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Publication Open Access Activation of the pleiotropic drug resistance pathway can promote mitochondrial DNA retention by fusion-defective mitochondria in saccharomyces cerevisiae(Genetics Society America (GSA), 2014) Department of Chemical and Biological Engineering; Dunn, Cory David; Mutlu, Nebibe; Garipler, Görkem; Akdoğan, Emel; Faculty Member; Department of Chemical and Biological Engineering; College of SciencesGenetic and microscopic approaches using Saccharomyces cerevisiae have identified many proteins that play a role in mitochondrial dynamics, but it is possible that other proteins and pathways that play a role in mitochondrial division and fusion remain to be discovered. Mutants lacking mitochondrial fusion are characterized by rapid loss of mitochondrial DNA. We took advantage of a petite-negative mutant that is unable to survive mitochondrial DNA loss to select for mutations that allow cells with fusion-deficient mitochondria to maintain the mitochondrial genome on fermentable medium. Nextgeneration sequencing revealed that all identified suppressor mutations not associated with known mitochondrial division components were localized to PDR1 or PDR3, which encode transcription factors promoting drug resistance. Further studies revealed that at least one, if not all, of these suppressor mutations dominantly increases resistance to known substrates of the pleiotropic drug resistance pathway. Interestingly, hyperactivation of this pathway did not significantly affect mitochondrial shape, suggesting that mitochondrial division was not greatly affected. Our results reveal an intriguing genetic connection between pleiotropic drug resistance and mitochondrial dynamics.
Publication Metadata only Aerogel-copper nanocomposites prepared using the adsorption of a polyfluorinated complex from supercritical CO2(Springer, 2012) Kostenko, Svetlana O.; Kurykin, Michael A.; Khrustalev, Victor N.; Khokhlov, Alexei R.; Zhang, Lichun; Aindow, Mark; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Bozbağ, Selmi Erim; Erkey, Can; Researcher; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; College of Engineering; N/A; 29633A supercritical deposition method has been used to synthesize aerogel-copper nanocomposites. Carbon, resorcinol-formaldehyde, and silica aerogels (CAs, RFAs, and SAs) were impregnated with a new polyfluorinated copper precursor (CuDI6), which has a high solubility in supercritical carbon dioxide (scCO(2)). Adsorption isotherms of CuDI6 onto various aerogels from scCO(2) were determined at 35 degrees C and 10.6 MPa using a batch method which is based on the measurement of the fluid phase concentration. The relative affinity between CuDI6 and different aerogels changed in the following order: CA > RFA > SA. The effect of temperature on the adsorption isotherms for the CuDI6-CO2-CA system was also studied at 35 and 55 degrees C and at a CO2 density of 736.1 kg/m(3). The CuDI6 uptake at a particular CuDI6 concentration increased with increasing temperature. Adsorbed CuDI6 was found to convert into Cu and Cu/Cu2O nanoparticles on the aerogel supports after chemical or thermal treatments at ambient pressure and at temperatures ranging from 200 to 400 degrees C.Publication Metadata only Aggregation of fillers blended into random elastomeric networks: theory and comparison with experiments(2006) Demir, Mustafa M.; Menceloğlu, Yusuf Z.; Department of Chemical and Biological Engineering; Erman, Burak; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 179997A theoretical model describing aggregation of filler particles in amorphous elastomers is proposed. The model is based on a counting technique originally used in genome analysis to characterize the size and distribution of overlapping segments randomly placed on a DNA molecule. In the present model, the particles are first assumed to aggregate randomly upon mixing into the elastomer and their sizes are calculated. The sizes and distributions of aggregates are also studied in the presence of attractive interparticle forces. Results of the proposed model are compared with experimental data on silica-filled end-linked poly(dimethylsiloxane) networks. Comparison of the theory and experiment shows that the random aggregation assumption where no attractive forces exist between the particles is not valid and a significant attraction between the silica particles is needed in the theory to justify the experimental data obtained using atomic force microscopy. For filler content below 1.45 vol.