The interaction of IQGAPs with calmodulin-like proteins

Since their identification over 15 years ago, the IQGAP (IQ-motif-containing GTPase-activating protein) family of proteins have been implicated in a wide range of cellular processes, including cytoskeletal reorganization, cell–cell adhesion, cytokinesis and apoptosis. These processes rely on protein–protein interactions, and understanding these (and how they influence one another) is critical in determining how the IQGAPs function. A key group of interactions is with calmodulin and the structurally related proteins myosin essential light chain and S100B. These interactions occur primarily through a series of IQ motifs, which are α-helical segments of the protein located towards the middle of the primary sequence. The three human IQGAP isoforms (IQGAP1, IQGAP2 and IQGAP3) all have four IQ motifs. However, these have different affinities for calmodulin, myosin light chain and S100B. Whereas all four IQ motifs of IQGAP1 interact with calmodulin in the presence of calcium, only the last two do so in the absence of calcium. IQ1 (the first IQ motif) interacts with the myosin essential light chain Mlc1sa and the first two undergo a calcium-dependent interaction with S100B. The significance of the interaction between Mlc1sa and IQGAP1 in mammals is unknown. However, a similar interaction involving the Saccharomyces cerevisiae IQGAP-like protein Iqg1p is involved in cytokinesis, leading to speculation that there may be a similar role in mammals.

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IQ-motif selectivity in human IQGAP2 and IQGAP3: binding of calmodulin and myosin essential light chain

Bioscience Reports ◽

10.1042/bsr20100123 ◽

2011 ◽

Vol 31 (5) ◽

pp. 371-379 ◽

Cited By ~ 22

Author(s):

Erwan Atcheson ◽

Elaine Hamilton ◽

Sevvel Pathmanathan ◽

Brett Greer ◽

Pat Harriott ◽

...

Keyword(s):

Light Chain ◽

Binding Sites ◽

Binding Properties ◽

Iq Motif ◽

Binding Partner ◽

Essential Light Chain ◽

Calcium Sensing ◽

Eukaryotic Proteins ◽

Transient Interactions ◽

Related Proteins

The IQGAP [IQ-motif-containing GAP (GTPase-activating protein)] family members are eukaryotic proteins that act at the interface between cellular signalling and the cytoskeleton. As such they collect numerous inputs from a variety of signalling pathways. A key binding partner is the calcium-sensing protein CaM (calmodulin). This protein binds mainly through a series of IQ-motifs which are located towards the middle of the primary sequence of the IQGAPs. In some IQGAPs, these motifs also provide binding sites for CaM-like proteins such as myosin essential light chain and S100B. Using synthetic peptides and native gel electrophoresis, the binding properties of the IQ-motifs from human IQGAP2 and IQGAP3 have been mapped. The second and third IQ-motifs in IQGAP2 and all four of the IQ-motifs of IQGAP3 interacted with CaM in the presence of calcium ions. However, there were differences in the type of interaction: while some IQ-motifs were able to form complexes with CaM which were stable under the conditions of the experiment, others formed more transient interactions. The first IQ-motifs from IQGAP2 and IQGAP3 formed transient interactions with CaM in the absence of calcium and the first motif from IQGAP3 formed a transient interaction with the myosin essential light chain Mlc1sa. None of these IQ-motifs interacted with S100B. Molecular modelling suggested that all of the IQ-motifs, except the first one from IQGAP2 formed α-helices in solution. These results extend our knowledge of the selectivity of IQ-motifs for CaM and related proteins.

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RFX1: a promising therapeutic arsenal against cancer

Cancer Cell International ◽

10.1186/s12935-021-01952-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Joby Issac ◽

Pooja S. Raveendran ◽

Ani V. Das

Keyword(s):

