Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79
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Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
Structure of the Mammalian 80S Initiation Complex with Initiation Factor 5B on HCV-IRES RNA
ARTICLES Structure of the mammalian 80S initiation complex with initiation factor 5B on HCV-IRES RNA Hiroshi Yamamoto1,3, Anett Unbehaun1,3, Justus Loerke1, Elmar Behrmann1, Marianne Collier1, Jörg Bürger1,2, Thorsten Mielke1,2 & Christian M T Spahn1 The universally conserved eukaryotic initiation factor (eIF) 5B, a translational GTPase, is essential for canonical translation initiation. It is also required for initiation facilitated by the internal ribosomal entry site (IRES) of hepatitis C virus (HCV) RNA. Met eIF5B promotes joining of 60S ribosomal subunits to 40S ribosomal subunits bound by initiator tRNA (Met-tRNAi ). However, the exact molecular mechanism by which eIF5B acts has not been established. Here we present cryo-EM reconstructions of the Met mammalian 80S–HCV-IRES–Met-tRNAi –eIF5B–GMPPNP complex. We obtained two substates distinguished by the rotational state of the ribosomal subunits and the configuration of initiator tRNA in the peptidyl (P) site. Accordingly, a combination of Met conformational changes in the 80S ribosome and in initiator tRNA facilitates binding of the Met-tRNAi to the 60S P site and redefines the role of eIF5B as a tRNA-reorientation factor. Met Eukaryotic translation initiation is a highly regulated process within stable ribosomal binding of Met-tRNAi and elongation competence the translation cycle that proceeds via 48S and 80S initiation-complex in vivo11–13. However, the molecular mechanism linking eIF5B–GTP Met Met intermediates. At least 12 eIFs facilitate recruitment of Met-tRNAi hydrolysis and proper placement of Met-tRNAi in the ribosomal and mRNA to the ribosomal 40S subunit and regulate the interaction of P site is not known. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Datasheet Blank Template
SAN TA C RUZ BI OTEC HNOL OG Y, INC . CWC15 (C-8): sc-514479 BACKGROUND APPLICATIONS CWC15 (CWC15 spliceosome-associated protein), also known as ORF5, Cwf15, CWC15 (C-8) is recommended for detection of CWC15 of mouse, rat and C11orf5 or HSPC14, is a 229 amino acid protein involved in pre-mRNA splicing. human origin by Western Blotting (starting dilution 1:100, dilution range The gene encoding CWC15 maps to human chromosome 11q21. With approx - 1:100- 1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein imately 135 million base pairs and 1,400 genes, chromosome 11 makes up (1 ml of cell lysate)], immunofluorescence (starting dilution 1:50, dilution around 4% of human genomic DNA and is considered a gene and disease as- range 1:50- 1:500) and solid phase ELISA (starting dilution 1:30, dilution sociation dense chromosome. The chromosome 11 encoded Atm gene is impor - range 1:30-1:3000). tant for regulation of cell cycle arrest and apoptosis following double strand Suitable for use as control antibody for CWC15 siRNA (h): sc-97055, CWC15 DNA breaks. Atm mutation leads to the disorder known as ataxia-telang iecta - siRNA (m): sc-142639, CWC15 shRNA Plasmid (h): sc-97055-SH, CWC15 sia. The blood disorders sickle cell anemia and thalassemia are caused by β shRNA Plasmid (m): sc-142639-SH, CWC15 shRNA (h) Lentiviral Particles: HBB gene mutations. Wilms’ tumors, WAGR syndrome and Denys-Drash syn - sc- 97055-V and CWC15 shRNA (m) Lentiviral Particles: sc-142639-V. drome are associated with mutations of the WT1 gene. -
Structural Characterization of the Human Eukaryotic Initiation Factor 3 Protein Complex by Mass Spectrometry*□S