%, the model agrees, qualitatively, with experiment and shows the increase in cluster size with increasing amount of filler. It also explains the increase in the dispersion of aggregate sizes with increasing amount of filler.Publication Metadata only Anharmonicity, mode-coupling and entropy in a fluctuating native protein(Iop Publishing Ltd, 2010) N/A; Department of Physics; Department of Computer Engineering; N/A; Department of Chemical and Biological Engineering; Kabakçıoğlu, Alkan; Yüret, Deniz; Gür, Mert; Erman, Burak; Faculty Member; Faculty Member; PhD Student; Faculty Member; Department of Physics; Department of Computer Engineering; Department of Chemical and Biological Engineering; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 49854; 179996; 216930; 179997We develop a general framework for the analysis of residue fluctuations that simultaneously incorporates anharmonicity and mode-coupling in a unified formalism. We show that both deviations from the Gaussian model are important for modeling the multidimensional energy landscape of the protein Crambin (1EJG) in the vicinity of its native state. the effect of anharmonicity and mode-coupling on the fluctuational entropy is in the order of a few percent.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 Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics(Institute of Physics (IOP) Publishing, 2018) Gul, Ahmet; Department of Chemical and Biological Engineering; Erman, Burak; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 179997Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.Publication Metadata only Ca3[BN2]I3: the first halide-rich alkaline earth nitridoborate with isolated [BN2]3 - units(Wiley, 2015) Aydemir, Umut; Drathen, Christina; Akselrud, Lev; Prots, Yurii; Hoehn, Peter; Department of Chemical and Biological Engineering; N/A; Department of Chemistry; Toros, Turna Ezgi; Yahyaoğlu, Müjde; Somer, Mehmet Suat; Undergraduate Student; Master Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Chemistry; College of Engineering; Graduate School of Sciences and Engineering; College of Sciences; N/A; N/A; 178882The title compound Ca-3[BN2]I-3 was obtained from reactions of mixtures of the starting materials Ca-3[BN2](2) and CaI2 in a 1:4 ratio in sealed Nb tubes at 1223 K. The crystal structure was solved from powder synchrotron diffraction data. Ca-3[BN2]I-3 is the first example of a halide-rich nitridoborate crystallizing in the rhombohedral space group R32 [no. 155, Pearson code: hR96; Z = 12; a = 16.70491(2) angstrom, c = 12.41024(2) angstrom]. The crystal structure is built up by two interpenetrating networks of condensed edge-sharing [BN2]@Ca-6 and [square]@I-6 trigonal antiprisms (square = void). In Ca-3[BN2]I-3 two crystallograhically distinct [BN2](3-) anions are present with d(B1-N) = 1.393(2) angstrom and d(B2-N) = 1.369(9) angstrom. Their bond angles are practically linear, varying only slightly: N-B1-N = 179(1)degrees and N-B2-N = 180 degrees. Vibrational spectra were interpreted based on the D-infinity h symmetry of the discrete linear [N-B-N](3-) moieties, considering the site symmetry reduction and the presence of two distinct [BN2](3-) groups.Publication Metadata only Characterization and prediction of protein interfaces to infer protein-protein interaction networks(Bentham Science Publ Ltd, 2008) N/A; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Tunçbağ, Nurcan; Gürsoy, Attila; Faculty Member; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; College of Engineering; 26605; 245513; 8745Complex protein-protein interaction networks govern biological processes in cells. Protein interfaces are the sites where proteins physically interact. Identification and characterization of protein interfaces will lead to understanding how proteins interact with each other and how they are involved in protein-protein interaction networks. What makes a given interface bind to different proteins; how similar/different the interactions in proteins are some key questions to be answered. Enormous amount of protein structures and experimental protein-protein interactions data necessitate advanced computational methods for analyzing and inferring new knowledge. Interface prediction methods use a wide range of sequence, structural and physico-chemical characteristics that distinguish interface residues from non-interface surface residues. Here, we present a review focusing on the characteristics of interfaces and the current status of interface prediction methods.Publication Open Access