Complex Protein Interaction Research Articles

Family with sequence similarity 134 member B-mediated reticulophagy ameliorates hepatocyte apoptosis induced by dithiothreitol.

BACKGROUNDEndoplasmic reticulum (ER) stress-related hepatocyte apoptosis is responsible for multiple hepatic diseases. Previous studies have revealed that endoplasmic reticulophagy (ER-phagy) promotes the selective clearance of damaged ER fragments during ER stress, playing a crucial role in maintaining ER homeostasis and inhibiting apoptosis. Family with sequence similarity 134 member B (FAM134B) is a receptor involved in ER-phagy that can form a complex with calnexin (CNX) and microtubule-associated protein 1 light chain 3 (LC3). The complex can mediate the selective isolation of ER fragments to attenuate hepatocyte apoptosis. However, the precise regulatory mechanisms remain unclear.AIMTo elucidate the effect of FAM134B-mediated ER-phagy on ER stress-induced apoptosis in buffalo rat liver 3A (BRL-3A) rat hepatocytes and the potential regulatory mechanisms.METHODSER stress-related hepatocyte apoptosis was induced using dithiothreitol (DTT). Proteins related to ER stress and autophagy were measured with western blotting. Protein complex interactions with FAM134B were isolated by co-immunoprecipitation. ER-phagy was evaluated in immunofluorescence experiments. Cell cycle distribution and apoptosis were measured by flow cytometry. Mitochondrial Ca2+ levels were evaluated by the co-localization of intracellular Ca2+-tracker and Mito-tracker. The small interfering RNA against FAM134B was used to knockdown FAM134B in BRL-3A cells.RESULTSER stress-related and autophagy-related proteins in BRL-3A cells were elevated by both short and long-term DTT treatment. Furthermore, co-immunoprecipitation confirmed an interaction between FAM134B, CNX, FAM134B, and LC3 in BRL-3A cells. Immunofluorescence assays revealed that autolysosomes significantly decreased following short-term DTT treatment, but increased after long-term treatment. Mitochondrial Ca2+ levels and apoptotic rates were dramatically elevated, and more cells were arrested in the G1 stage after short-term DTT treatment; however, these decreased 48 h later. Moreover, FAM134B downregulation accelerated mitochondrial apoptotic pathway activation and aggravated hepatocyte apoptosis under ER stress.CONCLUSIONFAM134B-mediated ER-phagy attenuates hepatocyte apoptosis by suppressing the mitochondrial apoptotic pathway. Our findings provide new evidence highlighting the importance of FAM134B-mediated ER-phagy in attenuating hepatocyte apoptosis.

RPpocket: An RNA-Protein Intuitive Database with RNA Pocket Topology Resources.

RNA–protein complexes regulate a variety of biological functions. Thus, it is essential to explore and visualize RNA–protein structural interaction features, especially pocket interactions. In this work, we develop an easy-to-use bioinformatics resource: RPpocket. This database provides RNA–protein complex interactions based on sequence, secondary structure, and pocket topology analysis. We extracted 793 pockets from 74 non-redundant RNA–protein structures. Then, we calculated the binding- and non-binding pocket topological properties and analyzed the binding mechanism of the RNA–protein complex. The results showed that the binding pockets were more extended than the non-binding pockets. We also found that long-range forces were the main interaction for RNA–protein recognition, while short-range forces strengthened and optimized the binding. RPpocket could facilitate RNA–protein engineering for biological or medical applications.

A screening method for binding synthetic metallo-complexes to haem proteins

The introduction of a second coordination sphere, in the form of a protein scaffold, to synthetic catalysts can be beneficial for their reactivity and substrate selectivity. Here we present semi-native polyacrylamide gel electrophoresis (semi-native PAGE) as a rapid screening method for studying metal complex-protein interactions. Such a screening is generally performed using electron spray ionization mass spectrometry (ESI-MS) and/or UV–Vis spectroscopy. Semi-native PAGE analysis has the advantage that it does not rely on spectral changes of the metal complex upon protein interaction and can be applied for high-throughput screening and optimization of complex binding. In semi-native PAGE non-denatured protein samples are loaded on a gel containing sodium dodecyl sulphate (SDS), leading to separation based on differences in structural stability. Semi-native PAGE gel runs of catalyst-protein mixtures were compared to gel runs obtained with native and denaturing PAGE. ESI-MS was additionally realised to confirm protein-complex binding. The general applicability of semi-native PAGE was investigated by screening the binding of various cobalt- and ruthenium-based compounds to three types of haem proteins.