Supplemental Material can be found at: http://www.mcponline.org/cgi/content/full/M600399-MCP200 /DC1 Research Structural Characterization of the Human Eukaryotic Initiation Factor 3 Protein Complex by Mass Spectrometry*□S Eugen Damoc‡, Christopher S. Fraser§, Min Zhou¶, Hortense Videler¶, Greg L. Mayeurʈ, John W. B. Hersheyʈ, Jennifer A. Doudna§, Carol V. Robinson¶**, and Julie A. Leary‡ ‡‡ Protein synthesis in mammalian cells requires initiation The initiation phase of eukaryotic protein synthesis involves factor eIF3, an ϳ800-kDa protein complex that plays a formation of an 80 S ribosomal complex containing the initi- Downloaded from central role in binding of initiator methionyl-tRNA and ator methionyl-tRNAi bound to the initiation codon in the mRNA to the 40 S ribosomal subunit to form the 48 S mRNA. This is a multistep process promoted by proteins initiation complex. The eIF3 complex also prevents pre- called eukaryotic initiation factors (eIFs).1 Currently at least 12 mature association of the 40 and 60 S ribosomal subunits eIFs, composed of at least 29 distinct subunits, have been and interacts with other initiation factors involved in start identified (1). Mammalian eIF3, the largest initiation factor, is a codon selection. The molecular mechanisms by which multisubunit complex with an apparent molecular mass of www.mcponline.org eIF3 exerts these functions are poorly understood. Since ϳ800 kDa. This protein complex plays an essential role in its initial characterization in the 1970s, the exact size, translation by binding directly to the 40 S ribosomal subunit composition, and post-translational modifications of and promoting formation of the 43 S preinitiation complex ⅐ ⅐ mammalian eIF3 have not been rigorously determined. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology
Cancer Research and Treatment 2003;35(4):304-313 New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology Yong-Wan Kim, Ph.D.1, Min-Je Suh, M.S.1, Jin-Sik Bae, M.S.1, Su Mi Bae, M.S.1, Joo Hee Yoon, M.D.2, Soo Young Hur, M.D.2, Jae Hoon Kim, M.D.2, Duck Young Ro, M.D.2, Joon Mo Lee, M.D.2, Sung Eun Namkoong, M.D.2, Chong Kook Kim, Ph.D.3 and Woong Shick Ahn, M.D.2 1Catholic Research Institutes of Medical Science, 2Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul; 3College of Pharmacy, Seoul National University, Seoul, Korea Purpose: This study utilized both mRNA differential significant genes of unknown function affected by the display and the Gene Ontology (GO) analysis to char- HPV-16-derived pathway. The GO analysis suggested that acterize the multiple interactions of a number of genes the cervical cancer cells underwent repression of the with gene expression profiles involved in the HPV-16- cancer-specific cell adhesive properties. Also, genes induced cervical carcinogenesis. belonging to DNA metabolism, such as DNA repair and Materials and Methods: mRNA differential displays, replication, were strongly down-regulated, whereas sig- with HPV-16 positive cervical cancer cell line (SiHa), and nificant increases were shown in the protein degradation normal human keratinocyte cell line (HaCaT) as a con- and synthesis. trol, were used. Each human gene has several biological Conclusion: The GO analysis can overcome the com- functions in the Gene Ontology; therefore, several func- plexity of the gene expression profile of the HPV-16- tions of each gene were chosen to establish a powerful associated pathway, identify several cancer-specific cel- cervical carcinogenesis pathway. -
Molecular Basis for the Distinct Cellular Functions of the Lsm1-7 and Lsm2-8 Complexes
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.055376; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Molecular basis for the distinct cellular functions of the Lsm1-7 and Lsm2-8 complexes Eric J. Montemayor1,2, Johanna M. Virta1, Samuel M. Hayes1, Yuichiro Nomura1, David A. Brow2, Samuel E. Butcher1 1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. 2Department of Biomolecular Chemistry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. Correspondence should be addressed to E.J.M. ([email protected]) and S.E.B. ([email protected]). Abstract Eukaryotes possess eight highly conserved Lsm (like Sm) proteins that assemble into circular, heteroheptameric complexes, bind RNA, and direct a diverse range of biological processes. Among the many essential functions of Lsm proteins, the cytoplasmic Lsm1-7 complex initiates mRNA decay, while the nuclear Lsm2-8 complex acts as a chaperone for U6 spliceosomal RNA. It has been unclear how these complexes perform their distinct functions while differing by only one out of seven subunits. Here, we elucidate the molecular basis for Lsm-RNA recognition and present four high-resolution structures of Lsm complexes bound to RNAs. The structures of Lsm2-8 bound to RNA identify the unique 2′,3′ cyclic phosphate end of U6 as a prime determinant of specificity. In contrast, the Lsm1-7 complex strongly discriminates against cyclic phosphates and tightly binds to oligouridylate tracts with terminal purines. -
