Research Outputs
Permanent URI for this communityhttps://hdl.handle.net/20.500.14288/2
Browse
115 results
Search Results
Publication Open Access 3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients(Public Library of Science, 2019) Dinçer, Cansu; Kaya, Tuğba; Tunçbağ, Nurcan; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; 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); College of Engineering; 26605; 8745Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in "patches" which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways, revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between each group and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine.
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 A mobile application for symptom management in patients with breast cancer(Oncology Nursing Society, 2022) Seven M.; N/A; N/A; Department of Computer Engineering; N/A; Paşalak, Şeyma İnciser; Bağçivan, Gülcan; Özkasap, Öznur; Selçukbiricik, Fatih; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Health Sciences; School of Nursing; College of Engineering; School of Medicine; 125009; 261422; 113507; 202015OBJECTIVES: To evaluate the effect of a symptom management mobile application on quality of life and symptom severity in women with breast cancer undergoing chemotherapy. SAMPLE & SETTING: This parallel randomized pilot study consisted of women with breast cancer admitted to oncology outpatient clinics between November 2019 and January 2021 in Turkey. METHODS & VARIABLES: Participants (N = 40) were randomly assigned to the intervention (n = 20) or control group (n = 20). The intervention group used the mobile application in conjunction with usual care. The control group received usual care. Participants were assessed during the first, third, and last chemotherapy cycles. Data were collected using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire–Core 30 and the Edmonton Symptom Assessment System. RESULTS: During the study, the decrease in general health and physical functioning and the increase in the severity of depression/sadness in the intervention group were statistically lower than in the control group. IMPLICATIONS FOR NURSING: The use of a mobile application for symptom management may promote general well-being and physical function and may alleviate symptoms of depression/sadness in women with breast cancer undergoing chemotherapy. Further studies are needed to evaluate the application in clinical settings with larger groups.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 A survey of available tools and web servers for analysis of protein-protein interactions and interfaces(Oxford University Press (OUP), 2009) Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Keskin, Özlem; Gürsoy, Attila; Makinacı, Gözde Kar; Tunçbağ, Nurcan; Faculty Member; Faculty Member; PhD Student; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 26605; 8745; N/A; 245513The unanimous agreement that cellular processes are (largely) governed by interactions between proteins has led to enormous community efforts culminating in overwhelming information relating to these proteins; to the regulation of their interactions, to the way in which they interact and to the function which is determined by these interactions. These data have been organized in databases and servers. However, to make these really useful, it is essential not only to be aware of these, but in particular to have a working knowledge of which tools to use for a given problem; what are the tool advantages and drawbacks; and no less important how to combine these for a particular goal since usually it is not one tool, but some combination of tool-modules that is needed. This is the goal of this review.Publication Metadata only Advances in template-based protein docking by utilizing interfaces towards completing structural interactome(Current Biology Ltd, 2015) N/A; N/A; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Muratçıoğlu, Serena; Maiorov, Emine Güven; Keskin, Özlem; Gürsoy, Attila; PhD Student; PhD Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer 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; 26605; 8745The increase in the number of structurally determined protein complexes strengthens template-based docking (TBD) methods for modelling protein-protein interactions (PPIs). These methods utilize the known structures of protein complexes as templates to predict the quaternary structure of the target proteins. The templates may be partial or complete structures. Interface based (partial) methods have recently gained interest due in part to the observation that the interface regions are reusable. We describe how available template interfaces can be used to obtain the structural models of protein interactions. Despite the agreement that a majority of the protein complexes can be modelled using the available Protein Data Bank (PDB) structures, a handful of studies argue that we need more template proteins to increase the structural coverage of PPIs. We also discuss the performance of the interface TBD methods at large scale, and the significance of capturing multiple conformations for improving accuracy.Publication Metadata only Allostery and population shift in drug discovery(Elsevier, 2010) Nussinov, Ruth; 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; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26605; 8745; N/AProteins can exist in a large number of conformations around their native states that can be characterized by an energy landscape. The landscape illustrates individual valleys, which are the conformational substates. From the functional standpoint, there are two key points: first, all functionally relevant substates pre-exist; and second, the landscape is dynamic and the relative populations