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Publication Metadata only A new dataset of protein-protein interfaces(Cell Press, 2007) Güney, Emre; Nussinov, Ruth; Tsai, C. J.; Department of Computer Engineering; Department of Chemical and Biological Engineering; Gürsoy, Attila; Keskin, Özlem; Tunçbağ, Nurcan; Faculty Member; Faculty Member; PhD Student; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Engineering; College of Engineering; 8745; 26605; 245513Publication Metadata only Analysis and network representation of hotspots in protein interfaces using minimum cut trees(Wiley, 2010) Department of Chemical and Biological Engineering; Department of Industrial Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Tunçbağ, Nurcan; Salman, Fatma Sibel; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Department of Industrial Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; College of Engineering; College of Engineering; 245513; 178838; 26605; 8745We propose a novel approach to analyze and visualize residue contact networks of protein interfaces by graph-based algorithms using a minimum cut tree (mincut tree). Edges in the network are weighted according to an energy function derived from knowledge-based potentials. The mincut tree, which is constructed from the weighted residue network, simplifies and summarizes the complex structure of the contact network by an efficient and informative representation. This representation offers a comprehensible view of critical residues and facilitates the inspection of their organization. We observed, on a nonredundant data set of 38 protein complexes with experimental hotspots that the highest degree node in the mincut tree usually corresponds to an experimental hotspot. Further, hotspots are found in a few paths in the mincut tree. In addition, we examine the organization of hotspots (hot regions) using an iterative clustering algorithm on two different case studies. We find that distinct hot regions are located on specific sites of the mincut tree and some critical residues hold these clusters together. Clustering of the interface residues provides information about the relation of hot regions with each other. Our new approach is useful at the molecular level for both identification of critical paths in the protein interfaces and extraction of hot regions by clustering of the interface residues.Publication Metadata only Anharmonicity, mode-coupling and entropy in a fluctuating native protein(Iop Publishing Ltd, 2010) N/A; Department of Physics; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Kabakçıoğlu, Alkan; Yüret, Deniz; Gür, Mert; Erman, Burak; Faculty Member; Faculty Member; PhD Student; Faculty Member; Department of Physics; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 49854; 179996; 216930; 179997We develop a general framework for the analysis of residue fluctuations that simultaneously incorporates anharmonicity and mode-coupling in a unified formalism. We show that both deviations from the Gaussian model are important for modeling the multidimensional energy landscape of the protein Crambin (1EJG) in the vicinity of its native state. the effect of anharmonicity and mode-coupling on the fluctuational entropy is in the order of a few percent.Publication Metadata only Combining protein-protein interaction networks with structures(Cell Press, 2009) Nussinov, Ruth; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Kar, Gözde; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 8745; 26605Publication Metadata only Computational basis of knowledge-based conformational probabilities derived from local- and long-range interactions in proteins(Wiley-Liss, 2007) N/A; Department of Industrial Engineering; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Örmeci, Lerzan; Gürsoy, Attila; Tunca, Güzin; Erman, Burak; Faculty Member; Faculty Member; Master Student; Faculty Member; Department of Industrial Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 32863; 8745; N/A; 179997The probabilities of the various basins in Ramachandran maps are examined critically. The theoretical basis of probability calculations both from molecular computations and from protein libraries are discussed. The well-defined basins of the Ramachandran maps are treated as rotational isomeric states. Statistical independence and dependence of the states of different residues along the peptide chain are discussed. The Flory isolated pair hypothesis, near neighbor correlations, context effects, and long-range correlations are examined critically. A method of evaluating long-range correlations in helical and extended sequences is introduced in analogy with earlier polymer theory. Three different protein libraries are constructed where data is considered from residues in the M coiled regions, (ii) all regions, and (iii) only the helical and extended regions of proteins. Singlet and pairwise dependent probabilities calculated from these libraries are used to predict whether a given sequence is helical or extended. Predictions using pairwise dependence were not better than those using singlet probabilities. Modeling of long-range correlations improved the predictions significantly. Removal of the Chameleon sequences from the data set also improved the predictions, but to a lesser extent.Publication Metadata only Conformational energies and entropies of peptides, and the peptide-protein binding problem(IOP Publishing Ltd, 2009) N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Ünal, Evrim Besray; Gürsoy, Attila; Erman, Burak; 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; College of Engineering; College of Engineering; N/A; 8745; 179997A novel statistical thermodynamic approach is applied to free-peptide