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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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Department: search.filters.department.Department of Computer EngineeringSubject: search.filters.subject.Biochemistry

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Now showing 1 - 10 of 29
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    Enriching the human apoptosis pathway by predicting the structures of protein-protein complexes
    (Elsevier, 2012) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Özbabacan, Saliha Ece Acuner; Faculty Member; Faculty Member; PhD Student; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26605; 8745; 264351
    Apoptosis is a matter of life and death for cells and both inhibited and enhanced apoptosis may be involved in the pathogenesis of human diseases. The structures of protein-protein complexes in the apoptosis signaling pathway are important as the structural pathway helps in understanding the mechanism of the regulation and information transfer, and in identifying targets for drug design. Here, we aim to predict the structures toward a more informative pathway than currently available. Based on the 3D structures of complexes in the target pathway and a protein-protein interaction modeling tool which allows accurate and proteome-scale applications, we modeled the structures of 29 interactions, 21 of which were previously unknown. Next, 27 interactions which were not listed in the KEGG apoptosis pathway were predicted and subsequently validated by the experimental data in the literature. Additional interactions are also predicted. The multi-partner hub proteins are analyzed and interactions that can and cannot co-exist are identified. Overall, our results enrich the understanding of the pathway with interactions and provide structural details for the human apoptosis pathway. They also illustrate that computational modeling of protein-protein interactions on a large scale can help validate experimental data and provide accurate, structural atom-level detail of signaling pathways in the human cell.
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    Hot spots in protein-protein interfaces: towards drug discovery
    (Elsevier, 2014) N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Çukuroğlu, Engin; Engin, Hatice Billur; Gürsoy, Attila; Keskin, Özlem; PhD Student; PhD Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; N/A; College of Engineering; College of Engineering; N/A; N/A; 8745; 26605
    Identification of drug-like small molecules that alter protein-protein interactions might be a key step in drug discovery. However, it is very challenging to find such molecules that target interface regions in protein complexes. Recent findings indicate that such molecules usually target specifically energetically favored residues (hot spots) in protein protein interfaces. These residues contribute to the stability of protein-protein complexes. Computational prediction of hot spots on bound and unbound structures might be useful to find druggable sites on target interfaces. We review the recent advances in computational hot spot prediction methods in the first part of the review and then provide examples on how hot spots might be crucial in drug design. (C) 2014 Published by Elsevier Ltd.
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    Structural cooperativity in histone H3 tail modifications
    (Wiley, 2011) N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Şanlı, Deniz; Keskin, Özlem; Gürsoy, Attila; Erman, Burak; Researcher; Faculty Member; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; 26605; 8745; 179997
    Post-translational modifications of histone H3 tails have crucial roles in regulation of cellular processes. There is cross-regulation between the modifications of K4, K9, and K14 residues. The modifications on these residues drastically promote or inhibit each other. In this work, we studied the structural changes of the histone H3 tail originating from the three most important modifications; tri-methylation of K4 and K9, and acetylation of K14. We performed extensive molecular dynamics simulations of four types of H3 tails: (i) the unmodified H3 tail having no chemical modification on the residues, (ii) the tri-methylated lysine 4 and lysine 9 H3 tail (K4me3K9me3), (iii) the tri-methylated lysine 4 and acetylated lysine 14 H3 tail (K4me3K14ace), and (iv) tri-methylated lysine 9 and acetylated lysine 14 H3 tail (K9me3K14ace). Here, we report the effects of K4, K9, and K14 modifications on the backbone torsion angles and relate these changes to the recognition and binding of histone modifying enzymes. According to the Ramachandran plot analysis; (i) the dihedral angles of K4 residue are significantly affected by the addition of three methyl groups on this residue regardless of the second modification, (ii) the dihedral angle values of K9 residue are similarly altered majorly by the tri-methylation of K4 residue, (iii) different combinations of modifications (tri-methylation of K4 and K9, and acetylation of K14) have different influences on phi and psi values of K14 residue. Finally, we discuss the consequences of these results on the binding modes and specificity of the histone modifying enzymes such as DIM-5, GCN5, and JMJD2A.
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    TRAF3 signaling: Competitive binding and evolvability of adaptive viral molecular mimicry
    (Elsevier, 2016) Guven-Maiorov, Emine; VanWaes, Carter; Chen, Zhong; Tsai, Chung-Jung; Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Faculty Member; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; 26605; 8745
    Background: The tumor necrosis factor receptor (TNFR) associated factor 3 (TRAF3) is a key node in innate and adaptive immune signaling pathways. TRAF3 negatively regulates the activation of the canonical and non canonical NF-kappa B pathways and is one of the key proteins in antiviral immunity. Scope of Review: Here we provide a structural overview of TRAF3 signaling in terms of its competitive binding and consequences to the cellular network. For completion, we also include molecular mimicry of TRAF3 physiological partners by some viral proteins. Major Conclusions: By out-competing host partners, viral proteins aim to subvert TRAF3 antiviral action. Mechanistically, dynamic, competitive binding by the organism's own proteins and same-site adaptive pathogen mimicry follow the same conformational selection principles. General Significance: Our premise is that irrespective of the eliciting event - physiological or acquired pathogenic trait - pathway activation (or suppression) may embrace similar conformational principles. However, even though here we largely focus on competitive binding at a shared site, similar to physiological signaling other pathogen subversion mechanisms can also be at play. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.
