PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
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Article Citation - WoS: 2Citation - Scopus: 3Non-Apoptotic Cell Death Induction Via Sapogenin Based Supramolecular Particles(Nature Publishing Group, 2022) Üner, Göklem; Bedir, Erdal; Serçinoğlu, Onur; Ballar Kırmızıbayrak, PetekThe discovery of novel chemotherapeutics that act through different mechanisms is critical for dealing with tumor heterogeneity and therapeutic resistance. We previously reported a saponin analog (AG-08) that induces non-canonical necrotic cell death and is auspicious for cancer therapy. Here, we describe that the key element in triggering this unique cell death mechanism of AG-08 is its ability to form supramolecular particles. These self-assembled particles are internalized via a different endocytosis pathway than those previously described. Microarray analysis suggested that AG-08 supramolecular structures affect several cell signaling pathways, including unfolded protein response, immune response, and oxidative stress. Finally, through investigation of its 18 analogs, we further determined the structural features required for the formation of particulate structures and the stimulation of the unprecedented cell death mechanism of AG-08. The unique results of AG-08 indicated that supramolecular assemblies of small molecules are promising for the field of anticancer drug development, although they have widely been accepted as nuisance in drug discovery studies.Article Citation - WoS: 7Citation - Scopus: 7Novel Regulation Mechanism of Adrenal Cortisol and Dhea Biosynthesis Via the Endogen Erad Inhibitor Small Vcp-Interacting Protein(Nature Publishing Group, 2022) İlhan, Recep; Üner, Göklem; Yılmaz, Sinem; Atalay Sahar, Esra; Çaylı, Sevil; Erzurumlu, Yalçın; Gözen, Oğuz; Ballar Kırmızıbayrak, PetekEndoplasmic reticulum-associated degradation (ERAD) is a well-characterized mechanism of protein quality control by removal of misfolded or unfolded proteins. The tight regulation of ERAD is critical for protein homeostasis as well as lipid metabolism. Although the mechanism is complex, all ERAD branches converge on p97/VCP, a key protein in the retrotranslocation step. The multifunctionality of p97/VCP relies on its multiple binding partners, one of which is the endogenous ERAD inhibitor, SVIP (small VCP-interacting protein). As SVIP is a promising target for the regulation of ERAD, we aimed to assess its novel physiological roles. We revealed that SVIP is highly expressed in the rat adrenal gland, especially in the cortex region, at a consistently high level during postnatal development, unlike the gradual increase in expression seen in developing nerves. Steroidogenic stimulators caused a decrease in SVIP mRNA expression and increase in SVIP protein degradation in human adrenocortical H295R cells. Interestingly, silencing of SVIP diminished cortisol secretion along with downregulation of steroidogenic enzymes and proteins involved in cholesterol uptake and cholesterol biosynthesis. A certain degree of SVIP overexpression mainly increased the biosynthesis of cortisol as well as DHEA by enhancing the expression of key steroidogenic proteins, whereas exaggerated overexpression led to apoptosis, phosphorylation of eIF2α, and diminished adrenal steroid hormone biosynthesis. In conclusion, SVIP is a novel regulator of adrenal cortisol and DHEA biosynthesis, suggesting that alterations in SVIP expression levels may be involved in the deregulation of steroidogenic stimulator signaling and abnormal adrenal hormone secretion.Article Citation - WoS: 62Citation - Scopus: 59Exponentially Selective Molecular Sieving Through Angstrom Pores(Nature Publishing Group, 2021) Sun, Pengzhan; Yağmurcukardeş, Mehmet; Zhang, R.; Kuang, Wenjun; Lozada-Hidalgo, Marcelo; Liu, B. L.; Geim, Andre K.Two-dimensional crystals with angstrom-scale pores are widely considered as candidates for a next generation of molecular separation technologies aiming to provide extreme, exponentially large selectivity combined with high flow rates. No such pores have been demonstrated experimentally. Here we study gas transport through individual graphene pores created by low intensity exposure to low kV electrons. Helium and hydrogen permeate easily through these pores whereas larger species such as xenon and methane are practically blocked. Permeating gases experience activation barriers that increase quadratically with molecules’ kinetic diameter, and the effective diameter of the created pores is estimated as ∼2 angstroms, about one missing carbon ring. Our work reveals stringent conditions for achieving the long sought-after exponential selectivity using porous two-dimensional membranes and suggests limits on their possible performance.Article Citation - WoS: 16Citation - Scopus: 15Gene Cloning, Heterologous Expression, and Partial Characterization of a Novel Cold-Adapted Subfamily I.3 Lipase From Pseudomonas Fluorescence Ke38(Nature Publishing Group, 2020) Karakaş, Fulya; Arslanoğlu, AlperA novel cold-active true lipase from Pseudomonas sp. KE38 was cloned, sequencing and expressed in E. coli by degenerate PCR and genome walking technique. The open reading frame of the cloned gene encoded a polypeptide chain of 617 amino acids with a confirmed molecular weight of 64 kD. Phylogenetic analysis of the deduced amino acid sequence of the lipase indicated that it had high similarity with lipases of subfamily ?.3 of bacterial lipases. Recombinant lipase was purified in denatured form as inclusion bodies, which were then renatured by urea followed by dialysis. Lipase activity was determined titrimetrically using olive oil as substrate. The enzyme showed optimal activity at 25 °C, pH 8.5 and was highly stable in the presence of various metal ions and organic solvents. Low optimal temperature and high activity in the presence of methanol and ethanol make this lipase a potential candidate for transesterification reactions and biodiesel production. © 2020, The Author(s).Article Citation - WoS: 26Citation - Scopus: 27Internal Surface Electric Charge Characterization of Mesoporous Silica(Nature Publishing Group, 2019) Şen, Tümcan; Barışık, MuratMesoporous silica is an emerging technology to solve problems of existing and to support projected revolutionary applications