Researcher:
Özdemir, E. Sıla

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PhD Student

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E. Sıla

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Özdemir

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Özdemir, E. Sıla

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2017 - 20207

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    Analysis of single amino acid variations in singlet hot spots of protein-protein interfaces
    (Oxford Univ Press, 2018) N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Özdemir, E. Sıla; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 8745; 26605
    Motivation: Single amino acid variations (SAVs) in protein-protein interaction (PPI) sites play critical roles in diseases. PPI sites (interfaces) have a small subset of residues called hot spots that contribute significantly to the binding energy, and they may form clusters called hot regions. Singlet hot spots are the single amino acid hot spots outside of the hot regions. The distribution of SAVs on the interface residues may be related to their disease association. Results: We performed statistical and structural analyses of SAVs with literature curated experimental thermodynamics data, and demonstrated that SAVs which destabilize PPIs are more likely to be found in singlet hot spots rather than hot regions and energetically less important interface residues. In contrast, non-hot spot residues are significantly enriched in neutral SAVs, which do not affect PPI stability. Surprisingly, we observed that singlet hot spots tend to be enriched in disease-causing SAVs, while benign SAVs significantly occur in non-hot spot residues. Our work demonstrates that SAVs in singlet hot spot residues have significant effect on protein stability and function.
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    Arl2-mediated allosteric release of farnesylated kras4b from shuttling factor pde delta
    (2018) Jang, Hyunbum; Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Özdemir, E. Sıla; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); N/A; College of Engineering; College of Engineering; N/A; 8745; 40548
    Proper localization of Ras proteins at the plasma membrane (PM) is crucial for their functions. To get to the PM, KRas4B and some other Ras family proteins bind to the PDE delta shuttling protein through their farnesylated hypervariable regions (HVRs). The docking of their famesyl (and to a lesser extent geranylgeranyl) in the hydrophobic pocket of PDE delta's stabilizes the interaction. At the PM, guanosine 5'-triphosphate (GTP)-bound Arf-like protein 2 (Arl2) assists in the release of Ras from the PDE delta. However, exactly how is still unclear. Using all-atom molecular dynamics simulations, we unraveled the detailed mechanism of Arl2-mediated release of KRas4B, the most abundant oncogenic Ras isoform, from PDE delta. We simulated ternary Arl2 PDE delta KRas4B HVR complexes and observed that Arl2 binding weakens the PDE delta farnesylated HVR interaction. Our detailed analysis showed that allosteric changes (involving beta 6 of PDE delta and additional PDE delta residues) compress the hydrophobic PDE delta pocket and push the HVR out. Mutating PDE delta residues that mediate allosteric changes in PDE delta terminates the release process. Mutant Ras proteins are enriched in human cancers, with currently no drugs in the clinics. This mechanistic account may inspire efforts to develop drugs suppressing oncogenic KRas4B release.
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    Developments in integrative modeling with dynamical interfaces
    (Current Biology Ltd, 2019) Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Özdemir, E. Sıla; Gürsoy, Attila; Keskin, Özlem; PhD Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); N/A; College of Engineering; College of Engineering; N/A; 8745; 40548
    Proteins are dynamic, and this holds especially for their surfaces. They display ensembles of conformations, which allows them to interact with diverse partners, often via the same patch of surface, and execute their distinct functions. Binding a specific partner can stimulate - or suppress - a distinct signaling pathway. This diversity poses a challenge: how to reliably model a specific protein-protein interaction (PPI)? This problem is compounded in protein assemblies, which are typically large, involving multiple protein-protein interfaces. Integrative modeling (IM), which combines diverse data, has emerged as the most promising strategy; however, modeling dynamical interfaces, often at the detailed level, which are at the heart of reliable predictions of assemblies, still poses a challenge. Here we review hurdles and advances in integrative modeling of dynamical interfaces; while some could have been predicted or expected, others transformed modeling in unanticipated ways. We further comment on what we believe could be possible future advances.
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    Methods for discovering and targeting druggable protein-protein interfaces and their application to repurposing
    (Humana Press Inc, 2019) Nussinov, Ruth; N/A; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Halakou, Farideh; Özdemir, E. Sıla; Keskin, Özlem; Gürsoy, Attila; PhD Student; PhD Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 26605; 8745