Microrchidia CW-Type Zinc Finger 2, a Chromatin Modifier in a Spectrum of Peripheral Neuropathies.

Microrchidia CW-type zinc finger 2 (MORC2) gene encodes a protein expressed in all tissues and enriched in the brain. MORC2 protein is composed of a catalytic ATPase domain, three coil-coiled domains allowing dimerization or protein complex interaction, a zinc-finger CW domain allowing DNA interaction, and a CHROMO-like (CHRromatin Organization Modifier) domain. Recently, de novo or dominantly inherited heterozygous mutations have been associated with a spectrum of disorders affecting the peripheral nervous system such as the Charcot-Marie-Tooth disease, spinal muscular atrophy-like phenotype disorder, or a neurodevelopmental syndrome associated with developmental delay, impaired growth, dysmorphic facies, and axonal neuropathy (DIGFAN). In this review, we detail the various mutations of MORC2 and their consequences on clinical manifestations. Possible genotype-phenotype correlations as well as intra and inter-family variability are discussed. MORC2 molecular functions such as transcriptional modulation, DNA damage repair, and lipid metabolism are then reviewed. We further discuss the impact of MORC2 mutations on the epigenetic landscape in the neuromuscular system and hypothesize probable pathophysiological mechanisms underlying the phenotypic variability observed.

Complex protein interactions mediate Drosophila Lar function in muscle tissue.

The type IIa family of receptor protein tyrosine phosphatases (RPTPs), including Lar, RPTPσ and RPTPδ, are well-studied in coordinating actin cytoskeletal rearrangements during axon guidance and synaptogenesis. To determine whether this regulation is conserved in other tissues, interdisciplinary approaches were utilized to study Lar-RPTPs in the Drosophila musculature. Here we find that the single fly ortholog, Drosophila Lar (Dlar), is localized to the muscle costamere and that a decrease in Dlar causes aberrant sarcomeric patterning, deficits in larval locomotion, and integrin mislocalization. Sequence analysis uncovered an evolutionarily conserved Lys-Gly-Asp (KGD) signature in the extracellular region of Dlar. Since this tripeptide sequence is similar to the integrin-binding Arg-Gly-Asp (RGD) motif, we tested the hypothesis that Dlar directly interacts with integrin proteins. However, structural analyses of the fibronectin type III domains of Dlar and two vertebrate orthologs that include this conserved motif indicate that this KGD tripeptide is not accessible and thus unlikely to mediate physical interactions with integrins. These results, together with the proteomics identification of basement membrane (BM) proteins as potential ligands for type IIa RPTPs, suggest a complex network of protein interactions in the extracellular space that may mediate Lar function and/or signaling in muscle tissue.

Computational Structure Prediction for Antibody-Antigen Complexes From Hydrogen-Deuterium Exchange Mass Spectrometry: Challenges and Outlook.

Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.

Machine learning solutions for predicting protein–protein interactions

AbstractProteins are “social molecules.” Recent experimental evidence supports the notion that large protein aggregates, known as biomolecular condensates, affect structurally and functionally many biological processes. Condensate formation may be permanent and/or time dependent, suggesting that biological processes can occur locally, depending on the cell needs. The question then arises as to which extent we can monitor protein‐aggregate formation, both experimentally and theoretically and then predict/simulate functional aggregate formation. Available data are relative to mesoscopic interacting networks at a proteome level, to protein‐binding affinity data, and to interacting protein complexes, solved with atomic resolution. Powerful algorithms based on machine learning (ML) can extract information from data sets and infer properties of never‐seen‐before examples. ML tools address the problem of protein–protein interactions (PPIs) adopting different data sets, input features, and architectures. According to recent publications, deep learning is the most successful method. However, in ML‐computational biology, convincing evidence of a success story comes out by performing general benchmarks on blind data sets. Results indicate that the state‐of‐the‐art ML approaches, based on traditional and/or deep learning, can still be ameliorated, irrespectively of the power of the method and richness in input features. This being the case, it is quite evident that powerful methods still are not trained on the whole possible spectrum of PPIs and that more investigations are necessary to complete our knowledge of PPI‐functional interactions.This article is categorized under: Software > Molecular Modeling Structure and Mechanism > Computational Biochemistry and Biophysics Data Science > Artificial Intelligence/Machine Learning Molecular and Statistical Mechanics > Molecular Interactions

A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets.

