The Src Family Kinases, Fgr, Fyn, Lck, and Lyn, Colocalize With Coated Membranes in Platelets

Abstract Nonreceptor protein tyrosine kinases phosphorylate proteins, thereby activating many intracellular signaling pathways and mediating protein-protein interactions. Protein phosphorylation is regulated in large part by the subcellular localization of these kinases and their respective substrates. Src is the most studied of these kinases, although other members of the Src family have been shown to be important in the differentiation of specific cell types. Src and Src family members are reported to be membrane-associated, but detergent-extraction studies have demonstrated a major difference in the solubility of Src compared with other members of the Src family (Fgr, Fyn, Lck, Lyn, and Yes), suggesting that their subcellular distributions may be different. By immunoelectron microscopy, we demonstrate that, unlike Src, the Src-related kinases are associated with electron-dense cytoplasmic domains and plasma membrane domains that correspond in size and frequency to endocytotic vesicles and coated pits. Clusters of labeling for these kinases also were seen adjacent to granule membranes. These kinases colocalize with the coated vesicle protein, clathrin, confirming their association with this class of endocytotic vesicle. We hypothesize that this vesicular association of Src-related kinases indicates a role for them in the endocytotic vesicle–mediated uptake and trafficking of plasma proteins into platelet granules.

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Interactome Analysis of KIN (Kin17) Shows New Functions of This Protein

Current Issues in Molecular Biology ◽

10.3390/cimb43020056 ◽

2021 ◽

Vol 43 (2) ◽

pp. 767-781

Author(s):

Vanessa Pinatto Gaspar ◽

Anelise Cardoso Ramos ◽

Philippe Cloutier ◽

José Renato Pattaro Junior ◽

Francisco Ferreira Duarte Junior ◽

...

Keyword(s):

Dna Replication ◽

Protein Interactions ◽

Ribosome Biogenesis ◽

Cell Metabolism ◽

Cell Types ◽

Protein Protein Interactions ◽

Cellular Mechanisms ◽

Cancerous Cell ◽

First Time

KIN (Kin17) protein is overexpressed in a number of cancerous cell lines, and is therefore considered a possible cancer biomarker. It is a well-conserved protein across eukaryotes and is ubiquitously expressed in all cell types studied, suggesting an important role in the maintenance of basic cellular function which is yet to be well determined. Early studies on KIN suggested that this nuclear protein plays a role in cellular mechanisms such as DNA replication and/or repair; however, its association with chromatin depends on its methylation state. In order to provide a better understanding of the cellular role of this protein, we investigated its interactome by proximity-dependent biotin identification coupled to mass spectrometry (BioID-MS), used for identification of protein–protein interactions. Our analyses detected interaction with a novel set of proteins and reinforced previous observations linking KIN to factors involved in RNA processing, notably pre-mRNA splicing and ribosome biogenesis. However, little evidence supports that this protein is directly coupled to DNA replication and/or repair processes, as previously suggested. Furthermore, a novel interaction was observed with PRMT7 (protein arginine methyltransferase 7) and we demonstrated that KIN is modified by this enzyme. This interactome analysis indicates that KIN is associated with several cell metabolism functions, and shows for the first time an association with ribosome biogenesis, suggesting that KIN is likely a moonlight protein.

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Expanding the potential genes of inborn errors of immunity through protein interactions

BMC Genomics ◽

10.1186/s12864-021-07909-3 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Humza A. Khan ◽

Manish J. Butte

Keyword(s):

Genetic Variation ◽

Protein Interactions ◽

Immune Cell ◽

Genetic Disorders ◽

Cell Types ◽

Protein Protein Interactions ◽

Inborn Errors ◽

Post Translational Modifications ◽

New Genes ◽

Inborn Errors Of Immunity

Abstract Background Inborn errors of immunity (IEI) are a group of genetic disorders that impair the immune system, with over 400 genes described so far, and hundreds more to be discovered. To facilitate the search for new genes, we need a way to prioritize among all the genes in the genome those most likely to play an important role in immunity. Results Here we identify a new list of genes by linking known IEI genes to new ones by using open-source databases of protein-protein interactions, post-translational modifications, and transcriptional regulation. We analyze this new set of 2,530 IEI-related genes for their tolerance of genetic variation and by their expression levels in various immune cell types. Conclusions By merging genes derived from protein interactions of known IEI genes with transcriptional data, we offer a new list of candidate genes that may play a role in as-yet undiscovered IEIs.

