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Publication Open Access HotRegion: a database of predicted hot spot clusters(Oxford University Press (OUP), 2012) N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Çukuroğlu, Engin; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 8745; 26605Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided.Publication Open Access HotSprint: database of computational hot spots in protein interfaces(Oxford University Press (OUP), 2008) Tunçbağ, Nurcan; Department of Electrical and Electronics Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Güney, Emre; Keskin, Özlem; Gürsoy, Attila; Master Student; Faculty Member; Department of Electrical and Electronics Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 26605; 8745We present a new database of computational hot spots in protein interfaces: HotSprint. Hot spots are residues comprising only a small fraction of interfaces yet accounting for the majority of the binding energy. HotSprint contains data for 35 776 protein interfaces among 49 512 protein interfaces extracted from the multi-chain structures in Protein Data Bank (PDB) as of February 2006. The conserved residues in interfaces with certain buried accessible solvent area (ASA) and complex ASA thresholds are flagged as computational hot spots. The predicted hot spots are observed to correlate with the experimental hot spots with an accuracy of 76. Several machine-learning methods (SVM, Decision Trees and Decision Lists) are also applied to predict hot spots, results reveal that our empirical approach performs better than the others. A web interface for the HotSprint database allows users to browse and query the hot spots in protein interfaces; and it provides information for interface residues that are functionally and structurally important as well as the evolutionary history and solvent accessibility of residues in interfaces.Publication Open Access Mode coupling points to functionally important residues in myosin II(Wiley, 2014) Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Physics; Varol, Onur; Yüret, Deniz; Erman, Burak; Kabakçıoğlu, Alkan; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Physics; Graduate School of Sciences and Engineering; College of Engineering; College of Sciences; N/A; 179996; 179997; 49854Relevance of mode coupling to energy/information transfer during protein function, particularly in the context of allosteric interactions is widely accepted. However, existing evidence in favor of this hypothesis comes essentially from model systems. We here report a novel formal analysis of the near-native dynamics of myosin II, which allows us to explore the impact of the interaction between possibly non-Gaussian vibrational modes on fluctutational dynamics. We show that an information-theoretic measure based on mode coupling alone yields a ranking of residues with a statistically significant bias favoring the functionally critical locations identified by experiments on myosin II.Publication Open Access PRISM: a web server and repository for prediction of protein-protein interactions and modeling their 3D complexes(Oxford University Press (OUP), 2014) Nussinov, Ruth; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Başpınar, Alper; Çukuroğlu, Engin; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 26605; 8745The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs). The prediction algorithm is knowledge-based. It combines structural similarity and accounts for evolutionary conservation in the template interfaces. The predicted models are stored in its repository. Given two protein structures, PRISM will provide a structural model of their complex if a matching template interface is available. Users can download the complex structure, retrieve the interface residues and visualize the complex model.Publication Open Access PRISM: protein interactions by structural matching(Oxford University Press (OUP), 2005) Nussinov, Ruth; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Öğmen, Utkan; Keskin, Özlem; Aytuna, Ali Selim; Gürsoy, Attila; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 26605; N/A; 8745Prism (https://gordion.hpc.eng.ku.edu.tr/prism) is a website for protein interface analysis and prediction of putative protein-protein interactions. It is composed of a database holding protein interface structures derived from the Protein Data Bank (PDB). The server also includes summary information about related proteins and an interactive protein interface viewer. A list of putative protein-protein interactions obtained by running our prediction algorithm can also be accessed. These results are applied to a set of protein structures obtained from the PDB at the time of algorithm execution (January 2004). Users can browse through the non-redundant dataset of representative interfaces on which the prediction algorithm depends, retrieve the list of similar structures to these interfaces or see the results of interaction predictions for a particular protein. Another service provided is interactive prediction. This is done by running the algorithm for user input structures.
Publication Metadata only Transient proteinprotein interactions(Oxford Univ Press, 2011) N/A; N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Özbabacan, Saliha Ece Acuner; Engin, Hatice Billur; Gürsoy, Attila; Keskin, Özlem; PhD Student; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 264351; N/A; 8745; 26605Transient complexes are crucial for diverse biological processes such as biochemical pathways and signaling cascades in the cell. Here, we give an overview of the transient interactions; the importance of transient interactions as drug targets; and the structural characterization of transient proteinprotein complexes based on the geometrical and physicochemical features of the transient complexes' interfaces. To better understand and eventually design transient proteinprotein interactions (TPPIs), a molecular perspective of the proteinprotein interfaces is necessary. Obtaining high-quality structures of proteinprotein interactions could be one way of achieving this goal. After introducing the association kinetics of TPPIs, we elaborate on the experimental techniques detecting TPPIs in combination with the computational methods which classify transient and/or non-obligate complexes. In this review, currently available databases and servers that can be used to identify and predict TPPIs are also compiled.Publication Open Access Unraveling the molecular mechanism of interactions of the Rho GTPases Cdc42 and Rac1 with the scaffolding protein IQGAP2(American Society for Biochemistry and Molecular Biology (ASBMB), 2018) Jang, Hyunbum; Li, Zhigang; Sacks, David B.; Nussinov, Ruth; Department of Computer Engineering; Department of Chemical and Biological Engineering; Gürsoy, Attila; Keskin, Özlem; Özdemir, E. Sıla; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Engineering; Graduate School of Sciences and Engineering; 8745; 26605; N/AIQ motif-containing GTPase-activating proteins (IQGAPs) are scaffolding proteins playing central roles in cell-cell adhesion, polarity, and motility. The Rho GTPases Cdc42 and Rac1, in their GTP-bound active forms, interact with all three human IQGAPs. The IQGAP-Cdc42 interaction promotes metastasis by enhancing actin polymerization. However, despite their high sequence identity, Cdc42 and Rac1 differ in their interactions with IQGAP. Two Cdc42 molecules can bind to the Ex-domain and the RasGAP site of the GTPase-activating protein (GAP)related domain (GRD) of IQGAP and promote IQGAP dimerization. Only one Rac1 molecule might bind to the RasGAP site of GRD and may not facilitate the dimerization, and the exact mechanism of Cdc42 and Rac1 binding to IQGAP is unclear. Using all-atom molecular dynamics simulations, site-directed mutagenesis, and Western blotting, we unraveled the detailed mechanisms of Cdc42 and Rac1 interactions with IQGAP2. We observed that Cdc42 binding to the Ex-domain of GRD of IQGAP2 (GRD2) releases the Ex-domain at the C-terminal region of GRD2, facilitating IQGAP2 dimerization. Cdc42 binding to the Ex-domain promoted allosteric changes in the RasGAP site, providing a binding site for the second Cdc42 in the RasGAP site. Of note, the Cdc42 "insert loop" was important for the interaction of the first Cdc42 with the Ex-domain. By contrast, differences in Rac1 insert-loop sequence and structure precluded its interaction with the Ex-domain. Rac1 could bind only to the RasGAP site of apo-GRD2 and could not facilitate IQGAP2 dimerization. Our detailed mechanistic insights help decipher how Cdc42 can stimulate actin polymerization in metastasis.