developments are described along with applications of these techniques. Ultimately the goal of these technologies is to map out the entire circuitry of PPI within human cells to be able to predict the global consequences of perturbations to the cell system. This predictive capability will have major impacts on the future of both disease diagnosis and treatment.

AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters.

Modern rational modulator design and structure-function characterization often concentrate on concave regions of biomolecular surfaces, ranging from well-defined small-molecule binding sites to large protein-protein interaction interfaces. Here, we introduce a β-cluster as a pseudomolecular representation of fragment-centric pockets detected by AlphaSpace [J. Chem. Inf. Model. 2015, 55, 1585], a recently developed computational analysis tool for topographical mapping of biomolecular concavities. By mimicking the shape as well as atomic details of potential molecular binders, this new β-cluster representation allows direct pocket-to-ligand shape comparison and can be used to guide ligand optimization. Furthermore, we defined the β-score, the optimal Vina score of the β-cluster, as an indicator of pocket ligandability and developed an ensemble β-cluster approach, which allows one-to-one pocket mapping and comparison among aligned protein structures. We demonstrated the utility of β-cluster representation by applying the approach to a wide variety of problems including binding site detection and comparison, characterization of protein-protein interactions, and fragment-based ligand optimization. These new β-cluster functionalities have been implemented in AlphaSpace 2.0, which is freely available on the web at http://www.nyu.edu/projects/yzhang/AlphaSpace2.

Exploring Energy Profiles of Protein-Protein Interactions (PPIs) Using DFT Method

Background: Large-scale energy landscape characterization of protein-protein interactions (PPIs) is important to understand the interaction mechanism and protein-protein docking methods. The experimental methods for detecting energy landscapes are tedious and the existing computational methods require longer simulation time. Objective: The objective of the present work is to ascertain the energy profiles at the interface regions in a rapid manner to analyze the energy landscape of protein-protein interactions. Methods: The atomic coordinates obtained from the X-ray and NMR spectroscopy data are considered as inputs to compute cumulative energy profiles for experimentally validated protein-protein complexes. The energies computed by the program were comparable to the standard molecular dynamics simulations. Results: The PPI Profiler not only enables rapid generation of energy profiles but also facilitates the detection of hot spot residue atoms involved therein. Conclusion: The hotspot residues and their computed energies matched with the experimentally determined hot spot residues and their energies which correlated well by employing the MM/GBSA method. The proposed method can be employed to scan entire proteomes across species at an atomic level to study the key PPI interactions.

Techniques for detecting protein-protein interactions in living cells: principles, limitations, and recent progress.

Detecting protein-protein interactions (PPIs) provides fundamental information for understanding biochemical processes such as the transduction of signals from one cellular location to another; however, traditional biochemical techniques cannot provide sufficient spatio-temporal information to elucidate these molecular interactions in living cells. Over the past decade, several new techniques have enabled the identification and characterization of PPIs. In this review, we summarize three main techniques for detecting PPIs in vivo, focusing on their basic principles and applications in biological studies. We place a special emphasis on their advantages and limitations, and, in particular, we introduced some uncommon new techniques, such as single-molecule FRET (smFRET), FRET-fluorescence lifetime imaging microscopy (FRET-FLIM), cytoskeleton-based assay for protein-protein interaction (CAPPI) and single-molecule protein proximity index (smPPI), highlighting recent improvements to the established techniques. We hope that this review will provide a valuable reference to enable researchers to select the most appropriate technique for detecting PPIs.

Protein-Protein Interaction Assay to Analyze NOX4/p22phox Heterodimerization.

The stabilization and activation of NOX4 through its binding with p22phox are well documented; however little is known of the precise manner by which these two proteins interact. In recent years, the field of proteomics has undergone tremendous development with the introduction of many novel methods for the identification and characterization of protein-protein interactions (PPIs). To enhance our understanding of structural determinants leading to the association between NOX4 and p22phox, we developed a binary luciferase reporter assay (NanoBiT®) to quantitatively assess NOX4-p22phox heterodimerization. The complementation reporter quantitatively determines the accurate, reduced, or failed complex assembly, which can be confirmed and further interrogated by analyzing NOX4 catalytic activity (H2O2 release), protein expression, and dimer localization. This association-based PPI technique represents both a much-needed expansion of the NOX4 lead discovery tool box and a versatile method to probe the architecture of NOX and DUOX complexes in the future.

The Machado-Joseph disease-associated expanded form of ataxin-3: Overexpression, purification, and preliminary biophysical and structural characterization

An expansion of the polyglutamine (polyQ) tract within the deubiquitinase ataxin-3 protein is believed to play a role in a neurodegenerative disorder. Ataxin-3 contains a Josephin catalytic domain and a polyQ tract that renders it intrinsically prone to aggregate, and thus full-length protein is difficult to characterize structurally by high-resolution methods. We established a robust protocol for expression and purification of wild-type and expanded ataxin-3, presenting 19Q and 74Q, respectively. Both proteins are monodisperse as assessed by analytical size exclusion chromatography. Initial biophysical characterization was performed, with apparent transition melting temperature of expanded ataxin-3 lower than the wild-type counterpart. We further characterize the molecular envelope of wild-type and expanded polyQ tract in ataxin-3 using small angle X-ray scattering (SAXS). Characterization of protein-protein interactions between ataxin-3 and newly identified binding partners will benefit from our protocol.