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Insulin signalling: putting the G- in protein-protein interactions

Biochemical Journal ◽

10.1042/bj20040619 ◽

2004 ◽

Vol 380 (1) ◽

pp. e11-e12 ◽

Cited By ~ 10

Author(s):

Craig C. MALBON

Keyword(s):

Insulin Receptor ◽

Cross Talk ◽

Protein Interactions ◽

Tyrosine Kinases ◽

Cell Biology ◽

Receptor Tyrosine Kinases ◽

Insulin Signalling ◽

Cell Signalling ◽

Protein Protein Interactions ◽

Proximal Point

Cell signalling via receptor tyrosine kinases, such as the insulin receptor, and via heterotrimeric G-proteins, such as Gαi, Gαs and Gαq family members, constitute two of most avidly studied paradigms in cell biology. That elements of these two populous signalling pathways must cross-talk to achieve proper signalling in the regulation of cell proliferation, differentiation and metabolism has been anticipated, but the evolution of our thinking and the analysis of such cross-talk have lagged behind the ever-expanding troupe of players and the recognition of multivalency as the rule, rather than the exception, in signalling biology. New insights have been provided by Kreuzer et al. in this issue of the Biochemical Journal, in which insulin is shown to provoke recruitment of Gαi-proteins to insulin-receptor-based complexes that can regulate the gain of insulin-receptor-catalysed autophosphorylation, a proximal point in the insulin-sensitive cascade of signalling. Understanding the convergence and cross-talk of signals from the receptor tyrosine kinases and G-protein-coupled receptor pathways in physical, spatial and temporal contexts will remain a major challenge of cell biology.

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Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupled receptor

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1800756115 ◽

2018 ◽

Vol 115 (12) ◽

pp. 3036-3041 ◽

Cited By ~ 43

Author(s):

Yinglong Miao ◽

J. Andrew McCammon

Keyword(s):

Protein Binding ◽

G Protein ◽

Protein Interactions ◽

Intracellular Signaling ◽

Md Simulations ◽

Binding Pocket ◽

Signaling Proteins ◽

Protein Protein Interactions ◽

Intracellular Loops ◽

G Protein Coupled

Protein–protein binding is key in cellular signaling processes. Molecular dynamics (MD) simulations of protein–protein binding, however, are challenging due to limited timescales. In particular, binding of the medically important G-protein-coupled receptors (GPCRs) with intracellular signaling proteins has not been simulated with MD to date. Here, we report a successful simulation of the binding of a G-protein mimetic nanobody to the M2 muscarinic GPCR using the robust Gaussian accelerated MD (GaMD) method. Through long-timescale GaMD simulations over 4,500 ns, the nanobody was observed to bind the receptor intracellular G-protein-coupling site, with a minimum rmsd of 2.48 Å in the nanobody core domain compared with the X-ray structure. Binding of the nanobody allosterically closed the orthosteric ligand-binding pocket, being consistent with the recent experimental finding. In the absence of nanobody binding, the receptor orthosteric pocket sampled open and fully open conformations. The GaMD simulations revealed two low-energy intermediate states during nanobody binding to the M2 receptor. The flexible receptor intracellular loops contribute remarkable electrostatic, polar, and hydrophobic residue interactions in recognition and binding of the nanobody. These simulations provided important insights into the mechanism of GPCR–nanobody binding and demonstrated the applicability of GaMD in modeling dynamic protein–protein interactions.

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Protein expression of prenyltransferase subunits in postmortem schizophrenia dorsolateral prefrontal cortex

Translational Psychiatry ◽

10.1038/s41398-019-0610-7 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 3

Author(s):

Anita L. Pinner ◽

Toni M. Mueller ◽

Khaled Alganem ◽

Robert McCullumsmith ◽

James H. Meador-Woodruff

Keyword(s):

