scholarly journals InteractoMIX: a suite of computational tools to exploit interactomes in biological and clinical research

2016 ◽  
Vol 44 (3) ◽  
pp. 917-924 ◽  
Author(s):  
Daniel Poglayen ◽  
Manuel Alejandro Marín-López ◽  
Jaume Bonet ◽  
Oriol Fornes ◽  
Javier Garcia-Garcia ◽  
...  
Keyword(s):  
Clinical Research ◽  
Protein Interactions ◽  
Biological Processes ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Cellular Processes ◽  
Structural Details ◽  
One Stop ◽  
Health And Disease

Virtually all the biological processes that occur inside or outside cells are mediated by protein–protein interactions (PPIs). Hence, the charting and description of the PPI network, initially in organisms, the interactome, but more recently in specific tissues, is essential to fully understand cellular processes both in health and disease. The study of PPIs is also at the heart of renewed efforts in the medical and biotechnological arena in the quest of new therapeutic targets and drugs. Here, we present a mini review of 11 computational tools and resources tools developed by us to address different aspects of PPIs: from interactome level to their atomic 3D structural details. We provided details on each specific resource, aims and purpose and compare with equivalent tools in the literature. All the tools are presented in a centralized, one-stop, web site: InteractoMIX (http://interactomix.com).

Methods to analyse composition and dynamics of macromolecular complexes

2013 ◽  
Vol 41 (5) ◽  
pp. 1235-1241 ◽  
Author(s):  
Heinrich Heide ◽  
Ilka Wittig
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Protein Biosynthesis ◽  
Biological Processes ◽  
Protein Protein Interactions ◽  
Macromolecular Complexes ◽  
Cellular Processes ◽  
Recent Developments ◽  
Dna Replication And Repair ◽  
Health And Disease

Macromolecular complexes are involved in a broad spectrum of cellular processes including protein biosynthesis, protein secretion and degradation, metabolism, DNA replication and repair, and signal transduction along with other important biological processes. The analysis of protein complexes in health and disease is important to gain insights into cellular physiology and pathophysiology. In the last few decades, research has focused on the identification and the dynamics of macromolecular complexes. Several techniques have been developed to isolate native protein complexes from cells and tissues to allow further characterization by microscopic and proteomic analysis. In the present paper, we provide a brief overview of proteomic methods that can be used to identify protein–protein interactions, focusing on recent developments to study the entire complexome of a biological sample.

Comparison of Computational Tools for Protein-Protein Interaction (PPI) Mapping and Analysis

2013 ◽  
Vol 63 (1) ◽  
Author(s):  
Geok Wei Leong ◽  
Sheau Chen Lee ◽  
Cher Chien Lau ◽  
Peter Klappa ◽  
Mohd Shahir Shamsir Omar
Keyword(s):  
Protein Interactions ◽  
Network Visualization ◽  
Database Integration ◽  
File Format ◽  
Output File ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Protein Protein Interaction ◽  
Visualization Tools

Several visualization tools for the mapping of protein-protein interactions have been developed in recent years. However, a systematic comparison of the virtues and limitations of different PPI visualization tools has not been carried out so far. In this study, we compare seven commonly used visualization tools, based on input and output file format, layout algorithm, database integration, Gene Ontology annotation and accessibility of each tool. The assessment was carried out based on brain disease datasets. Our suggested tools, NAViGaTOR, Cytoscape and Gephi perform competitively as PPI network visualization tools, can be a reference for future researches on PPI mapping and analysis. 

scholarly journals Systematic identification of signal integration by protein kinase A

2015 ◽  
Vol 112 (14) ◽  
pp. 4501-4506 ◽  
Author(s):  
Marie Filteau ◽  
Guillaume Diss ◽  
Francisco Torres-Quiroz ◽  
Alexandre K. Dubé ◽  
Andrea Schraffl ◽  
...  
Keyword(s):  
Protein Kinase ◽  
Protein Kinase A ◽  
Protein Interactions ◽  
Carbon Sources ◽  
Biological Processes ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Complex Formation ◽  
Growth And Aging ◽  
Kinase A

Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein–protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA.

scholarly journals SUMO-specific Isopeptidases Tuning Cardiac SUMOylation in Health and Disease

2021 ◽  
Vol 8 ◽  
Author(s):  
Paul W. Hotz ◽  
Stefan Müller ◽  
Luca Mendler
Keyword(s):  
Protein Interactions ◽  
Cardiovascular Health ◽  
Current Knowledge ◽  
Chromatin Binding ◽  
Protein Protein Interactions ◽  
Target Proteins ◽  
Cellular Processes ◽  
Cardiac Functions ◽  
Health And Disease ◽  
Rapid Kinetics

