Publications without Fulltext
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
Browse
12 results
Search Results
Publication Metadata only A diversity combination model incorporating an inward bias for interaural time-level difference cue integration in sound lateralization(MDPI, 2020) N/A; N/A; Department of Computer Engineering; N/A; Mojtahedi, Sina; Erzin, Engin; Ungan, Pekcan; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 34503; N/AA sound source with non-zero azimuth leads to interaural time level differences (ITD and ILD). Studies on hearing system imply that these cues are encoded in different parts of the brain, but combined to produce a single lateralization percept as evidenced by experiments indicating trading between them. According to the duplex theory of sound lateralization, ITD and ILD play a more significant role in low-frequency and high-frequency stimulations, respectively. In this study, ITD and ILD, which were extracted from a generic head-related transfer functions, were imposed on a complex sound consisting of two low- and seven high-frequency tones. Two-alternative forced-choice behavioral tests were employed to assess the accuracy in identifying a change in lateralization. Based on a diversity combination model and using the error rate data obtained from the tests, the weights of the ITD and ILD cues in their integration were determined by incorporating a bias observed for inward shifts. The weights of the two cues were found to change with the azimuth of the sound source. While the ILD appears to be the optimal cue for the azimuths near the midline, the ITD and ILD weights turn to be balanced for the azimuths far from the midline.Publication Metadata only Predicting protein-protein interactions from the molecular to the proteome level(Amer Chemical Soc, 2016) Tunçbağ, Nurcan; 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; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; 26605; 8745Identification of protein protein interactions (PPIs) is at the center of molecular biology considering the unquestionable role of proteins in cells. Combinatorial interactions result in a repertoire of multiple functions; hence, knowledge of PPI and binding regions naturally serve to functional proteomics and drug discovery. Given experimental limitations to find all interactions in a proteome, computational prediction/modeling of protein interactions is a prerequisite to proceed on the way to complete interactions at the proteome level. This review aims to provide a background on PPIs and their types. Computational methods for PPI predictions can use a variety of biological data including sequence-, evolution-, expression-, and structure-based data. Physical and statistical modeling are commonly used to integrate these data and infer PPI predictions. We review and list the state-of-the-art methods, servers, databases, and tools for protein-protein interaction prediction.Publication Metadata only A strategy based on protein-protein interface motifs may help in identifying drug off-targets(American Chemical Society (ACS), 2012) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Ergin, Billur Çelebi; Faculty Member; Faculty Member; Teaching Faculty; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; 26605; 8745; 261792Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can "attack" nodes or edges of a protein-protein interaction network In this work, we propose a new network strategy, "The Interface Attack", based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding to others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model that we call "Protein Interface and Interaction Network (P2IN)", which is the integration of protein-protein interface structures and protein interaction networks. This interface based, network organization clarifies which protein pairs have structurally similar interfaces and which proteins may compete to bind the same surface region. We built the P2IN with the p53 signaling network and performed network robustness analysis. We show that (1) "hitting" frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes), (2) frequent interfaces are not always topologically critical elements in the network, and (3) interface attack may reveal functional changes in the system better than the attack of single proteins. In the off target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D.Publication Metadata only 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; 40548Proper 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.Publication Metadata only A genome-wide functional screen identifies enhancer and protective genes for amyloid beta-peptide toxicity(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Picon-Pages, Pol; Bosch-Morato, Monica; Subirana, Laia; Rubio-Moscardo, Francisca; Guivernau, Biuse; Fanlo-Ucar, Hugo; Herrera-Fernandez, Victor; Vicente, Ruben; Fernandez-Fernandez, Jose M.; Garcia-Ojalvo, Jordi; Oliva, Baldomero; Posas, Francesc; de Nadal, Eulalia; Munoz, Francisco J.; N/A; N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Zeylan, Melisa Ece; Şenyüz, Simge; Gürsoy, Attila; Keskin, Özlem; PhD Student; Master Student; Faculty Member; Faculty Member; 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; 8745; 26605Alzheimer's disease (AD) is known to be caused by amyloid beta-peptide (A beta) misfolded into beta-sheets, but this knowledge has not yet led to treatments to prevent AD. To identify novel molecular players in A beta toxicity, we carried out a genome-wide screen in Saccharomyces cerevisiae, using a library of 5154 gene knock-out strains expressing A beta(1-42). We identified 81 mammalian orthologue genes that enhance A beta(1-42) toxicity, while 157 were protective. Next, we performed interactome and text-mining studies to increase the number of genes and to identify the main cellular functions affected by A beta oligomers (oA beta). We found that the most affected cellular functions were calcium regulation, protein translation and mitochondrial activity. We focused on SURF4, a protein that regulates the store-operated calcium channel (SOCE). An in vitro analysis using human neuroblastoma cells showed that SURF4 silencing induced