Western Blotting and Co-immunoprecipitation of Endogenous STIM/ORAI and Protein Partners.

The characterization of protein-protein interactions through methods such as co-immunoprecipitation, followed by Western blot analysis, is a crucial step in the understanding of protein functions and the biology of the cell. Since the discovery of ORAI and STIM proteins as component of store-operated channel (SOC), overexpressing systems have been used to demonstrate how ORAI and STIM can associate with physiological and pathological conditions. Here we describe a protocol allowing endogenous studies.

Characterization of Protein-Protein Interactions in Recombinant Hemoglobin Producing Escherichia coli Cells Using Molecularly Imprinted Polymers.

The worldwide blood shortage has generated demands for alternatives to transfusible human blood. One such important option is based on recombinant hemoglobin-based oxygen carriers (rHBOCs). Most efforts have been focused on various E. coli based production systems. One of the key challenges in these systems is to devise an efficient and economical protein production strategy involving selection of suitable host cell and Hb variant, growth conditions and media engineering. Hb also influences the heterologous host cell metabolism and therefore the identification of modified protein-protein interactions is critical for optimizing Hb production. In this study, molecularly imprinted polymers (MIPs) directed against Hb were used to identify the human Hb protein interaction network in E. coli. One E. coli host protein, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), interacted strongly with Hb, especially fetal Hb (HbF).

Observing Extremely Weak Protein-Protein Interactions with Conventional Single-Molecule Fluorescence Microscopy.

Extremely weak protein-protein interactions (PPIs), signified by micromolar or even millimolar dissociation constants, are one of the keys to understanding the rapid responses of cellular systems. Although single-molecule methods are particularly useful in determining kinetics of biological processes, their application is largely limited to rather strong interactions because of the diffraction-limited observation volume. In this study, we report a single-molecule method that allows the characterization of PPIs using a prey concentration 4 orders of magnitude lower than the dissociation constant. Instead of increasing the concentration of diffusing molecules, which is inevitably limited by the optical diffraction limit, we employed an increased density of surface bait protein. The low occupancy of the surface baits permitted determination of the kinetics with single-molecule resolution. We used this approach to study a PPI network consisting of Ras and its downstream proteins including full-length Rafs and catalytic subunits of phosphoinositide 3-kinase.

ChemInform Abstract: Current Experimental Methods for Characterizing Protein‐Protein Interactions

AbstractReview: 260 refs.

Uncovering Aberrant Mutant PKA Function with Flow Cytometric FRET

Biology has been revolutionized by tools that allow the detection and characterization of protein-protein interactions (PPIs). Förster resonance energy transfer (FRET)-based methods have become particularly attractive as they allow quantitative studies of PPIs within the convenient and relevant context of living cells. We describe here an approach that allows the rapid construction of live-cell FRET-based binding curves using a commercially available flow cytometer. We illustrate a simple method for absolutely calibrating the cytometer, validating our binding assay against the gold standard isothermal calorimetry (ITC), and using flow cytometric FRET to uncover the structural and functional effects of the Cushing-syndrome-causing mutation (L206R) on PKA's catalytic subunit. We discover that this mutation not only differentially affects PKAcat's binding to its multiple partners but also impacts its rate of catalysis. These findings improve our mechanistic understanding of this disease-causing mutation, while illustrating the simplicity, general applicability, and power of flow cytometric FRET.

In silico Therapeutics for Neurogenic Hypertension and Vasovagal Syncope.

Neurocardiovascular diseases (NCVD) are the leading cause of death in the developed world and will remain so till 2020. In these diseases the pathologically changed nervous control of cardiovascular system has the central role. The actual NCV syndromes are neurogenic hypertension, representing the sympathetically mediated disorder, and vasovagal syncope, which is the vagally mediated disorders. Vasovagal syncope, the disease far from its etiological treatment, could benefit from recruiting and application of antimuscarinic drugs used in other parasympathetic disorders. The informational spectrum method (ISM), a method widely applied for the characterization of protein-protein interactions in the field of immunology, endocrinology and anti HIV drug discovery, was applied for the first time in the analysis of neurogenic hypertension and vasovagal syncope therapeutic targets. In silico analysis revealed the potential involvement of apelin in neurogenic hypertension. Applying the EIIP/ISM bioinformatics concept in investigation of drugs for treatment of vasovagal syncope suggests that 78% of tested antimuscarinic drugs could have anti vasovagal syncope effect. The presented results confirm that ISM is a promissing method for investigation of molecular mechanisms underlying pathophysiological proceses of NCV syndromes and discovery of therapeutics targets for their treatment.