Prefrontal Cortex ◽

Protein Expression ◽

Protein Interactions ◽

Intracellular Signaling ◽

Dorsolateral Prefrontal Cortex ◽

Signaling Proteins ◽

Protein Protein Interactions ◽

Protein Prenylation ◽

Lipid Modifications ◽

Dorsolateral Prefrontal

AbstractThe pathophysiology of schizophrenia includes altered neurotransmission, dysregulated intracellular signaling pathway activity, and abnormal dendritic morphology that contribute to deficits of synaptic plasticity in the disorder. These processes all require dynamic protein–protein interactions at cell membranes. Lipid modifications target proteins to membranes by increasing substrate hydrophobicity by the addition of a fatty acid or isoprenyl moiety, and recent evidence suggests that dysregulated posttranslational lipid modifications may play a role in multiple neuropsychiatric disorders, including schizophrenia. Consistent with these emerging findings, we have recently reported decreased protein S-palmitoylation in schizophrenia. Protein prenylation is a lipid modification that occurs upstream of S-palmitoylation on many protein substrates, facilitating membrane localization and activity of key intracellular signaling proteins. Accordingly, we hypothesized that, in addition to palmitoylation, protein prenylation may be abnormal in schizophrenia. To test this, we assayed protein expression of the five prenyltransferase subunits (FNTA, FNTB, PGGT1B, RABGGTA, and RABGGTB) in postmortem dorsolateral prefrontal cortex from patients with schizophrenia and paired comparison subjects (n = 13 pairs). We found decreased levels of FNTA (14%), PGGT1B (13%), and RABGGTB (8%) in schizophrenia. To determine whether upstream or downstream factors may be driving these changes, we also assayed protein expression of the isoprenoid synthases FDPS and GGPS1 and prenylation-dependent processing enzymes RCE and ICMT. We found these upstream and downstream enzymes to have normal protein expression. To rule out effects from chronic antipsychotic treatment, we assayed FNTA, PGGT1B, and RABGGTB in the cortex from rats treated long-term with haloperidol decanoate and found no change in the expression of these proteins. Given the role prenylation plays in localization of key signaling proteins found at the synapse, these data offer a potential mechanism underlying abnormal protein–protein interactions and protein localization in schizophrenia.

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An activity-based probe reveals dynamic protein–protein interactions mediating IGF-1R transactivation by the GABAB receptor

Biochemical Journal ◽

10.1042/bj20120188 ◽

2012 ◽

Vol 443 (3) ◽

pp. 627-634 ◽

Cited By ~ 17

Author(s):

Xin Lin ◽

Xin Li ◽

Ming Jiang ◽

Linhai Chen ◽

Chanjuan Xu ◽

...

Keyword(s):

Protein Interactions ◽

Protein Complex ◽

Tyrosine Kinases ◽

Chemical Biology ◽

Molecular Mechanisms ◽

Gabab Receptor ◽

Type I ◽

Protein Protein Interactions ◽

Downstream Effectors ◽

Factor Type

Many GPCRs (G-protein-coupled receptors) can activate RTKs (receptor tyrosine kinases) in the absence of RTK ligands, a phenomenon called transactivation. However, the underlying molecular mechanisms remain undefined. In the present study we investigate the molecular basis of GABAB (γ-aminobutyric acid B) receptor-mediated transactivation of IGF-1R (insulin-like growth factor type I receptor) in primary neurons. We take a chemical biology approach by developing an activity-based probe targeting the GABAB receptor. This probe enables us first to lock the GABAB receptor in an inactive state and then activate it with a positive allosteric modulator, thereby permitting monitoring of the dynamic of the protein complex associated with IGF-1R transactivation. We find that activation of the GABAB receptor induces a dynamic assembly and disassembly of a protein complex, including both receptors and their downstream effectors. FAK (focal adhesion kinase), a non-RTK, plays a key role in co-ordinating this dynamic process. Importantly, this dynamic of the GABAB receptor-associated complex is critical for transactivation and transactivation-dependent neuronal survival. The present study has identified an important mechanism underlying GPCR transactivation of RTKs, which was enabled by a new chemical biology tool generally applicable for dissecting GPCR signalling.

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Proteins with SH2 and SH3 domains couple receptor tyrosine kinases to intracellular signalling pathways

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.1993.0069 ◽

1993 ◽

Vol 340 (1293) ◽

pp. 279-285 ◽

Cited By ~ 35

Keyword(s):

Protein Interactions ◽

Tyrosine Kinases ◽

Receptor Protein ◽

Signalling Pathways ◽

Protein Protein Interactions ◽

Sh3 Domains ◽

Ras Pathway ◽

Sh2 Domains ◽

Intracellular Signalling Pathways ◽

Src Homology

The targets of receptor protein-tyrosine kinases are characterized by Src homology 2 (SH2) domains, that mediate specific interactions with receptor autophosphorylation sites. SH 2-mediated interactions are important for the activation of biochemical signalling pathways in cells stimulated with growth factors. A distinct protein module, the SH3 domain, is frequently found in polypeptides that contain SH2 domains, and is also implicated in controlling protein-protein interactions in signal transduction. Evidence suggesting that SH2 and SH3 domains act synergistically in stimulation of the Ras pathway is discussed.

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Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

10.1101/2020.09.17.301200 ◽

2020 ◽

Author(s):

Mayank Baranwal ◽

Abram Magner ◽

Jacob Saldinger ◽

Emine S. Turali-Emre ◽

Shivani Kozarekar ◽

...

