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Department: search.filters.department.Department of Chemical and Biological EngineeringSubject: search.filters.subject.Cell biology

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Now showing 1 - 10 of 24
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    Artificial intelligence based methods for hot spot prediction
    (Current Biology Ltd, 2022) N/A; N/A; N/A; N/A; Department of Chemical and Biological Engineering; Department of Computer Engineering; Department of Chemical and Biological Engineering; Övek, Damla; Abalı, Zeynep; Zeylan, Melisa Ece; Keskin, Özlem; Gürsoy, Attila; Tunçbağ, Nurcan; PhD Student; PhD Student; PhD Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; N/A; N/A; 26605; 8745; 245513
    Proteins interact through their interfaces to fulfill essential functions in the cell. They bind to their partners in a highly specific manner and form complexes that have a profound effect on understanding the biological pathways they are involved in. Any abnormal interactions may cause diseases. Therefore, the identification of small molecules which modulate protein interactions through their interfaces has high thera-peutic potential. However, discovering such molecules is challenging. Most protein-protein binding affinity is attributed to a small set of amino acids found in protein interfaces known as hot spots. Recent studies demonstrate that drug-like small molecules specifically may bind to hot spots. Therefore, hot spot prediction is crucial. As experimental data accumulates, artificial intelligence begins to be used for computational hot spot prediction. First, we review machine learning and deep learning for computational hot spot prediction and then explain the significance of hot spots toward drug design.
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    PublicationOpen Access
    Centriolar satellites are required for efficient ciliogenesis and ciliary content regulation
    (Wiley, 2019) Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Odabaşı, Ezgi; Karalar, Elif Nur Fırat; Gül, Şeref; Kavaklı, İbrahim Halil; Other; Researcher; Faculty Member; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; N/A; 206349; N/A; 40319
    Centriolar satellites are ubiquitous in vertebrate cells. They have recently emerged as key regulators of centrosome/cilium biogenesis, and their mutations are linked to ciliopathies. However, their precise functions and mechanisms of action remain poorly understood. Here, we generated a kidney epithelial cell line (IMCD3) lacking satellites by CRISPR/Cas9-mediated PCM1 deletion and investigated the cellular and molecular consequences of satellite loss. Cells lacking satellites still formed full-length cilia but at significantly lower numbers, with changes in the centrosomal and cellular levels of key ciliogenesis factors. Using these cells, we identified new ciliary functions of satellites such as regulation of ciliary content, Hedgehog signaling, and epithelial cell organization in three-dimensional cultures. However, other functions of satellites, namely proliferation, cell cycle progression, and centriole duplication, were unaffected in these cells. Quantitative transcriptomic and proteomic profiling revealed that loss of satellites affects transcription scarcely, but significantly alters the proteome. Importantly, the centrosome proteome mostly remains unaltered in the cells lacking satellites. Together, our findings identify centriolar satellites as regulators of efficient cilium assembly and function and provide insight into disease mechanisms of ciliopathies.
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    PublicationOpen Access
    Clock regulation of metabolites reveals coupling between transcription and metabolism
    (Elsevier, 2017) Sancar, Aziz; Krishnaiah, Saikumari Y.; Wu, Gang; Altman, Brian J.; Growe, Jacqueline; Rhoades, Seth D.; Coldren, Faith; Venkataraman, Anand; Olarerin-George, Anthony O.; Francey, Lauren J.; Mukherjee, Sarmistha; Girish, Saiveda; Selby, Christopher P.; Ubeydullah, E.R.; Sianati, Bahareh; Sengupta, Arjun; Anafi, Ron C.; Baur, Joseph A.; Dang, Chi V.; Hogenesch, John B.; Weljie, Aalim M.; Department of Chemical and Biological Engineering; Kavaklı, İbrahim Halil; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 40319; N/A
    The intricate connection between the circadian clock and metabolism remains poorly understood. We used high temporal resolution metabolite profiling to explore clock regulation of mouse liver and cell-autonomous metabolism. In liver, similar to 50% of metabolites were circadian, with enrichment of nucleotide, amino acid, and methylation pathways. In U2 OS cells, 28% were circadian, including amino acids and NAD biosynthesis metabolites. Eighteen metabolites oscillated in both systems and a subset of these in primary hepatocytes. These 18 metabolites were enriched in methylation and amino acid pathways. To assess clock dependence of these rhythms, we used genetic perturbation. BMAL1 knockdown diminished metabolite rhythms, while CRY1 or CRY2 perturbation generally shortened or lengthened rhythms, respectively. Surprisingly, CRY1 knockdown induced 8 hr rhythms in amino acid, methylation, and vitamin metabolites, decoupling metabolite from transcriptional rhythms, with potential impact on nutrient sensing in vivo. These results provide the first comprehensive views of circadian liver and cell-autonomous metabolism.