ranging from targeted drug delivery to artificial kidney. However, one of the major driving mechanisms, electric charging of internal mesoporous surfaces, has not been characterized yet. In the nanoscale confinements of mesoporous structures made of pore throats and pore voids, surface charges diverge from existing theoretical calculations and show local variation due to two occurrences. First, when the size of pore throat becomes comparable with the thickness of ionic layering forming on throats' surfaces, ionic layers from opposite surfaces overlap so that ionic concentration on the surface becomes different than Boltzmann distribution predicts, and there will no longer be an equilibrium of zero electric potential at pore throat centers. Second, when this non zero potential inside throats becomes different than the potential of pore voids, ionic diffusion from void to throat creates axial ionic variation on surfaces. For such a case, we performed a pore level analysis on mesoporous internal surface charge at various porosities and ionic conditions. Pore parameters strongly affected the average internal charge which we characterized as a function of overlap ratio and porosity, first time in literature. Using this, a phenomenological model was developed as an extension of the existing theory to include nano-effects, to predict the average mesoporous internal surface charge as a function of EDL thickness, pore size and porosity.Article Citation - WoS: 12Citation - Scopus: 15Magnetic Mechanism for the Biological Functioning of Hemoglobin(Nature Publishing Group, 2020) Mayda, Selma; Kandemir, Zafer; Bulut, Nejat; Maekawa, SadamichiThe role of magnetism in the biological functioning of hemoglobin has been debated since its discovery by Pauling and Coryell in 1936. The hemoglobin molecule contains four heme groups each having a porphyrin layer with a Fe ion at the center. Here, we present combined density-functional theory and quantum Monte Carlo calculations for an effective model of Fe in a heme cluster. In comparison with these calculations, we analyze the experimental data on human adult hemoglobin (HbA) from the magnetic susceptibility, Mossbauer and magnetic circular dichroism (MCD) measurements. In both the deoxygenated (deoxy) and the oxygenated (oxy) cases, we show that local magnetic moments develop in the porphyrin layer with antiferromagnetic coupling to the Fe moment. Our calculations reproduce the magnetic susceptibility measurements on deoxy and oxy-HbA. For deoxy-HbA, we show that the anomalous MCD signal in the UV region is an experimental evidence for the presence of antiferromagnetic Fe-porphyrin correlations. The functional properties of hemoglobin such as the binding of O-2, the Bohr effect and the cooperativity are explained based on the magnetic correlations. This analysis suggests that magnetism could be involved in the functioning of hemoglobin.Article Citation - WoS: 79Citation - Scopus: 94Biofabrication of in Situ Self Assembled 3d Cell Cultures in a Weightlessness Environment Generated Using Magnetic Levitation(Nature Publishing Group, 2018) Anıl İnevi, Müge; Yaman, Sena; Arslan Yıldız, Ahu; Meşe, Gülistan; Yalçın Özuysal, Özden; Tekin, Hüseyin Cumhur; Özçivici, EnginMagnetic levitation though negative magnetophoresis is a novel technology to simulate weightlessness and has recently found applications in material and biological sciences. Yet little is known about the ability of the magnetic levitation system to facilitate biofabrication of in situ three dimensional (3D) cellular structures. Here, we optimized a magnetic levitation though negative magnetophoresis protocol appropriate for long term levitated cell culture and developed an in situ 3D cellular assembly model with controlled cluster size and cellular pattern under simulated weightlessness. The developed strategy outlines a potential basis for the study of weightlessness on 3D living structures and with the opportunity for real-time imaging that is not possible with current ground-based simulated weightlessness techniques. The low-cost technique presented here may offer a wide range of biomedical applications in several research fields, including mechanobiology, drug discovery and developmental biology.Article Citation - WoS: 560Citation - Scopus: 607A Community Effort To Assess and Improve Drug Sensitivity Prediction Algorithms(Nature Publishing Group, 2014) Costello, James C.; Heiser, Laura M.; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P.; Wang, Nicholas J.; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A.; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; NCI-DREAM Community; Karaçalı, Bilge; Collins, James J.; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W.; Stolovitzky, GustavoPredicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.Article Citation - WoS: 240Citation - Scopus: 264A Community Computational Challenge To Predict the Activity of Pairs of Compounds(Nature Publishing Group, 2014) Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P.; Costello, James C.; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M.; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J.; Shen, Yao; NCI-DREAM Community; Karaçalı, Bilge; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, AndreaRecent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.Article Citation - WoS: 37Citation - Scopus: 45On the Performance of Pre-Microrna Detection Algorithms(Nature Publishing Group, 2017) Saçar Demirci, Müşerref Duygu; Baumbach, Jan; Allmer, JensMicroRNAs are crucial for post-transcriptional gene regulation, and their dysregulation has been associated with diseases like cancer and, therefore, their analysis has become popular. The experimental discovery of miRNAs is cumbersome and, thus, many computational tools have been proposed. Here we assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new ones, and combining multiple approaches into ensemble methods. In an exhaustive attempt, we condense the results of millions of computations and show that no method is clearly superior; however, we provide a guideline for biomedical researchers to select a tool. Finally, we demonstrate that combining all of the methods into one ensemble approach, for the first time, allows reliable purely computational pre-miRNA detection in large eukaryotic genomes.