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    Embedding alternative conformations of proteins in protein–protein interaction networks
    (Humana Press inc, 2020) N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Halakou, Farideh; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 8745; 26605
    While many proteins act alone, the majority of them interact with others and form molecular complexes to undertake biological functions at both cellular and systems levels. Two proteins should have complementary shapes to physically connect to each other. As proteins are dynamic and changing their conformations, it is vital to track in which conformation a specific interaction can happen. Here, we present a step-by-step guide to embedding the protein alternative conformations in each protein–protein interaction in a systems level. All external tools/websites used in each step are explained, and some notes and suggestions are provided to clear any ambiguous point.
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    Membrane-associated Ras dimers are isoform-specific: K-Ras dimers differ from H-Ras dimers
    (Portland Press Ltd, 2016) Nussinov, Ruth; Jang, Hyunbum; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Muratçıoğlu, Serena; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 26605; 8745
    Are the dimer structures of active Ras isoforms similar? This question is significant since Ras can activate its effectors as a monomer; however, as a dimer, it promotes Raf's activation and MAPK (mitogen-activated protein kinase) cell signalling. In the present study, we model possible catalytic domain dimer interfaces of membrane-anchored GTP-bound K-Ras4B and H-Ras, and compare their conformations. The active helical dimers formed by the allosteric lobe are isoform-specific: K-Ras4B-GTP favours the alpha 3 and alpha 4 interface; H-Ras-GTP favours alpha 4 and alpha 5. Both isoforms also populate a stable beta-sheet dimer interface formed by the effector lobe; a less stable beta-sandwich interface is sustained by salt bridges of the beta-sheet side chains. Raf's high-affinity beta-sheet interaction is promoted by the active helical interface. Collectively, Ras isoforms' dimer conformations are not uniform; instead, the isoform-specific dimers reflect the favoured interactions of the HVRs (hypervariable regions) with cell membrane microdomains, biasing the effector-binding site orientations, thus isoform binding selectivity.
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    Interactions and dynamics of ras
    (Wiley, 2017) Jang, H.; Nussinov, R.; Department of Chemical and Biological Engineering; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Muratçıoğlu, Serena; Gürsoy, Attila; Faculty Member; PhD Student; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 26605; N/A; 8745
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    Characterization and prediction of protein interfaces to infer protein-protein interaction networks
    (Bentham Science Publ Ltd, 2008) N/A; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Tunçbağ, Nurcan; Gürsoy, Attila; Faculty Member; Faculty Member; Faculty Member; College of Engineering; College of Engineering; College of Engineering; 26605; 245513; 8745
    Complex protein-protein interaction networks govern biological processes in cells. Protein interfaces are the sites where proteins physically interact. Identification and characterization of protein interfaces will lead to understanding how proteins interact with each other and how they are involved in protein-protein interaction networks. What makes a given interface bind to different proteins; how similar/different the interactions in proteins are some key questions to be answered. Enormous amount of protein structures and experimental protein-protein interactions data necessitate advanced computational methods for analyzing and inferring new knowledge. Interface prediction methods use a wide range of sequence, structural and physico-chemical characteristics that distinguish interface residues from non-interface surface residues. Here, we present a review focusing on the characteristics of interfaces and the current status of interface prediction methods.
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    GTP-dependent K-Ras dimerization
    (Cell Press, 2015) Chavan, Tanmay S.; Freed, Benjamin C.; Jang, Hyunbum; Khavrutskii, Lyuba; Freed, R. Natasha; Dyba, Marzena A.; Stefanisko, Karen; Tarasov, Sergey G.; Gursoy, Attila; Keskin, Ozlem; Tarasova, Nadya I.; Gaponenko, Vadim; Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Muratçıoğlu, Serena; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 26605; 8745
    Ras proteins recruit and activate effectors, including Raf, that transmit receptor-initiated signals. Monomeric Ras can bind Raf; however, activation of Raf requires its dimerization. It has been suspected that dimeric Ras may promote dimerization and activation of Raf. Here, we show that the GTP-bound catalytic domain of K-Ras4B, a highly oncogenic splice variant of the K-Ras isoform, forms stable homodimers. We observe two major dimer interfaces. The first, highly populated beta-sheet dimer interface is at the Switch I and effector binding regions, overlapping the binding surfaces of Raf, PI3K, RalGDS, and additional effectors. This interface has to be inhibitory to such effectors. The second, helical interface also overlaps the binding sites of some effectors. This interface may promote activation of Raf. Our data reveal how Ras self-association can regulate effector binding and activity, and suggest that disruption of the helical dimer interface by drugs may abate Raf signaling in cancer.
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    Expanding the conformational selection paradigm in protein-ligand docking
    (Humana Press Inc, 2012) Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Kuzu, Güray; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Faculty Member; N/A; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 26605; 8745
    Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein-protein, protein-DNA, protein-RNA, and protein-small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery. Actually, in practice this has already been taking place for some years in increasing numbers. Essentially, it argues for using not a single conformer, but an ensemble. The paradigm of conformational selection holds that because the ensemble is heterogeneous, within it there will be states whose conformation matches that of the ligand. Even if the population of this state is low, since it is favorable for binding the ligand, it will bind to it with a subsequent population shift toward this conformer. Here we suggest expanding it by first modeling all protein interactions in the cell by using Prism, an efficient motif-based protein-protein interaction modeling strategy, followed by ensemble generation. Such a strategy could be particularly useful for signaling proteins, which are major targets in drug discovery and bind multiple partners through a shared binding site, each with some-minor or major-conformational change.