Protein Interactions ◽

Target Genes ◽

Cellular Proliferation ◽

Protein Protein Interactions ◽

Oncogenic Potential ◽

Cellular Processes ◽

Wide Range ◽

Induced Apoptosis ◽

Pleiotropic Function

AbstractRegulatory factor X1 (RFX1) is an evolutionary conserved transcriptional factor that influences a wide range of cellular processes such as cell cycle, cell proliferation, differentiation, and apoptosis, by regulating a number of target genes that are involved in such processes. On a closer look, these target genes also play a key role in tumorigenesis and associated events. Such observations paved the way for further studies evaluating the role of RFX1 in cancer. These studies were indispensable due to the failure of conventional chemotherapeutic drugs to target key cellular hallmarks such as cancer stemness, cellular plasticity, enhanced drug efflux, de-regulated DNA repair machinery, and altered pathways evading apoptosis. In this review, we compile significant evidence for the tumor-suppressive activities of RFX1 while also analyzing its oncogenic potential in some cancers. RFX1 induction decreased cellular proliferation, modulated the immune system, induced apoptosis, reduced chemoresistance, and sensitized cancer stem cells for chemotherapy. Thus, our review discusses the pleiotropic function of RFX1 in multitudinous gene regulations, decisive protein–protein interactions, and also its role in regulating key cell signaling events in cancer. Elucidation of these regulatory mechanisms can be further utilized for RFX1 targeted therapy.

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Ways into Understanding HIF Inhibition

Cancers ◽

10.3390/cancers13010159 ◽

2021 ◽

Vol 13 (1) ◽

pp. 159

Author(s):

Tina Schönberger ◽

Joachim Fandrey ◽

Katrin Prost-Fingerle

Keyword(s):

Protein Interactions ◽

Target Genes ◽

Protein Protein Interactions ◽

Low Oxygen ◽

Drug Candidates ◽

Open Questions ◽

Wide Range ◽

Hif Pathway

Hypoxia is a key characteristic of tumor tissue. Cancer cells adapt to low oxygen by activating hypoxia-inducible factors (HIFs), ensuring their survival and continued growth despite this hostile environment. Therefore, the inhibition of HIFs and their target genes is a promising and emerging field of cancer research. Several drug candidates target protein–protein interactions or transcription mechanisms of the HIF pathway in order to interfere with activation of this pathway, which is deregulated in a wide range of solid and liquid cancers. Although some inhibitors are already in clinical trials, open questions remain with respect to their modes of action. New imaging technologies using luminescent and fluorescent methods or nanobodies to complement widely used approaches such as chromatin immunoprecipitation may help to answer some of these questions. In this review, we aim to summarize current inhibitor classes targeting the HIF pathway and to provide an overview of in vitro and in vivo techniques that could improve the understanding of inhibitor mechanisms. Unravelling the distinct principles regarding how inhibitors work is an indispensable step for efficient clinical applications and safety of anticancer compounds.

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Structure, Function, Involvement in Diseases and Targeting of 14-3-3 Proteins: An Update

Current Medicinal Chemistry ◽

10.2174/0929867324666170426095015 ◽

2018 ◽

Vol 25 (1) ◽

pp. 5-21 ◽

Cited By ~ 25

Author(s):

Ylenia Cau ◽

Daniela Valensin ◽

Mattia Mori ◽

Sara Draghi ◽

Maurizio Botta

Keyword(s):

Protein Interactions ◽

Molecular Mechanisms ◽

Physiological Role ◽

Specific Protein ◽

Protein Protein Interactions ◽

Cellular Processes ◽

Protein Partners ◽

High Sequence Homology ◽

Small Molecule Modulators

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.

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Visual detection of binary, ternary, and quaternary protein interactions in fission yeast by Pil1 co-tethering assay

Journal of Cell Science ◽

10.1242/jcs.258774 ◽

2021 ◽

Author(s):

Zhong-Qiu Yu ◽

Xiao-Man Liu ◽

Dan Zhao ◽

Dan-Dan Xu ◽

Li-Lin Du

Keyword(s):