Posters A.Pdf
INVESTIGATING THE COUPLING MECHANISM IN THE E. COLI MULTIDRUG TRANSPORTER, MdfA, BY FLUORESCENCE SPECTROSCOPY N. Fluman, D. Cohen-Karni, E. Bibi Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, Israel In bacteria, multidrug transporters couple the energetically favored import of protons to export of chemically-dissimilar drugs (substrates) from the cell. By this function, they render bacteria resistant against multiple drugs. In this work, fluorescence spectroscopy of purified protein is used to unravel the mechanism of coupling between protons and substrates in MdfA, an E. coli multidrug transporter. Intrinsic fluorescence of MdfA revealed that binding of an MdfA substrate, tetraphenylphosphonium (TPP), induced a conformational change in this transporter. The measured affinity of MdfA-TPP was increased in basic pH, raising a possibility that TPP might bind tighter to the deprotonated state of MdfA. Similar increases in affinity of TPP also occurred (1) in the presence of the substrate chloramphenicol, or (2) when MdfA is covalently labeled by the fluorophore monobromobimane at a putative chloramphenicol interacting site. We favor a mechanism by which basic pH, chloramphenicol binding, or labeling with monobromobimane, all induce a conformational change in MdfA, which results in deprotonation of the transporter and increase in the affinity of TPP. PHENOTYPE CHARACTERIZATION OF AZOSPIRILLUM BRASILENSE Sp7 ABC TRANSPORTER (wzm) MUTANT A. Lerner1,2, S. Burdman1, Y. Okon1,2 1Department of Plant Pathology and Microbiology, Faculty of Agricultural, Food and Environmental Quality Sciences, Hebrew University of Jerusalem, Rehovot, Israel, 2The Otto Warburg Center for Agricultural Biotechnology, Faculty of Agricultural, Food and Environmental Quality Sciences, Hebrew University of Jerusalem, Rehovot, Israel Azospirillum, a free-living nitrogen fixer, belongs to the plant growth promoting rhizobacteria (PGPR), living in close association with plant roots. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
Study of the G Protein Nucleolar 2 Value in Liver Hepatocellular Carcinoma Treatment and Prognosis
Hindawi BioMed Research International Volume 2021, Article ID 4873678, 12 pages https://doi.org/10.1155/2021/4873678 Research Article Study of the G Protein Nucleolar 2 Value in Liver Hepatocellular Carcinoma Treatment and Prognosis Yiwei Dong,1 Qianqian Cai,2 Lisheng Fu,1 Haojie Liu,1 Mingzhe Ma,3 and Xingzhong Wu 1 1Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Key Lab of Glycoconjugate Research, Ministry of Public Health, Shanghai 200032, China 2Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China 3Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai 200025, China Correspondence should be addressed to Xingzhong Wu; [email protected] Received 10 May 2021; Accepted 29 June 2021; Published 20 July 2021 Academic Editor: Tao Huang Copyright © 2021 Yiwei Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. LIHC (liver hepatocellular carcinoma) mostly occurs in patients with chronic liver disease. It is primarily induced by a vicious cycle of liver injury, inflammation, and regeneration that usually last for decades. The G protein nucleolar 2 (GNL2), as a protein- encoding gene, is also known as NGP1, Nog2, Nug2, Ngp-1, and HUMAUANTIG. Few reports are shown towards the specific biological function of GNL2. Meanwhile, it is still unclear whether it is related to the pathogenesis of carcinoma up to date. Here, our study attempts to validate the role and function of GNL2 in LIHC via multiple databases and functional assays.