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1.
Int J Mol Sci ; 23(22)2022 Nov 17.
Article in English | MEDLINE | ID: covidwho-2295420

ABSTRACT

MSClustering is an efficient software package for visualizing and analyzing complex networks in Cytoscape. Based on the distance matrix of a network that it takes as input, MSClustering automatically displays the minimum span clustering (MSC) of the network at various characteristic levels. To produce a view of the overall network structure, the app then organizes the multi-level results into an MSC tree. Here, we demonstrate the package's phylogenetic applications in studying the evolutionary relationships of complex systems, including 63 beta coronaviruses and 197 GPCRs. The validity of MSClustering for large systems has been verified by its clustering of 3481 enzymes. Through an experimental comparison, we show that MSClustering outperforms five different state-of-the-art methods in the efficiency and reliability of their clustering.


Subject(s)
Computational Biology , Software , Computational Biology/methods , Phylogeny , Reproducibility of Results , Cluster Analysis
2.
J Proteome Res ; 22(2): 637-646, 2023 02 03.
Article in English | MEDLINE | ID: covidwho-2160141

ABSTRACT

Biological networks are often used to represent complex biological systems, which can contain several types of entities. Analysis and visualization of such networks is supported by the Cytoscape software tool and its many apps. While earlier versions of stringApp focused on providing intraspecies protein-protein interactions from the STRING database, the new stringApp 2.0 greatly improves the support for heterogeneous networks. Here, we highlight new functionality that makes it possible to create networks that contain proteins and interactions from STRING as well as other biological entities and associations from other sources. We exemplify this by complementing a published SARS-CoV-2 interactome with interactions from STRING. We have also extended stringApp with new data and query functionality for protein-protein interactions between eukaryotic parasites and their hosts. We show how this can be used to retrieve and visualize a cross-species network for a malaria parasite, its host, and its vector. Finally, the latest stringApp version has an improved user interface, allows retrieval of both functional associations and physical interactions, and supports group-wise enrichment analysis of different parts of a network to aid biological interpretation. stringApp is freely available at https://apps.cytoscape.org/apps/stringapp.


Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Software , Proteins , Eukaryota
3.
LETTERS IN DRUG DESIGN & DISCOVERY ; 19(5):397-412, 2022.
Article in English | Web of Science | ID: covidwho-1938552

ABSTRACT

Background: Glycyrrhiza uralensis, also known as liquorice, is a herbal remedy that is traditionally used worldwide for treating respiratory ailments and ameliorating breathing. Objective: The objective of this systematic study was to investigate active ingredients of Glycyrrhiza uralensis and determine its mode of action in silico against severe and acute respiratory complications of respiratory ailments through network pharmacology and molecular docking studies. Methods: TCMSP database search helped retrieve the compounds of Glycyrrhiza uralensis and their protein targets, especially related to respiratory ailments. Subsequently, the protein-protein association was attained as a network by using the STITCH database. Cytoscape and its ClueGO plugin were used to study gene ontology (GO) enrichment. In addition, seven natural compounds were docked in the active site of four different molecular targets;JUN-FOS, COX2, MAPK14 and IL-6, to identify the binding mechanism of ligands under study. Results: TCMSP database search resulted in the retrieval of 280 compounds of Glycyrrhiza uralensis (including formononetin, naringenin, sitosterol, isorhamnetin, kaempferol, quercetin and Glycyrrhizin) and 135 protein targets. A careful study of targets showed that 26 prospective targets (including JUN, FOS, IL6, MAPK14 and PTGS2) related to respiratory ailments were identified. Gene ontology (GO) enrichment analysis resulted in the retrieval of 176 GO terms, which were associated with respiratory ailments. This study proposed that Glycyrrhiza uralensis acts against respiratory ailments through various proteins, such as JUN, FOS, IL6, MAPK14 and PTGS2. Docking results revealed that among all studied ligands, the flavonoid-based compounds isorhamnetin and kaempferol form stronger complexes with JUN-FOS-DNA, MAPK-14, and IL-6 proteins (Cscore=6.81, 4.27, and 4.77, respectively) and the saponin based compound glycyrrhizin (Cscore=13.07) demonstrated stronger binding affinity towards COX2 enzyme. Conclusion: Conclusively, isorhamnetin, kaempferol and glycyrrhizin in Glycyrrhiza uralensis may regulate several signaling pathways through JUN-FOS-DNA, MAPK-14, and IL-6, which might play a therapeutic role against respiratory ailments.

4.
Cells ; 10(9)2021 08 29.
Article in English | MEDLINE | ID: covidwho-1374308

ABSTRACT

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine-cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from the literature and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated the literature information on cell-cytokine interactions from two systems of immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink, we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify cell types and cytokine interactions following SARS-CoV-2 infection, highlighting important cytokine interactions that might contribute to severe illness in a subgroup of patients. Such findings have the potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository.


Subject(s)
COVID-19/immunology , Cytokines/metabolism , Immunity , Inflammatory Bowel Diseases/immunology , Cell Communication , Colitis, Ulcerative/immunology , Colitis, Ulcerative/pathology , Databases, Genetic , Humans , Inflammatory Bowel Diseases/pathology , Signal Transduction
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