Fission Yeast ◽

Protein Interactions ◽

Visual Detection ◽

Protein Protein Interactions ◽

Phosphatidylinositol 3 Kinase ◽

Basic Form ◽

Bait Protein ◽

Cellular Processes ◽

Prey Protein ◽

Versatile Tool

Protein-protein interactions are vital for executing nearly all cellular processes. To facilitate the detection of protein-protein interactions in living cells of the fission yeast Schizosaccharomyces pombe, here we present an efficient and convenient method termed the Pil1 co-tethering assay. In its basic form, we tether a bait protein to mCherry-tagged Pil1, which forms cortical filamentary structures, and examine whether a GFP-tagged prey protein colocalizes with the bait. We demonstrate that this assay is capable of detecting pairwise protein-protein interactions of cytosolic proteins and nuclear proteins. Furthermore, we show that this assay can be used for detecting not only binary protein-protein interactions, but also ternary and quaternary protein-protein interactions. Using this assay, we systematically characterized the protein-protein interactions in the Atg1 complex and in the phosphatidylinositol 3-kinase (PtdIns3K) complexes and found that Atg38 is incorporated into the PtdIns3K complex I via an Atg38-Vps34 interaction. Our data show that this assay is a useful and versatile tool and should be added to the routine toolbox of fission yeast researchers.

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Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases

Current Topics in Medicinal Chemistry ◽

10.2174/1568026618666181025114903 ◽

2018 ◽

Vol 18 (20) ◽

pp. 1719-1736 ◽

Cited By ~ 3

Author(s):

Sharanya Sarkar ◽

Khushboo Gulati ◽

Manikyaprabhu Kairamkonda ◽

Amit Mishra ◽

Krishna Mohan Poluri

Keyword(s):

Small Molecule ◽

Protein Interactions ◽

Small Molecule Inhibitors ◽

Computational Techniques ◽

Protein Protein Interactions ◽

Computational Tools ◽

Computational Approaches ◽

Protein Protein Interaction ◽

Wide Range ◽

Therapeutic Measures

Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.

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Protein–protein interactions in bacteria: a promising and challenging avenue towards the discovery of new antibiotics

Beilstein Journal of Organic Chemistry ◽

10.3762/bjoc.14.267 ◽

2018 ◽

Vol 14 ◽

pp. 2881-2896 ◽

Cited By ~ 7

Author(s):

Laura Carro

Keyword(s):

Protein Interactions ◽

Bacterial Infections ◽

Multidrug Resistant ◽

Resistant Bacteria ◽

Protein Protein Interactions ◽

Lead Discovery ◽

Antibiotic Development ◽

Cellular Processes ◽

Ppi Networks ◽

New Antibiotics

Antibiotics are potent pharmacological weapons against bacterial infections; however, the growing antibiotic resistance of microorganisms is compromising the efficacy of the currently available pharmacotherapies. Even though antimicrobial resistance is not a new problem, antibiotic development has failed to match the growth of resistant pathogens and hence, it is highly critical to discover new anti-infective drugs with novel mechanisms of action which will help reducing the burden of multidrug-resistant microorganisms. Protein–protein interactions (PPIs) are involved in a myriad of vital cellular processes and have become an attractive target to treat diseases. Therefore, targeting PPI networks in bacteria may offer a new and unconventional point of intervention to develop novel anti-infective drugs which can combat the ever-increasing rate of multidrug-resistant bacteria. This review describes the progress achieved towards the discovery of molecules that disrupt PPI systems in bacteria for which inhibitors have been identified and whose targets could represent an alternative lead discovery strategy to obtain new anti-infective molecules.

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Metallocluster transactions: dynamic protein interactions guide the biosynthesis of Fe–S clusters in bacteria

Biochemical Society Transactions ◽

10.1042/bst20180365 ◽

2018 ◽

Vol 46 (6) ◽

pp. 1593-1603 ◽

Cited By ~ 9

Author(s):

Chenkang Zheng ◽

Patricia C. Dos Santos

Keyword(s):