segments in order to classify them according to their conformational energies, entropies and heat capacities. Our approach employs the rotational isomeric state (RIS) model in which the states are described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the pairwise-dependent states are derived from the torsion angle probabilities of the consecutive dipeptides in a coil library. The partition function is determined for a given sequence via RIS multiplication of the pre-determined matrices. The conformational partition function, Helmholtz free energy, energy, entropy and heat capacity are obtained. The model is applied to randomly produced peptides and also to known peptide inhibitors to analyze their thermodynamic properties. Peptides with low energy, low entropy and low-heat capacity are determined to be essential for a peptide to be a good candidate inhibitor. Free energy changes in peptide binding are also discussed.Publication Metadata only 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; Keskin, Özlem; Gürsoy, Attila; Özbabacan, Saliha Ece Acuner; Faculty Member; Faculty Member; PhD Student; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26605; 8745; 264351Apoptosis 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.Publication Metadata only Examining the stability of binding modes of the co-crystallized inhibitors of human HDAC8 by molecular dynamics simulation(Taylor & Francis Inc, 2020) Uba, Abdullahi İbrahim; Yelekçi, Kemal; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Weako, Jackson; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 26605; 8745Histone deacetylase (HDAC) 8 has been implicated as a potential therapeutic target in a variety of cancers, neurodegenerative disorders, metabolic dysregulation and autoimmune and inflammatory diseases. Several nonselective HDAC inhibitors have been co-crystallized with HDAC8. Molecular dynamics (MD) studies may yield valuable information on the structural stabilities of the complexes over time as determined by various pharmacophore features of the co-crystallized inhibitors. Here, using 11 unmodified X-ray crystal structures of human HDAC8 (complexes) structure-based pharmacophore models were built and clustered based on distance - a function of the number of common pharmacophore features and the root-mean-squared displacement between the matching features. Based on this information, a total of seven complexes (1T64, 1W22, 3RQD, 3SFF, 3F0R, 5VI6 and 5FCW) were submitted to unrestrained 50 ns-MD simulations using nanoscale MD (NAMD) software. 1T64 (HDAC8 in complex with TSA) was found to show the highest stability over time, presumably because of the TSA's ability to span HDAC8 catalytic channel and form a strong ionic interaction with zinc metal ion. Other stable complexes were 1W22, 3SFF, 3F0R and 5FCW. However, 3RQD and 5VI6 showed relative instability over 50 ns time period. This may be attributed to bulkiness of the capping groups of both largazole thiol and trapoxin A, making them unable to fit well into the active site of HDAC8. They rather formed steric clashes with residues on loop regions near the entrance to the channel. Thus, 1T64 and similar crystal structures may be good candidates for HDAC8 structural dynamics studies and inhibitor design.Publication Metadata only Fast and accurate modeling of protein-protein interactions by combining template-interface-based docking with flexible refinement(Wiley, 2012) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Tunçbağ, Nurcan; Gürsoy, Attila; Faculty Member; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; College of Engineering; 26605; 245513; 8745The similarity between folding and binding led us to posit the concept that the number of proteinprotein interface motifs in nature is limited, and interacting protein pairs can use similar interface architectures repeatedly, even if their global folds completely vary. Thus, known proteinprotein interface architectures can be used to model the complexes between two target proteins on the proteome scale, even if their global structures differ. This powerful concept is combined with a flexible refinement and global energy assessment tool. The accuracy of the method is highly dependent on the structural diversity of the interface architectures in the template dataset. Here, we validate this knowledge-based combinatorial method on the Docking Benchmark and show that it efficiently finds high-quality models for benchmark complexes and their binding regions even in the absence of template interfaces having sequence similarity to the targets. Compared to classical docking, it is computationally faster; as the number of target proteins increases, the difference becomes more dramatic. Further, it is able to distinguish binders from nonbinders. These features allow performing large-scale network modeling. The results on an independent target set (proteins in the p53 molecular interaction map) show that current method can be used to predict whether a given protein pair interacts. Overall, while constrained by the diversity of the template set, this approach efficiently produces high-quality models of proteinprotein complexes. We expect that with the growing number of known interface architectures, this type of knowledge-based methods will be increasingly used by the broad proteomics community.Publication Metadata only Functionally important residues from mode coupling during short-time protein dynamics(Cell Press, 2015) Varol, Onur; Department of Computer Engineering; Department of Chemical and Biological Engineering; Department of Physics; 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; College of Engineering; College of Engineering; College of Sciences; 179996; 179997; 49854