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Department: search.filters.department.Department of Computer EngineeringSubject: search.filters.subject.Science and technology

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Now showing 1 - 4 of 4
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    PublicationOpen Access
    Enriching traditional proteinprotein interaction networks with alternative conformations of proteins
    (Nature Publishing Group (NPG), 2017) Halakou, Farideh; Kılıç, Emel Şen; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; 26605; 8745
    Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation, lack some valuable information about the mechanistic details of biological processes. Mapping protein structures to these PPI networks not only provides structural details of each interaction but also helps us to find the mutual exclusive interactions. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different interactions, functions, and downstream signaling. In this study, we proposed a new representation for structural PPI networks inspecting the alternative conformations of proteins. We performed a large-scale study by creating breast cancer metastasis network and equipped it with different conformers of proteins. Our results showed that although 88% of proteins in our network has at least two structures in Protein Data Bank (PDB), only 22% of them have alternative conformations and the remaining proteins have different regions saved in PDB. However, using even this small set of alternative conformations we observed a considerable increase in our protein docking predictions. Our protein-protein interaction predictions increased from 54% to 76% using the alternative conformations. We also showed the benefits of investigating structural data and alternative conformations of proteins through three case studies.
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    PublicationOpen Access
    Interactome analysis of Bag-1 isoforms reveals novel interaction partners in endoplasmic reticulum-associated degradation
    (Public Library of Science, 2021) Can, Nisan Denizce; Baştürk, Ezgi; Kızılboğa, Tuğba; Akçay, İzzet Mehmet; Dingiloğlu, Baran; Tatlı, Özge; Acar, Sevilay; Kılbaş, Pelin Özfiliz; Jannuzzi, Ayşe Tarbin; Doğanay, Hamdi Levent; Yılmaz, Betül Karademir; Doğanay, Gizem Dinler; Department of Computer Engineering; Department of Chemical and Biological Engineering; Gürsoy, Attila; Keskin, Özlem; Elbeyli, Efe; Muratçıoğlu, Serena; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Engineering; 8745; 26605; N/A; N/A
    Bag-1 is a multifunctional protein that regulates Hsp70 chaperone activity, apoptosis, and proliferation. The three major Bag-1 isoforms have different subcellular localizations and partly non-overlapping functions. To identify the detailed interaction network of each isoform, we utilized mass spectrometry-based proteomics and found that interactomes of Bag-1 isoforms contained many common proteins, with variations in their abundances. Bag-1 interactomes were enriched with proteins involved in protein processing and degradation pathways. Novel interaction partners included VCP/p97; a transitional ER ATPase, Rad23B; a shuttling factor for ubiquitinated proteins, proteasome components, and ER-resident proteins, suggesting a role for Bag-1 also in ER-associated protein degradation (ERAD). Bag-1 pull-down from cells and tissues from breast cancer patients validated these interactions and showed cancer-related prominence. Using in silico predictions we detected hotspot residues of Bag-1. Mutations of these residues caused loss of binding to protein quality control elements and impaired proteasomal activity in MCF-7 cells. Following CD147 glycosylation pattern, we showed that Bag-1 downregulated VCP/p97-dependent ERAD. Overall, our data extends the interaction map of Bag-1, and broadens its role in protein homeostasis. Targeting the interaction surfaces revealed in this study might be an effective strategy in the treatment of cancer.
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    PublicationOpen Access
    Structural pathways of cytokines may illuminate their roles in regulation of cancer development and immunotherapy
    (Multidisciplinary Digital Publishing Institute (MDPI), 2014) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; Maiorov, Emine Güven; Özbabacan, Saliha Ece Acuner; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; N/A; 26605; 8745
    Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-?. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching-PRISM). © 2014 by the authors; licensee MDPI, Basel, Switzerland.
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    PublicationOpen Access
    The structural network of Interleukin-10 and its implications in inflammation and cancer
    (BioMed Central, 2014) Chen, Zhong; Van Waes, Carter; Nussinov, Ruth; Department of Computer Engineering; Özbabacan, Saliha Ece Acuner; Engin, Hatice Billur; Maiorov, Emine Güven; Kuzu, Güray; Muratçıoğlu, Serena; Başpınar, Alper; Gürsoy, Attila; PhD Student; Faculty Member; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; N/A; N/A; N/A; N/A; N/A; 8745
    Background: Inflammation has significant roles in all phases of tumor development, including initiation, progression and metastasis. Interleukin-10 (IL-10) is a well-known immuno-modulatory cytokine with an anti-inflammatory activity. Lack of IL-10 allows induction of pro-inflammatory cytokines and hinders anti-tumor immunity, thereby favoring tumor growth. The IL-10 network is among the most important paths linking cancer and inflammation. The simple node-and-edge network representation is useful, but limited, hampering the understanding of the mechanistic details of signaling pathways. Structural networks complete the missing parts, and provide details. The IL-10 structural network may shed light on the mechanisms through which disease-related mutations work and the pathogenesis of malignancies. Results: Using PRISM (a PRotein Interactions by Structural Matching tool), we constructed the structural network of IL-10, which includes its first and second degree protein neighbor interactions. We predicted the structures of complexes involved in these interactions, thereby enriching the available structural data. In order to reveal the significance of the interactions, we exploited mutations identified in cancer patients, mapping them onto key proteins of this network. We analyzed the effect of these mutations on the interactions, and demonstrated a relation between these and inflammation and cancer. Our results suggest that mutations that disrupt the interactions of IL-10 with its receptors (IL-10RA and IL-10RB) and alpha 2-macroglobulin (A2M) may enhance inflammation and modulate anti-tumor immunity. Likewise, mutations that weaken the A2M-APP (amyloid precursor protein) association may increase the proliferative effect of APP through preventing beta-amyloid degradation by the A2M receptor, and mutations that abolish the A2M-Kallikrein-13 (KLK13) interaction may lead to cell proliferation and metastasis through the destructive effect of KLK13 on the extracellular matrix. Conclusions: Prediction of protein-protein interactions through structural matching can enrich the available cellular pathways. In addition, the structural data of protein complexes suggest how oncogenic mutations influence the interactions and explain their potential impact on IL-10 signaling in cancer and inflammation.