Mirror cutting-assisted orthogonal digestion enabling large-scale and accurate protein complex characterization

蛋白质主要以复合物的形式参与各项生命活动。化学交联质谱(CXMS)技术作为近年来新兴的蛋白质复合物解析技术,不仅可实现蛋白质复合物规模化解析,而且普遍适用于任意相对分子质量和纯度的蛋白质复合物样品,因此已成为X-射线晶体衍射技术、冷冻电镜技术等蛋白质复合物解析经典技术的重要补充。目前,CXMS主要采用胰蛋白酶将交联后的蛋白质复合物进行酶切,并进行质谱鉴定。然而鉴定到的交联肽段谱图中b/y特征碎片离子的鉴定数目不足,且因肽段序列匹配连续性较差导致谱图可信度相对较低,影响了蛋白质复合物交联位点的鉴定精准度。该文基于镜像酶正交切割的互补特性,采用胰蛋白酶镜像酶与胰蛋白酶联合酶切的方法,对交联后的蛋白质复合物分别进行酶切,再利用液相色谱-质谱联用技术对酶解产生的交联肽段进行鉴定,进而实现蛋白质复合物的组成、相互作用和结构位点距离约束的解析。对牛血清白蛋白和大肠杆菌全蛋白的交联肽段的分析结果表明,该方法通过增加交联肽段谱图中特征碎裂离子的数目和连续性,鉴定到的大肠杆菌全蛋白的交联位点,较单一胰蛋白酶酶切,提高了16%。因此,镜像酶正交酶切策略能有效提高交联肽段的鉴定准确度和覆盖度,有望为实现规模化的蛋白质复合物精准解析提供新思路。

Quantitative Imaging With DNA-PAINT for Applications in Synaptic Neuroscience.

Super-resolution (SR) microscopy techniques have been advancing the understanding of neuronal protein networks and interactions. Unraveling the arrangement of proteins with molecular resolution provided novel insights into neuron cytoskeleton structure and actin polymerization dynamics in synaptic spines. Recent improvements in quantitative SR imaging have been applied to synaptic protein clusters and with improved multiplexing technology, the interplay of multiple protein partners in synaptic active zones has been elucidated. While all SR techniques come with benefits and drawbacks, true molecular quantification is a major challenge with the most complex requirements for labeling reagents and careful experimental design. In this perspective, we provide an overview of quantitative SR multiplexing and discuss in greater detail the quantification and multiplexing capabilities of the SR technique DNA-PAINT. Using predictable binding kinetics of short oligonucleotides, DNA-PAINT provides two unique approaches to address multiplexed molecular quantification: qPAINT and Exchange-PAINT. With precise and accurate quantification and spectrally unlimited multiplexing, DNA-PAINT offers an attractive route to unravel complex protein interaction networks in neurons. Finally, while the SR community has been pushing technological advances from an imaging technique perspective, the development of universally available, small, efficient, and quantitative labels remains a major challenge in the field.

Cell adhesion upregulates the cortical tension and actin cortex thickness during the adhesion process

Recent studies emphasize the pervasive function of intercellular adhesion and its interplay with cortical tension in biological processes such as morphogenesis, wound healing, and cancer metastasis. However, quantifying such interaction at single-cell level is challenging and results are dependent on experimental conditions. Most interrogations focus on collective behavior of cells or are performed in the presence of cell-ECM or cell-substrate adhesion. Thus, the interaction of cytoskeletal protein complexes with adhesion components and tension-adhesion regulation is not well clarified.

Cooperative allostery and structural dynamics of streptavidin at cryogenic- and ambient-temperature

Multimeric protein assemblies are abundant in nature. Streptavidin is an attractive protein that provides a paradigm system to investigate the intra- and intermolecular interactions of multimeric protein complexes. Also, it offers a versatile tool for biotechnological applications. Here, we present two apo-streptavidin structures, the first one is an ambient temperature Serial Femtosecond X-ray crystal (Apo-SFX) structure at 1.7 Å resolution and the second one is a cryogenic crystal structure (Apo-Cryo) at 1.1 Å resolution. These structures are mostly in agreement with previous structural data. Combined with computational analysis, these structures provide invaluable information about structural dynamics of apo streptavidin. Collectively, these data further reveal a novel cooperative allostery of streptavidin which binds to substrate via water molecules that provide a polar interaction network and mimics the substrate biotin which displays one of the strongest affinities found in nature.