SUMOylation is a transient posttranslational modification with small-ubiquitin like modifiers (SUMO1, SUMO2 and SUMO3) covalently attached to their target-proteins via a multi-step enzymatic cascade. SUMOylation modifies protein-protein interactions, enzymatic-activity or chromatin binding in a multitude of key cellular processes, acting as a highly dynamic molecular switch. To guarantee the rapid kinetics, SUMO target-proteins are kept in a tightly controlled equilibrium of SUMOylation and deSUMOylation. DeSUMOylation is maintained by the SUMO-specific proteases, predominantly of the SENP family. SENP1 and SENP2 represent family members tuning SUMOylation status of all three SUMO isoforms, while SENP3 and SENP5 are dedicated to detach mainly SUMO2/3 from its substrates. SENP6 and SENP7 cleave polySUMO2/3 chains thereby countering the SUMO-targeted-Ubiquitin-Ligase (StUbL) pathway. Several biochemical studies pinpoint towards the SENPs as critical enzymes to control balanced SUMOylation/deSUMOylation in cardiovascular health and disease. This study aims to review the current knowledge about the SUMO-specific proteases in the heart and provides an integrated view of cardiac functions of the deSUMOylating enzymes under physiological and pathological conditions.

An Integrated Prediction Method for Identifying Protein-Protein Interactions

2020 ◽  
Vol 17 (4) ◽  
pp. 271-286
Author(s):  
Chang Xu ◽  
Limin Jiang ◽  
Zehua Zhang ◽  
Xuyao Yu ◽  
Renhai Chen ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Feature Vector ◽  
Prediction Method ◽  
Feature Representation ◽  
Protein Interaction Networks ◽  
Learning Approach ◽  
Biological Processes ◽  
Integrated Learning ◽  
Protein Protein Interactions ◽  
Training Process

Background: Protein-Protein Interactions (PPIs) play a key role in various biological processes. Many methods have been developed to predict protein-protein interactions and protein interaction networks. However, many existing applications are limited, because of relying on a large number of homology proteins and interaction marks. Methods: In this paper, we propose a novel integrated learning approach (RF-Ada-DF) with the sequence-based feature representation, for identifying protein-protein interactions. Our method firstly constructs a sequence-based feature vector to represent each pair of proteins, viaMultivariate Mutual Information (MMI) and Normalized Moreau-Broto Autocorrelation (NMBAC). Then, we feed the 638- dimentional features into an integrated learning model for judging interaction pairs and non-interaction pairs. Furthermore, this integrated model embeds Random Forest in AdaBoost framework and turns weak classifiers into a single strong classifier. Meanwhile, we also employ double fault detection in order to suppress over-adaptation during the training process. Results: To evaluate the performance of our method, we conduct several comprehensive tests for PPIs prediction. On the H. pyloridataset, our method achieves 88.16% accuracy and 87.68% sensitivity, the accuracy of our method is increased by 0.57%. On the S. cerevisiaedataset, our method achieves 95.77% accuracy and 93.36% sensitivity, the accuracy of our method is increased by 0.76%. On the Humandataset, our method achieves 98.16% accuracy and 96.80% sensitivity, the accuracy of our method is increased by 0.6%. Experiments show that our method achieves better results than other outstanding methods for sequence-based PPIs prediction. The datasets and codes are available at https://github.com/guofei-tju/RF-Ada-DF.git.

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

2018 ◽  
Vol 25 (1) ◽  
pp. 5-21 ◽  
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.

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

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.

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

2018 ◽  
Vol 18 (20) ◽  
pp. 1719-1736 ◽  
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.

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

2018 ◽  
Vol 14 ◽  
pp. 2881-2896 ◽  
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.

scholarly journals Assay Systems for Profiling Deubiquitinating Activity

2020 ◽  
Vol 21 (16) ◽  
pp. 5638
Author(s):  
Jinhong Cho ◽  
Jinyoung Park ◽  
Eunice EunKyeong Kim ◽  
Eun Joo Song
Keyword(s):  
Protein Degradation ◽  
Protein Interactions ◽  
Live Cells ◽  
Deubiquitinating Enzyme ◽  
Protein Protein Interactions ◽  
Deubiquitinating Enzymes ◽  
Cell Lysates ◽  
Cellular Processes

Deubiquitinating enzymes regulate various cellular processes, particularly protein degradation, localization, and protein–protein interactions. The dysregulation of deubiquitinating enzyme (DUB) activity has been linked to several diseases; however, the function of many DUBs has not been identified. Therefore, the development of methods to assess DUB activity is important to identify novel DUBs, characterize DUB selectivity, and profile dynamic DUB substrates. Here, we review various methods of evaluating DUB activity using cell lysates or purified DUBs, as well as the types of probes used in these methods. In addition, we introduce some techniques that can deliver DUB probes into the cells and cell-permeable activity-based probes to directly visualize and quantify DUB activity in live cells. This review could contribute to the development of DUB inhibitors by providing important information on the characteristics and applications of various probes used to evaluate and detect DUB activity in vitro and in vivo.

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