Classification of drug molecules considering their IC(50) values using mixed-integer linear programming based hyper-boxes method(BioMed Central, 2008) Department of Industrial Engineering; Department of Chemical and Biological Engineering; Armutlu, Pelin; Özdemir, Muhittin Emre; Yüksektepe, Fadime Üney; Kavaklı, İbrahim Halil; Türkay, Metin; Faculty Member; Department of Industrial Engineering; Department of Chemical and Biological Engineering; The Center for Computational Biology and Bioinformatics (CCBB); College of Engineering; N/A; N/A; N/A; 40319; 24956Background: A priori analysis of the activity of drugs on the target protein by computational approaches can be useful in narrowing down drug candidates for further experimental tests. Currently, there are a large number of computational methods that predict the activity of drugs on proteins. In this study, we approach the activity prediction problem as a classification problem and, we aim to improve the classification accuracy by introducing an algorithm that combines partial least squares regression with mixed-integer programming based hyper-boxes classification method, where drug molecules are classified as low active or high active regarding their binding activity (IC(50) values) on target proteins. We also aim to determine the most significant molecular descriptors for the drug molecules. Results: We first apply our approach by analyzing the activities of widely known inhibitor datasets including Acetylcholinesterase (ACHE), Benzodiazepine Receptor (BZR), Dihydrofolate Reductase (DHFR), Cyclooxygenase-2 (COX-2) with known IC(50) values. The results at this stage proved that our approach consistently gives better classification accuracies compared to 63 other reported classification methods such as SVM, Naive Bayes, where we were able to predict the experimentally determined IC50 values with a worst case accuracy of 96%. To further test applicability of this approach we first created dataset for Cytochrome P450 C17 inhibitors and then predicted their activities with 100% accuracy. Conclusion: Our results indicate that this approach can be utilized to predict the inhibitory effects of inhibitors based on their molecular descriptors. This approach will not only enhance drug discovery process, but also save time and resources committed.Publication Open Access Comparative RNA-seq analysis of the drought-sensitive lentil (Lens culinaris) root and leaf under short- and long-term water deficits(Springer, 2019) Morgil, Hande; Cevahir, Gül; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; N/A; Kavaklı, İbrahim Halil; Tardu, Mehmet; Faculty Member; PhD Student; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; 40319; N/ADrought stress is one of the main environmental factors that affects growth and productivity of crop plants, including lentil. To gain insights into the genome-wide transcriptional regulation in lentil root and leaf under short- and long-term drought conditions, we performed RNA-seq on a drought-sensitive lentil cultivar (Lens culinaris Medik. cv. Sultan). After establishing drought conditions, lentil samples were subjected to de novo RNA-seq-based transcriptome analysis. The 207,076 gene transcripts were successfully constructed by de novo assembly from the sequences obtained from root, leaf, and stems. Differentially expressed gene (DEG) analysis on these transcripts indicated that period of drought stress had a greater impact on the transcriptional regulation in lentil root. The numbers of DEGs were 2915 under short-term drought stress while the numbers of DEGs were increased to 18,327 under long-term drought stress condition in the root. Further, Gene Ontology analysis revealed that the following biological processes were differentially regulated in response to long-term drought stress: protein phosphorylation, embryo development seed dormancy, DNA replication, and maintenance of root meristem identity. Additionally, DEGs, which play a role in circadian rhythm and photoreception, were downregulated suggesting that drought stress has a negative effect on the internal oscillators which may have detrimental consequences on plant growth and survival. Collectively, this study provides a detailed comparative transcriptome response of drought-sensitive lentil strain under short- and long-term drought conditions in root and leaf. Our finding suggests that not only the regulation of genes in leaves is important but also genes regulated in roots are important and need to be considered for improving drought tolerance in lentil.