Assessing Protein Interactions for Clustering of Mitochondrial Urea Cycle Enzymes.

Enzyme clustering is a phenomenon that involves partitioning of proteins that function together in a common subcellular or sub-organellar compartment. Traditional genetic, biochemical, and biophysical approaches for studying protein-protein interactions in complexes with defined stoichiometry yield inconclusive results when applied to clustered proteins. This chapter describes a combination of approaches to study clustered proteins including co-immunoprecipitation, biochemical co-localization in purified mitochondria, and super resolution imaging of endogenous proteins in situ. These approaches can be used to study interactions among proteins that form clusters. We will illustrate this approach by using the urea cycle enzymes that localize in the mitochondrial matrix, and form clusters at the inner mitochondrial membrane.

Peptide and protein chemistry approaches to study the tumor suppressor protein p53.

The tumor suppressor and master gene regulator protein p53 has been the subject of intense investigation for several decades due to its mutation in about half of all human cancers. However, mechanistic studies of p53 in cells are complicated by its many dynamic binding partners and heterogeneous post-translational modifications. The design of therapeutics that rescue p53 functions in cells requires a mechanistic understanding of its protein-protein interactions in specific protein complexes and identifying changes in p53 activity by diverse post-translational modifications. This review highlights the important roles that peptide and protein chemistry have played in biophysical and biochemical studies aimed at elucidating p53 regulation by several key binding partners. The design of various peptide inhibitors that rescue p53 function in cells and new opportunities in targeting p53-protein interactions are discussed. In addition, the review highlights the importance of a protein semisynthesis approach to comprehend the role of site-specific PTMs in p53 regulation.

Amber Suppression Technology for Mapping Site-specific Viral-host Protein Interactions in Mammalian Cells.

Probing the molecular interactions of viral-host protein complexes to understand pathogenicity is essential in modern virology to help the development of antiviral therapies. Common binding assays, such as co-immunoprecipitation or pull-downs, are helpful in investigating intricate viral-host proteins interactions. However, such assays may miss low-affinity and favour non-specific interactions. We have recently incorporated photoreactive amino acids at defined residues of a viral protein in vivo, by introducing amber stop codons (TAG) and using a suppressor tRNA. This is followed by UV-crosslinking, to identify interacting host proteins in live mammalian cells. The affinity-purified photo-crosslinked viral-host protein complexes are further characterized by mass spectrometry following extremely stringent washes. This combinatorial site-specific incorporation of a photoreactive amino acid and affinity purification-mass spectrometry strategy allows the definition of viral-host protein contacts at single residue resolution and greatly reduces non-specific interactors, to facilitate characterization of viral-host protein interactions. Graphic abstract: Schematic overview of the virus-host interaction assay based on an amber suppression approach. Mammalian cells grown in Bpa-supplemented medium are co-transfected with plasmids encoding viral sequences carrying a Flag tag, a (TAG) stop codon at the desired position, and an amber suppressor tRNA (tRNACUA)/aminoacyl tRNA synthetase (aaRS) orthogonal pair. Cells are then exposed to UV, to generate protein-protein crosslinks, followed by immunoprecipitation with anti-Flag magnetic beads. The affinity-purified crosslinks are probed by western blot using an anti-Flag antibody and the crosslinked host proteins are characterised by mass spectrometry.

Electrospray ionization of native membrane proteins proceeds via a charge equilibration step.