of the substates will change following allosteric events. Allosteric events perturb the structure, and the energetic strain propagates and shifts the population. This can lead to changes in the shapes and properties of target binding sites. Here we present an overview of dynamic conformational ensembles focusing on allosteric events in signaling. We propose that combining equilibrium fluctuation concepts with genomic screens could help drug discovery.Publication Metadata only Alterations in vaginal microbiota among pregnant women with COVID-19(Wiley, 2023) N/A; N/A; N/A; N/A; N/A; N/A; N/A; N/A; Department of Computer Engineering; Department of Chemical and Biological Engineering; N/A; Çelik, Ebru; Özcan, Gülin; Vatansever, Cansel; Paerhati, Erxiati; Kuşkucu, Mert Ahmet; Doğan, Özlem; Çekiç, Sebile Güler; Ergönül, Önder; Gürsoy, Attila; Keskin, Özlem; Can, Füsun; Faculty Member; PhD Student; PhD Student; PhD Student; Faculty Member; Faculty Member; Doctor; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; School of Medicine; Graduate School of Health Sciences; Graduate School of Health Sciences; Graduate School of Sciences and Engineering; School of Medicine; School of Medicine; N/A; School of Medicine; College of Engineering; College of Engineering; School of Medicine; N/A; N/A; N/A; N/A; N/A; N/A; Koç University Hospital; N/A; N/A; N/A; N/A; 116631; N/A; N/A; N/A; N/A; 170418; N/A; 110398; 8745; 26605; 103165The maintenance of vaginal microbiota is an important factor to achieve optimum pregnancy outcomes. The study aims to describe the alterations in the composition of vaginal microbiota in pregnant women with coronavirus disease 2019 (COVID-19). This was a prospective case-control study. Vaginal swabs were collected from uninfected pregnant women (n = 28) and pregnant women with COVID-19 (n = 19) during the active phase of infection and within a month after recovering from infection. The vaginal microbiota on the swabs was examined by 16S rRNA gene sequencing. Shannon index indicates that alpha diversity is significantly higher in women with COVID-19 (p = 0.012). There was a significant decrease in Firmicutes (p = 0.014) with an increase in Bacteroidota (p = 0.018) phyla and a decrease in Lactobacillus (p = 0.007) genus in women with COVID-19 than those of uninfected pregnant women. The relative abundance of L. crispatus, L. iners, L. gasseri, and L. jensenii were lower in the COVID-19 group than in uninfected pregnant women. In subgroup analysis, the amount of Ureaplasma spp. was higher in women with moderate/severe than those of asymptomatic/mild disease (p = 0.036). The study revealed that vaginal dysbiosis with low abundance of Lactobacillus species occurred in pregnant women infected with severe acute respiratory syndrome coronavirus-2. These findings may lead to new studies to elucidate the risk of pregnancy adverse outcomes related to COVID-19.Publication Metadata only An evaluation of DNA methylation levels and sleep in relation to hot flashes: a cross-sectional study(MDPI, 2024) Ozcivit Erkan, Ipek Betul; Seyisoglu, Hasan Hakan; Senel, Gulcin Benbir; Karadeniz, Derya; Ozdemir, Filiz; Kalayci, Aysel; Seven, Mehmet; Department of Computer Engineering; İnan, Neslihan Gökmen; Department of Computer Engineering; College of EngineeringObjectives: We aimed to evaluate the DNA methylation levels in perimenopausal and postmenopausal women, measured through Long Interspersed Element-1 (LINE-1) and Alu, and the sleep parameters in relation to the presence of hot flashes (HFs). Methods: This cross-sectional study included 30 peri- or postmenopausal women aged between 45 and 55. The menopausal status was determined according to STRAW + 10 criteria and all participants had a low cardiovascular disease (CVD) risk profile determined by Framingham risk score. The sample was divided into two groups based on the presence or absence of HFs documented in their medical history during their initial visit: Group 1 (n = 15) with HFs present and Group 2 (n = 15) with HFs absent. The patients had polysomnography test and HFs were recorded both by sternal skin conductance and self-report overnight. Genomic DNA was extracted from the women's blood and methylation status was analyzed by fluorescence-based real-time quantitative PCR. The quantified value of DNA methylation of a target gene was normalized by beta-actin. The primary outcome was the variation in methylation levels of LINE-1 and Alu and sleep parameters according to the presence of HFs. Results: LINE-1 and Alu methylation levels were higher in Group 1 (HFs present), although statistically non-significant. LINE-1 methylation levels were negatively correlated with age. Sleep efficiency was statistically significantly lower for women in Group 1 (HFs present) (74.66% +/- 11.16% vs. 82.63% +/- 7.31%;p = 0.03). The ratio of duration of awakening to total sleep time was statistically significantly higher in Group 1 (HFs present) (22.38% +/- 9.99% vs. 15.07% +/- 6.93, p = 0.03). Objectively recorded hot flashes were significantly higher in Group 1 (4.00 +/- 3.21 vs. 1.47 +/- 1.46, p = 0.03). None of the cases in Group 2 self-reported HF despite objectively recorded HFs during the polysomnography. The rate of hot flash associated with awakening was 41.4% in the whole sample. Conclusions: Women with a history of hot flashes exhibited lower sleep efficiency and higher awakening rates. Although a history of experiencing hot flashes was associated with higher LINE-1 and Alu methylation levels, no statistical significance was found. Further studies are needed to clarify this association. This study was funded by the Scientific Research Projects Coordination Unit of Istanbul University-Cerrahpasa. Project number: TTU-2021-35629.Publication 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.