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    Constructing structural networks of signaling pathways on the proteome scale
    (Current Biology Ltd, 2012) Nussinov, Ruth; Department of Chemical and Biological Engineering; N/A; Department of Computer Engineering; Keskin, Özlem; Kuzu, Güray; Gürsoy, Attila; Faculty Member; PhD Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 26605; N/A; 8745
    Proteins function through their interactions, and the availability of protein interaction networks could help in understanding cellular processes. However, the known structural data are limited and the classical network node-and-edge representation, where proteins are nodes and interactions are edges, shows only which proteins interact; not how they interact. Structural networks provide this information. Protein-protein interface structures can also indicate which binding partners can interact simultaneously and which are competitive, and can help forecasting potentially harmful drug side effects. Here, we use a powerful protein-protein interactions prediction tool which is able to carry out accurate predictions on the proteome scale to construct the structural network of the extracellular signal-regulated kinases (ERK) in the mitogen-activated protein kinase (MAPK) signaling pathway. This knowledge-based method, PRISM, is motif-based, and is combined with flexible refinement and energy scoring. PRISM predicts protein interactions based on structural and evolutionary similarity to known protein interfaces.
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    PublicationOpen Access
    Cyclophilin40 isomerase activity is regulated by a temperature-dependent allosteric interaction with Hsp90
    (Portland Press, 2015) Blackburn, Elizabeth A.; Wear, Martin A.; Landre, Vivian; Narayan, Vikram; Ning, Jia; Ball, Kathryn L.; Walkinshaw, Malcolm D.; Department of Chemical and Biological Engineering; Erman, Burak; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 179997
    Cyclophilin 40 (Cyp40) comprises an N-terminal cyclophilin domain with peptidyl-prolyl isomerase (PPIase) activity and a C-terminal tetratricopeptide repeat (TPR) domain that binds to the C-terminal -EEVD sequence common to both heat shock protein 70 (Hsp70) and Hsp90. We show in the present study that binding of peptides containing the MEEVD motif reduces the PPIase activity by similar to 30%. CD and fluorescence assays show that the TPR domain is less stable than the cyclophilin domain and is stabilized by peptide binding. Isothermal titration calorimetry (ITC) shows that the affinity for the -MEEVD peptide is temperature sensitive in the physiological temperature range. Results from these biophysical studies fit with the MD simulations of the apo and holo (peptide-bound) structures which show a significant reduction in root mean square (RMS) fluctuation in both TPR and cyclophilin domains when -MEEVD is bound. The MD simulations of the apo-protein also highlight strong anti-correlated motions between residues around the PPIase-active site and a band of residues running across four of the seven helices in the TPR domain. Peptide binding leads to a distortion in the shape of the active site and a significant reduction in these strongly anti-correlated motions, providing an explanation for the allosteric effect of ligand binding and loss of PPIase activity. Together the experimental and MD results suggest that on heat shock, dissociation of Cyp40 from complexes mediated by the TPR domain leads to an increased pool of free Cyp40 capable of acting as an isomerase/chaperone in conditions of cellular stress.