Electrospray ionization mass spectrometry is increasingly applied to study the structures and interactions of membrane protein complexes. However, the charging mechanism is complicated by the presence of detergent micelles during ionization. Here, we show that the final charge of membrane proteins can be predicted by their molecular weight when released from the non-charge reducing saccharide detergents. Our data indicate that PEG detergents lower the charge depending on the number of detergent molecules in the surrounding micelle, whereas fos-choline detergents may additionally participate in ion–ion reactions after desolvation. The supercharging reagent sulfolane, on the other hand, has no discernible effect on the charge of detergent-free membrane proteins. Taking our observations into the context of protein-detergent interactions in the gas phase, we propose a charge equilibration model for the generation of native-like membrane protein ions. During ionization of the protein-detergent complex, the ESI charges are distributed between detergent and protein according to proton affinity of the detergent, number of detergent molecules, and surface area of the protein. Charge equilibration influenced by detergents determines the final charge state of membrane proteins. This process likely contributes to maintaining a native-like fold after detergent release and can be harnessed to stabilize particularly labile membrane protein complexes in the gas phase.

A Quantitative Systems Approach to Define Novel Effects of Tumour p53 Mutations on Binding Oncoprotein MDM2.

Understanding transient protein interactions biochemically at the proteome scale remains a long-standing challenge. Current tools developed to study protein interactions in high-throughput measure stable protein complexes and provide binary readouts; they do not elucidate dynamic and weak protein interactions in a proteome. The majority of protein interactions are transient and cover a wide range of affinities. Nucleic acid programmable protein arrays (NAPPA) are self-assembling protein microarrays produced by freshly translating full-length proteins in situ on the array surface. Herein, we have coupled NAPPA to surface plasmon resonance imaging (SPRi) to produce a novel label-free platform that measures many protein interactions in real-time allowing the determination of the KDs and rate constants. The developed novel NAPPA-SPRi technique showed excellent ability to study protein-protein interactions of clinical mutants of p53 with its regulator MDM2. Furthermore, this method was employed to identify mutant p53 proteins insensitive to the drug nutlin-3, currently in clinical practice, which usually disrupts the p53-MDM2 interactions. Thus, significant differences in the interactions were observed for p53 mutants on the DNA binding domain (Arg-273-Cys, Arg-273-His, Arg-248-Glu, Arg-280-Lys), on the structural domain (His-179-Tyr, Cys-176-Phe), on hydrophobic moieties in the DNA binding domain (Arg-280-Thr, Pro-151-Ser, Cys-176-Phe) and hot spot mutants (Gly-245-Cys, Arg-273-Leu, Arg-248-Glu, Arg-248-Gly), which signifies the importance of point mutations on the MDM2 interaction and nutlin3 effect, even in molecular locations related to other protein activities.

A hybrid strategy combining solution NMR spectroscopy and isothermal titration calorimetry to characterize protein-nanodisc interaction

NMR is a powerful tool for characterizing intermolecular interactions at atomic resolution. However, the nature of the complex interactions of membrane-binding proteins makes it difficult to elucidate the interaction mechanisms. Here, we demonstrated that structural and thermodynamic analyses using solution NMR spectroscopy and isothermal titration calorimetry (ITC) can clearly detect a specific interaction between the pleckstrin homology (PH) domain of ceramide transport protein (CERT) and phosphatidylinositol 4-monophosphate (PI4P) embedded in the lipid nanodisc, and distinguish the specific interaction from nonspecific interactions with the bulk surface of the lipid nanodisc. This NMR-ITC hybrid strategy provides detailed characterization of protein-lipid membrane interactions.

Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease.

In HLA-DQ8-associated celiac disease, Gliadin-γ1 or Gliadin-α1 peptide is presented to the cell surface and recognized by several types of T-cell receptor (TCR), but it is still unclear how the TCR, peptide, and the major histocompatibility complex (MHC) act together to trigger celiac disease. For now, most of the analysis is based on static crystal structures. And the detailed information about these structures based on energetic interaction is still lacking. Here, we took four types of celiac disease-related MHC-peptide-TCR structures from three patients to perform computational alanine scanning calculations using the molecular mechanics generalized born surface area (MM/GBSA) approach combined with a recently developed interaction entropy (IE) method to identify the key residues on TCR, peptide, and MHC. Our study aims to shed some light on the interaction mechanism of this complex protein interaction system. Based on detailed computational analysis and mutational calculations, important binding interactions in these triple-interaction complexes are analyzed, and critical residues responsible for TCR/pMHC recognition pattern in HLA-DQ8-associated celiac disease are presented. These detailed analysis and computational result should help shed light on our understanding of the celiac disease and the development of the medical treatment.

A computational exploration of resilience and evolvability of protein\u2013protein interaction networks

Protein–protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype’s PPI network’s resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks’ resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms—random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.