Protein Interactions ◽

Protein Complexes ◽

Specific Protein ◽

Biological Synthesis ◽

Cluster Assembly ◽

Sequence Motifs ◽

Protein Protein Interactions ◽

Cysteine Desulfurase ◽

Wide Range ◽

Domains Of Life

Iron–sulfur (Fe–S) clusters are ubiquitous cofactors present in all domains of life. The chemistries catalyzed by these inorganic cofactors are diverse and their associated enzymes are involved in many cellular processes. Despite the wide range of structures reported for Fe–S clusters inserted into proteins, the biological synthesis of all Fe–S clusters starts with the assembly of simple units of 2Fe–2S and 4Fe–4S clusters. Several systems have been associated with the formation of Fe–S clusters in bacteria with varying phylogenetic origins and number of biosynthetic and regulatory components. All systems, however, construct Fe–S clusters through a similar biosynthetic scheme involving three main steps: (1) sulfur activation by a cysteine desulfurase, (2) cluster assembly by a scaffold protein, and (3) guided delivery of Fe–S units to either final acceptors or biosynthetic enzymes involved in the formation of complex metalloclusters. Another unifying feature on the biological formation of Fe–S clusters in bacteria is that these systems are tightly regulated by a network of protein interactions. Thus, the formation of transient protein complexes among biosynthetic components allows for the direct transfer of reactive sulfur and Fe–S intermediates preventing oxygen damage and reactions with non-physiological targets. Recent studies revealed the importance of reciprocal signature sequence motifs that enable specific protein–protein interactions and consequently guide the transactions between physiological donors and acceptors. Such findings provide insights into strategies used by bacteria to regulate the flow of reactive intermediates and provide protein barcodes to uncover yet-unidentified cellular components involved in Fe–S metabolism.

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Practical Model Selection for Prospective Virtual Screening

10.1101/337956 ◽

2018 ◽

Cited By ~ 1

Author(s):

Shengchao Liu ◽

Moayad Alnammi ◽

Spencer S. Ericksen ◽

Andrew F. Voter ◽

Gene E. Ananiev ◽

...

Keyword(s):

Random Forest ◽

Virtual Screening ◽

Protein Interactions ◽

High Throughput Screening ◽

Screening Methods ◽

Protein Protein Interactions ◽

Screening Algorithm ◽

Screening Performance ◽

Wide Range ◽

Public Datasets

AbstractVirtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the dataset and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual screening on two protein-protein interactions, PriA-SSB and RMI-FANCM, and present a strategy for choosing which algorithm is best for prospective compound prioritization. Our workflow identifies a random forest as the best algorithm for these targets over more sophisticated neural network-based models. The top 250 predictions from our selected random forest recover 37 of the 54 active compounds from a library of 22,434 new molecules assayed on PriA-SSB. We show that virtual screening methods that perform well in public datasets and synthetic benchmarks, like multi-task neural networks, may not always translate to prospective screening performance on a specific assay of interest.

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Exploring the Human-Nipah Virus Protein-Protein Interactome

Journal of Virology ◽

10.1128/jvi.01461-17 ◽

2017 ◽

Vol 91 (23) ◽

Cited By ~ 22

Author(s):

Luis Martinez-Gil ◽

Natalia M. Vera-Velasco ◽

Ismael Mingarro

Keyword(s):

Protein Interactions ◽

Affinity Purification ◽

Nipah Virus ◽

Productive Infection ◽

Virus Protein ◽

Protein Protein Interactions ◽

Data Set ◽

Wide Range ◽

Host Virus Interactions ◽

Virus Interactions

ABSTRACT Nipah virus is an emerging, highly pathogenic, zoonotic virus of the Paramyxoviridae family. Human transmission occurs by close contact with infected animals, the consumption of contaminated food, or, occasionally, via other infected individuals. Currently, we lack therapeutic or prophylactic treatments for Nipah virus. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. This aim led us to perform the present work, in which we identified 101 human-Nipah virus protein-protein interactions (PPIs), most of which (88) are novel. This data set provides a comprehensive view of the host complexes that are manipulated by viral proteins. Host targets include the PRP19 complex and the microRNA (miRNA) processing machinery. Furthermore, we explored the biologic consequences of the interaction with the PRP19 complex and found that the Nipah virus W protein is capable of altering p53 control and gene expression. We anticipate that these data will help in guiding the development of novel interventional strategies to counter this emerging viral threat. IMPORTANCE Nipah virus is a recently discovered virus that infects a wide range of mammals, including humans. Since its discovery there have been yearly outbreaks, and in some of them the mortality rate has reached 100% of the confirmed cases. However, the study of Nipah virus has been largely neglected, and currently we lack treatments for this infection. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. In the present work, we identified 101 human-Nipah virus protein-protein interactions using an affinity purification approach coupled with mass spectrometry. Additionally, we explored the cellular consequences of some of these interactions. Globally, this data set offers a comprehensive and detailed view of the host machinery's contribution to the Nipah virus's life cycle. Furthermore, our data present a large number of putative drug targets that could be exploited for the treatment of this infection.

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