higher intracellular calcium levels, while its overexpression decreased calcium entry. Furthermore, SURF4 silencing produced a significant reduction in cell death when cells were challenged with oA beta(1-42), whereas SURF4 overexpression induced A beta(1-42) cytotoxicity. In summary, we identified new enhancer and protective activities for A beta toxicity and showed that SURF4 contributes to oA beta(1-42) neurotoxicity by decreasing SOCE activity.Publication Metadata only PDEδ binding to ras isoforms provides a route to proper membrane localization(Amer Chemical Soc, 2017) Jang, Hyunbum; Nussinov, Ruth; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Muratçıoğlu, Serena; 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; 8745To signal, Ras isoforms must be enriched at the plasma membrane (PM). It was suggested that phosphodies-terase-delta (PDE delta) can bind and shuttle some farnesylated Ras isoforms to the PM, but not all. Among these, interest focused on K-Ras4B, the most abundant oncogenic Ras isoform. To study PDE delta/Ras interactions, we modeled and simulated the PDE delta/K-Ras4B complex. We obtained structures, which were similar to two subsequently determined crystal structures. We next modeled and simulated complexes of PDE delta with the farnesylated hypervariable regions K-Ras4A and N-Ras. Earlier data suggested that PDE delta extracts K-Ras4B and N-Ras from the PM, but surprisingly not K-kas4A. Earlier analysis of the crystal structures advanced that the presence of large/charged residues adjacent to the farnesylated site precludes the PDE delta interaction. Here, we show that PDE delta can bind to farnesylated K-Ras4A and N-Ras like K-Ras4B, albeit not as strongly. This weaker binding, coupled with the stronger anchoring of K-Ras4A in the membrane (but not of electrostatically neutral N-Ras), can explain the observation why PDE delta is unable to effectively extract K-Ras4A. We thus propose that farnesylated Ras isoforms can bind PDE delta to fulfill the required PM enrichment, and argue that the different environments, PM versus solution, can resolve apparently puzzling Ras observations. These are novel insights that would not be expected based on the crystal structures alone, which provide an elegant rationale for previously puzzling observations of the differential effects of PDE delta on farnesylated Ras family proteins.Publication Metadata only Ras conformational ensembles, allostery, and signaling(American Chemical Society (ACS), 2016) Lu, Shaoyong; Jang, Hyunbum; Nussinov, Ruth; Zhang, Jian; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Keskin, Özlem; Gürsoy, Attila; Muratçıoğlu, Serena; 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; 8745Ras proteins are classical members of small GTPases that function as molecular switches by alternating between inactive GDP-bound and active GTP-bound states. Ras activation is regulated by guanine nucleotide exchange factors that catalyze the exchange of GDP by GTP, and inactivation is terminated by GTPase-activating proteins that accelerate the intrinsic GTP hydrolysis rate by orders of magnitude. In this review, we focus on data that have accumulated over the past few years pertaining to the conformational ensembles and the allosteric regulation of Ras proteins and their interpretation from our conformational landscape standpoint. The Ras ensemble embodies all states, including the ligand-bound conformations, the activated (or inactivated) allosteric modulated states, post-translationally modified states, mutational states, transition states, and nonfunctional states serving as a reservoir for emerging functions. The ensemble is shifted by distinct mutational events, cofactors, post-translational modifications, and different membrane compositions. A better understanding of Ras biology can contribute to therapeutic strategies.Publication Metadata only Relation between kinetic conversion rates and anm mode frequencies(IEEE, 2010) N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Keskin, Özlem; Gürsoy, Attila; Özgür, Beytullah; 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/AElastic Network Models (ENMs) are informative, fast and largely used techniques for the elucidation of the intrinsic motions of the proteins. ENM normal modes resemble the conformational changes in the ligand-free states of the proteins. According to pre-existing equilibrium model the native state of the protein forms an ensemble of substates and ligand simply selects and shifts the population dynamics of the ensemble. In this study, we investigated the relation between normal mode frequencies and kinetic conversion rates of ensemble substates between each other.Publication Metadata only Towards drugs targeting multiple proteins in a systems biology approach(Bentham Science, 2007) Ma, B.; Nussinov, R.; 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; 8745Protein-protein interactions are increasingly becoming drug targets. This is understandable, since they are crucial at all levels of cellular expression and growth. In practice, targeting specific disease-related interactions has proven difficult, with success varying with specific complexes. Here, we take a Systems Biology approach to targeting protein-protein interactions. Below, we first briefly review drug discovery targeted at protein-protein interactions; we classify protein-protein complexes with respect to their types of interactions and their roles in cellular function and as being targets in drug design; we describe the properties of the interfaces as related to drug design, focusing on hot spots and surface cavities; and finally, in particular, we cast the interactions into the cellular network system, highlighting the challenge of partially targeting multiple interactions in the networks as compared to hitting a specific protein-protein interaction target. The challenge we now face is how to pick the targets and how to improve the efficiency of designed partially-specific multi-target drugs that would block parallel pathways in the network.Publication Metadata only 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; 26605Intrinsic 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.