Keyword(s):

Protein Interactions ◽

Intracellular Signaling ◽

Metabolic Regulation ◽

Selection Process ◽

3D Structure ◽

Structural Data ◽

Sequence Information ◽

Protein Protein Interactions ◽

Attention Network ◽

Interaction Sites

AbstractDevelopment of new methods for analysis of protein-protein interactions (PPIs) at molecular and nanometer scales gives insights into intracellular signaling pathways and will improve understanding of protein functions, as well as other nanoscale structures of biological and abiological origins. Recent advances in computational tools, particularly the ones involving modern deep learning algorithms, have been shown to complement experimental approaches for describing and rationalizing PPIs. However, most of the existing works on PPI predictions use protein-sequence information, and thus have difficulties in accounting for the three-dimensional organization of the protein chains. In this study, we address this problem and describe a PPI analysis method based on a graph attention network, named Struct2Graph, for identifying PPIs directly from the structural data of folded protein globules. Our method is capable of predicting the PPI with an accuracy of 98.89% on the balanced set consisting of an equal number of positive and negative pairs. On the unbalanced set with the ratio of 1:10 between positive and negative pairs, Struct2Graph achieves a five-fold cross validation average accuracy of 99.42%. Moreover, unsupervised prediction of the interaction sites by Struct2Graph for phenol-soluble modulins are found to be in concordance with the previously reported binding sites for this family.Author summaryPPIs are the central part of signal transduction, metabolic regulation, environmental sensing, and cellular organization. Despite their success, most strategies to decode PPIs use sequence based approaches do not generalize to broader classes of chemical compounds of similar scale as proteins that are equally capable of forming complexes with proteins that are not based on amino acids, and thus lack of an equivalent sequence-based representation. Here, we address the problem of prediction of PPIs using a first of its kind, 3D structure based graph attention network (available at https://github.com/baranwa2/Struct2Graph). Despite its excellent prediction performance, the novel mutual attention mechanism provides insights into likely interaction sites through its knowledge selection process in a completely unsupervised manner.

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Peptide Targeting of PDZ-Dependent Interactions as Pharmacological Intervention in Immune-Related Diseases

Molecules ◽

10.3390/molecules26216367 ◽

2021 ◽

Vol 26 (21) ◽

pp. 6367

Author(s):

Luis H. Gutiérrez-González ◽

Selma Rivas-Fuentes ◽

Silvia Guzmán-Beltrán ◽

Angélica Flores-Flores ◽

Jorge Rosas-García ◽

...

Keyword(s):

Small Molecules ◽

Protein Interactions ◽

Cell Types ◽

Pharmacological Intervention ◽

Protein Protein Interactions ◽

Pdz Proteins ◽

Immune Evasion Mechanism ◽

Cellular Processes ◽

Clinical Conditions ◽

Peptide Targeting

PDZ (postsynaptic density (PSD95), discs large (Dlg), and zonula occludens (ZO-1)-dependent interactions are widely distributed within different cell types and regulate a variety of cellular processes. To date, some of these interactions have been identified as targets of small molecules or peptides, mainly related to central nervous system disorders and cancer. Recently, the knowledge of PDZ proteins and their interactions has been extended to various cell types of the immune system, suggesting that their targeting by viral pathogens may constitute an immune evasion mechanism that favors viral replication and dissemination. Thus, the pharmacological modulation of these interactions, either with small molecules or peptides, could help in the control of some immune-related diseases. Deeper structural and functional knowledge of this kind of protein–protein interactions, especially in immune cells, will uncover novel pharmacological targets for a diversity of clinical conditions.

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Latest update on chemokine receptors as therapeutic targets

Biochemical Society Transactions ◽

10.1042/bst20201114 ◽

2021 ◽

Author(s):

Wing Yee Lai ◽

Anja Mueller

Keyword(s):

Protein Interactions ◽

Chemokine Receptors ◽

Inflammatory Diseases ◽

Specific Binding ◽

Therapeutic Targets ◽

Cell Types ◽

Fine Tuning ◽

Protein Protein Interactions ◽

Diverse Range ◽

Chemokine Ligand

The chemokine system plays a fundamental role in a diverse range of physiological processes, such as homeostasis and immune responses. Dysregulation in the chemokine system has been linked to inflammatory diseases and cancer, which renders chemokine receptors to be considered as therapeutic targets. In the past two decades, around 45 drugs targeting chemokine receptors have been developed, yet only three are clinically approved. The challenging factors include the limited understanding of aberrant chemokine signalling in malignant diseases, high redundancy of the chemokine system, differences between cell types and non-specific binding of the chemokine receptor antagonists due to the broad ligand-binding pockets. In recent years, emerging studies attempt to characterise the chemokine ligand–receptor interactions and the downstream signalling protein–protein interactions, aiming to fine tuning to the promiscuous interplay of the chemokine system for the development of precision medicine. This review will outline the updates on the mechanistic insights in the chemokine system and propose some potential strategies in the future development of targeted therapy.

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