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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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    Editorial overview: artificial intelligence (AI) methodologies in structural biology
    (Current Biology Ltd, 2022) Cheng, Feixiong; Department of Chemical and Biological Engineering; Tunçbağ, Nurcan; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 245513
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    Editorial overview: protein–protein interactions
    (Current Biology Ltd, 2015) Bonvin, Alexandre M. J. J.; Department of Chemical and Biological Engineering; Keskin, Özlem; Faculty Member; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; 26605
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    Encapsulation of pancreatic islets within nano-thin functional polyethylene glycol coatings for enhanced insulin secretion
    (Mary Ann Liebert, Inc, 2010) Scavone, Andrew; Liu, Xiang; Nothias, Jean-Manuel; Ostrega, Diane; WitkoWSKi, Piotr; Millis, Michael; Department of Chemical and Biological Engineering; Kızılel, Seda; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 28376
    Covalent attachment of polymers to cells and tissues could be used to solve a variety of problems associated with cellular therapies. Insulin-dependent diabetes mellitus is a disease resulting from the autoimmune destruction of the beta cells of the islets of Langerhans in the pancreas. Transplantation of islets into diabetic patients is an attractive form of treatment, provided that the islets could be protected from the host's immune system to prevent graft rejection, and smaller numbers of islets transplanted in smaller volumes could be sufficient to reverse diabetes. Therefore, a need exists to develop islet encapsulation strategies that minimize transplant volume. In this study, we demonstrate the formation of nano-thin, poly(ethylene glycol) (PEG)-rich functional conformal coatings on individual islets via layer-by-layer assembly technique. The surface of the islets is modified with biotin-PEG-N-hydroxysuccinimide (NHS), and the islets are further covered by streptavidin (SA) and biotin-PEG-peptide conjugates using the layer-by-layer method. An insulinotropic ligand, glucagon-like peptide-1 (GLP-1), is conjugated to biotin-PEG-NHS. The insulinotropic effect of GLP-1 is investigated through layer-by-layer encapsulation of islets using the biotin-PEG-GLP-1 conjugate. The effect of islet surface modification using the biotin-PEG-GLP-1 conjugate on insulin secretion in response to glucose challenge is compared via static incubation and dynamic perifusion assays. The results show that islets coated with the functional PEG conjugate are capable of secreting more insulin in response to high glucose levels compared to control islets. Finally, the presence of SA is confirmed by indirect fluorescent staining with SA-Cy3, and the presence of PEG-peptide on the surface of the islets after treatment with biotin-PEG-GLP-1 is confirmed by indirect fluorescent staining with biotin-PEG-fluorescein isothiocyanate (FITC) and separately with an anti-GLP-1 antibody. This work demonstrates the feasibility of treating pancreatic islets with reactive polymeric segments and provides the foundation for a novel means of potential immunoisolation. With this technique, it may be possible to encapsulate and/or modify islets before portal vein transplantation and reduce transplantation volume significantly, and promote islet viability and insulin secretion due to the presence of insulinotropic peptides on the islet surface. Layer-by-layer self-assembly of PEG-GLP-1 offers a unique approach to islet encapsulation to stimulate insulin secretion in response to high glucose levels.
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    Enhanced heterotetrameric assembly of potato ADP-Glucose pyrophosphorylase using reverse genetics
    (Oxford Univ Press, 2014) Cevahir, Gül; N/A; N/A; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Seferoğlu, Ayşe Bengisu; Koper, Kaan; Can, Fatma Betül; Kavaklı, İbrahim Halil; PhD Student; Master Student; Undergraduate Student; Faculty Member; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Sciences; College of Engineering; N/A; N/A; N/A; 40319
    ADP-glucose pyrophosphorylase (AGPase) is a key allosteric enzyme in plant starch biosynthesis. Plant AGPase is a heterotetrameric enzyme that consists of large (LS) and small subunits (SS), which are encoded by two different genes. Computational and experimental studies have revealed that the heterotetrameric assembly of AGPase is thermodynamically weak. Modeling studies followed by the mutagenesis of the LS of the potato AGPase identified a heterotetramer-deficient mutant, LSR88A. To enhance heterotetrameric assembly, LSR88A cDNA was subjected to error-prone PCR, and second-site revertants were identified according to their ability to restore glycogen accumulation, as assessed with iodine staining. Selected mutations were introduced into the wild-type (WT) LS and co-expressed with the WT SS in Escherichia coli glgC(-). The biochemical characterization of revertants revealed that (LSSSWT)-S-I90V, (LSSSWT)-S-Y378C and (LSSSWT)-S-D410G mutants displayed enhanced heterotetrameric assembly with the WT SS. Among these mutants, (LSSSWT)-S-Y378C AGPase displayed increased heat stability compared with the WT enzyme. Kinetic characterization of the mutants indicated that the (LSSSWT)-S-I90V and (LSSSWT)-S-Y378C AGPases have comparable allosteric and kinetic properties. However, the (LSSSWT)-S-D410G mutant exhibited altered allosteric properties of being less responsive and more sensitive to 3-phosphoglyceric acid activation and inorganic phosphate inhibition. This study not only enhances our understanding of the interaction between the SS and the LS of AGPase but also enables protein engineering to obtain enhanced assembled heat-stable variants of AGPase, which can be used for the improvement of plant yields.