    Drug repurposing is a creative and resourceful approach to increase the number of therapies by exploiting available and approved drugs. However, identifying new protein targets for previously approved drugs is challenging. Although new strategies have been developed for drug repurposing, there is broad agreement that there is room for further improvements. In this chapter, we review protein-protein interaction (PPI) interface-targeting strategies for drug repurposing applications. We discuss certain features, such as hot spot residue and hot region prediction and their importance in drug repurposing, and illustrate common methods used in PPI networks to identify drug off-targets. We also collect available online resources for hot spot prediction, binding pocket identification, and interface clustering which are effective resources in polypharmacology. Finally, we provide case studies showing the significance of protein interfaces and hot spots in drug repurposing.
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    Oncogenic K-Ras4B dimerization enhances downstream mitogen-activated protein kinase signaling
    (Academic Press Ltd- Elsevier Science Ltd, 2020) Jang, Hyunbum; Tsai, Chung-Jung; Nussinov, Ruth; N/A; N/A; N/A; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; N/A; Department of Chemical and Biological Engineering; Muratçıoğlu, Serena; Aydın, Cihan; Odabaşı, Ezgi; Karalar, Elif Nur Fırat; Kavaklı, İbrahim Halil; Özdemir, E. Sıla; Keskin, Özlem; Gürsoy, Attila; PhD Student; Researcher; Other; Faculty Member; Faculty Member; PhD Student; Faculty Member; Faculty Member; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; N/A; N/A; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; Department of Computer Engineering; N/A; 214696; 26605; 8745; 206349; 40319; 26605; 8745
    Ras recruits and activates effectors that transmit receptor-initiated signals. Monomeric Ras can bind Raf; however, Raf's activation requires dimerization, which can be facilitated by Ras dimerization. Previously, we showed that active K-Ras4B dimerizes in silico and in vitro through two major interfaces: (i) beta-interface, mapped to Switch I and effector-binding regions, (ii) alpha-interface at the allosteric lobe. Here, we chose constitutively active K-Ras4B as our control and two double mutants (K101D and R102E; and R41E and K42D) in the alpha- and beta-interfaces. Two of the mutations are from The Cancer Genome Atlas (TCGA) and the Catalogue of Somatic Mutations In Cancer (COSMIC) data sets. R41 and R102 are found in several adenocarcinomas in Ras isoforms. We performed site-directed mutagenesis, cellular localization experiments, and molecular dynamics (MD) simulations to assess the impact of the mutations on K-Ras4B dimerization and function. alpha-interface K101D/R102E double mutations reduced dimerization but only slightly reduced downstream phosphorylated extracellular signal-regulated kinase (ERK) (pERK) levels. While beta-interface R41E/K42D double mutations did not interfere with dimerization, they almost completely blocked KRas4B-mediated ERK phosphorylation. Both double mutations increased downstream phosphorylated Akt (pAkt) levels in cells. Changes in pERK and pAkt levels altered ERK- and Akt-regulated gene expressions, such as EGR1, JUN, and BCL2L11. These results underscore the role of the alpha-interface in K-Ras4B homodimerization and the beta-surface in effector binding. MD simulations highlight that the membrane and hypervariable region (HVR) interact with both alpha- and beta-interfaces of K-Ras4B mutants, respectively, inhibiting homodimerization and probably effector binding. Mutations at both interfaces interfered with mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase signaling but in different forms and extents. We conclude that dimerization is not necessary but enhances downstream MAPK signaling.
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    Relation between protein intrinsic normal mode weights and pre-existing conformer populations
    (Amer Chemical Soc, 2017) N/A; N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; Özgür, Beytullah; Özdemir, E. Sıla; 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; N/A; N/A; 8745; 26605
    Intrinsic fluctuations of a protein enable it to sample a large repertoire of conformers including the open and closed forms. These distinct forms of the protein called conformational substates pre-exist together in equilibrium as an ensemble independent from its ligands. The role of ligand might be simply to alter the equilibrium toward the most appropriate form for binding. Normal mode analysis is proved to be useful in identifying the directions of conformational changes between substates. In this study, we demonstrate that the ratios of normalized weights of a few normal modes driving the protein between its substates can give insights about the ratios of kinetic conversion rates of the substates, although a direct relation between the eigenvalues and kinetic conversion rates or populations of each substate could not be observed. The correlation between the normalized mode weight ratios and the kinetic rate ratios is around 83% on a set of 11 non-enzyme proteins and around 59% on a set of 17 enzymes. The results are suggestive that mode motions carry intrinsic relations with thermodynamics and kinetics of the proteins.
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    PublicationOpen 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/A
    IQ 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.