Researcher:
Keskin, Özlem

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Özlem

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Keskin

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Keskin, Özlem
Özkaya, Zehra Özlem Keskin

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Researcher Of Publications: search.filters.isAuthorOfPublication.81e93983-e095-49c6-b5fb-5ce23d54c577

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Now showing 1 - 10 of 153
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    A new dataset of non-redundant protein/protein interfaces
    (Biophysical Society, 2003) Tsai, CJ; Wolfson, H; Nussinov, R; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 26605
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    How similar are protein folding and protein binding nuclei? Examination of vibrational motions of energy hot spots and conserved residues
    (Cell Press, 2005) Haliloğlu, Türkan; Ma, Buyong; Nussinov, Ruth; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 26605
    The underlying physico-chemical principles of the interactions between domains in protein folding are similar to those between protein molecules in binding. Here we show that conserved residues and experimental hot spots at intermolecular binding interfaces overlap residues that vibrate with high frequencies. Similarly, conserved residues and hot spots are found in protein cores and are also observed to vibrate with high frequencies. In both cases, these residues contribute significantly to the stability. Hence, these observations validate the proposition that binding and folding are similar processes. In both packing plays a critical role, rationalizing the residue conservation and the experimental alanine scanning hot spots. We further show that high-frequency vibrating residues distinguish between protein binding sites and the remainder of the protein surface.
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    Determination of the correspondence between mobility (rigidity) and conservation of the interface residues
    (IEEE, 2010) N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Keskin, Özlem; Gürsoy, Attila; Makinacı, Gözde Kar; Faculty Member; Faculty Member; PhD Student; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26605; 8745; N/A
    Hot spots at protein interfaces may play specific functional roles and contribute to the stability of the protein complex. These residues are not homogeneously distributed along the protein interfaces; rather they are clustered within locally tightly packed regions forming a network of interactions among themselves. Here, we investigate the organization of computational hot spots at protein interfaces. A list of proteins whose free and bound forms exist is examined. Inter-residue distances of the interface residues are compared for both forms. Results reveal that there exist rigid block regions at protein interfaces. More interestingly, these regions correspond to computational hot regions. Hot spots can be determined with an average positive predictive value (PPV) of 0.73 and average sensitivity value of 0.70 for seven protein complexes.
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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; 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; 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; Çukuroğlu, Engin; 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; 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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    Modeling structural protein interaction networks for betweenness analysis
    (Springer-Verlag Berlin, 2014) N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Demircioğlu, Deniz; Keskin, Özlem; Gürsoy, Attila; Researcher; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; College of Engineering; College of Engineering; N/A; 26605; 8745
    Protein-protein interactions are usually represented as interaction networks (graphs), where the proteins are represented as nodes and the connections between the interacting proteins are shown as edges. Proteins or interactions with high betweenness are considered as key connector members of the network. The interactions of a protein are dictated by its structure. In this study, we propose a new protein interaction network model taking structures of proteins into consideration. With this model, it is possible to reveal simultaneous and mutually exclusive interactions of a protein. Effect of mutually exclusive interactions on information flow in a network is studied with weighted edge betweenness analysis and it is observed that a total of 68% of bottlenecks found in p53 pathway network differed from bottlenecks found via regular edge betweenness analysis. The new network model favored the proteins which have regulatory roles and take part in cell cycle and molecular functions like protein binding, transcription factor binding, and kinase activity.
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    Genome-wide RNA and DNA high throughput sequencing reveals proinflammatory and death gene signatures in head and neck squamous cell carcinoma lines with different HPV status
    (American Association for Cancer Research (AACR), 2014) Yang, Xinping; Cheng, Hui; Si, Han; Saleh, Anthony; Coupar, Jamie; Ferris, Robert L.; Yarbrough, Wendell G.; Prince, Mark E.; Carey, Thomas E.; Van Waes, Carter; Chen, Zhong; N/A; N/A; Department of Computer Engineering; N/A; Maiorov, Emine Güven; Keskin, Özlem; Gürsoy, Attila; PhD Student; Faculty Member; Faculty Member; N/A; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 26605; 8745; N/A
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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; Şanlı, Deniz; Keskin, Özlem; Gürsoy, Attila; Erman, Burak; Researcher; Faculty Member; 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; 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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    Identification of specificity and promiscuity of PDZ domain interactions through their dynamic behavior
    (Wiley, 2009) Gerek, Z. Nevin; Ozkan, S. Banu; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 26605
    PDZ domains (PDZs), the most common interaction domain proteins, play critical roles in many cellular processes. PDZs perform their job by binding specific protein partners. However, they are very promiscuous, binding to more than one protein, yet selective at the same time. We examined the binding related dynamics of various PDZs to have insight about their specificity and promiscuity. We used full atomic normal mode analysis and a modified coarse-grained elastic network model to compute the binding related dynamics. In the latter model, we introduced specificity for each single parameter constant and included the solvation effect implicitly. The modified model, referred to as specific-Gaussian Network Model (s-GNM), highlights some interesting differences in the conformational changes of PDZs upon binding to Class I or Class 11 type peptides. By clustering the residue fluctuation profiles of PDZs, we have shown: (i) binding selectivities can be discriminated from their dynamics, and (ii) the dynamics of different structural regions play critical roles for Class I and Class II specificity. s-GNM is further tested on a dual-specific PDZ which showed only Class I specificity when a point mutation exists on the beta A-beta B loop. We observe that the binding dynamics change consistently in the mutated and wild type structures. in addition, we found that the binding induced fluctuation profiles can be used to discriminate the binding selectivity of homolog structures. These results indicate that s-GNM can be a powerful method to study the changes in binding selectivities for mutant or homolog PDZs.
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    Prediction of protein interactions by structural matching: Prediction of PPI networks and the effects of mutations on PPIs that combines sequence and structural information
    (Humana Press Inc, 2017) Tunçbağ, Nurcan; Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; 26605; 8745
    Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein-protein interaction (PPI) prediction tool-its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.