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Real-Time Pymol Visualization for Rosetta and Pyrosetta
Real-Time PyMOL Visualization for Rosetta and PyRosetta Evan H. Baugh1, Sergey Lyskov1, Brian D. Weitzner1, Jeffrey J. Gray1,2* 1 Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland, United States of America, 2 Program in Molecular Biophysics, The Johns Hopkins University, Baltimore, Maryland, United States of America Abstract Computational structure prediction and design of proteins and protein-protein complexes have long been inaccessible to those not directly involved in the field. A key missing component has been the ability to visualize the progress of calculations to better understand them. Rosetta is one simulation suite that would benefit from a robust real-time visualization solution. Several tools exist for the sole purpose of visualizing biomolecules; one of the most popular tools, PyMOL (Schro¨dinger), is a powerful, highly extensible, user friendly, and attractive package. Integrating Rosetta and PyMOL directly has many technical and logistical obstacles inhibiting usage. To circumvent these issues, we developed a novel solution based on transmitting biomolecular structure and energy information via UDP sockets. Rosetta and PyMOL run as separate processes, thereby avoiding many technical obstacles while visualizing information on-demand in real-time. When Rosetta detects changes in the structure of a protein, new coordinates are sent over a UDP network socket to a PyMOL instance running a UDP socket listener. PyMOL then interprets and displays the molecule. This implementation also allows remote execution of Rosetta. When combined with PyRosetta, this visualization solution provides an interactive environment for protein structure prediction and design. Citation: Baugh EH, Lyskov S, Weitzner BD, Gray JJ (2011) Real-Time PyMOL Visualization for Rosetta and PyRosetta. -
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. -
Negative Regulation of TIMP1 Is Mediated by Transcription Factor TWIST1
181-186.qxd 29/5/2009 01:25 ÌÌ ™ÂÏ›‰·181 INTERNATIONAL JOURNAL OF ONCOLOGY 35: 181-186, 2009 181 Negative regulation of TIMP1 is mediated by transcription factor TWIST1 HIROHIKO OKAMURA1, KAYA YOSHIDA2 and TATSUJI HANEJI1 Departments of 1Histology and Oral Histology and 2Fundamental Oral Health Science, Institute of Health Biosciences, The University of Tokushima Graduate School, Kuramoto, Tokushima 770-8504, Japan Received January 13, 2009; Accepted March 27, 2009 DOI: 10.3892/ijo_00000327 Abstract. TWIST1 is involved in tumor invasion and meta- process was mediated through suppression of the ARF/ stasis by promoting epithelial-to-mesenchymal transition. MDM2/p53 pathway (6). It was also reported that amplification However, the molecular target of TWIST1 involving this of Twist1 gene was associated with the development of mechanism is poorly understood. To identify the TWIST1- acquired resistance to anticancer drugs and ectopic expression regulated genes, we established the Saos-2 cells stably of Twist1 gene leads to resistance to microtubule disrupting expressing TWIST1 gene by transfecting TWIST1 cDNA into agents (7). TWIST1 is shown to affect AKT to mediate taxol the cells and performed a differential display approach by resistance in nasopharyngeal carcinoma cells and up- using annealing control primers. Here, we report that one of regulation of AKT2 by TWIST1 promoted cell survival, the genes that were down-regulated in TWIST1 expressing migration and invasion in breast cancer cells (8,9). The cells is predicted to be TIMP1. TIMP1 has been reported as increased expression of TWIST1 has been commonly used as the naturally occurring specific inhibitor of matrix metallo- molecular marker for EMT (10). -
(MINA) (NM 032778) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC212554L4 MINA53 (MINA) (NM_032778) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: MINA53 (MINA) (NM_032778) Human Tagged ORF Clone Tag: mGFP Symbol: RIOX2 Synonyms: JMJD10; MDIG; MINA; MINA53; NO52; ROX Vector: pLenti-C-mGFP-P2A-Puro (PS100093) E. coli Selection: Chloramphenicol (34 ug/mL) Cell Selection: Puromycin ORF Nucleotide The ORF insert of this clone is exactly the same as(RC212554). Sequence: Restriction Sites: SgfI-MluI Cloning Scheme: ACCN: NM_032778 ORF Size: 1392 bp This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 MINA53 (MINA) (NM_032778) Human Tagged ORF Clone – RC212554L4 OTI Disclaimer: The molecular sequence of this clone aligns with the gene accession number as a point of reference only. However, individual transcript sequences of the same gene can differ through naturally occurring variations (e.g. polymorphisms), each with its own valid existence. This clone is substantially in agreement with the reference, but a complete review of all prevailing variants is recommended prior to use. More info OTI Annotation: This clone was engineered to express the complete ORF with an expression tag. Expression varies depending on the nature of the gene. RefSeq: NM_032778.3, NP_116167.3 RefSeq Size: 2221 bp RefSeq ORF: 1395 bp Locus ID: 84864 UniProt ID: Q8IUF8 Protein Families: Druggable Genome MW: 52.5 kDa Gene Summary: MINA is a c-Myc (MYC; MIM 190080) target gene that may play a role in cell proliferation or regulation of cell growth. -
Suramin Inhibits Osteoarthritic Cartilage Degradation by Increasing Extracellular Levels
Molecular Pharmacology Fast Forward. Published on August 10, 2017 as DOI: 10.1124/mol.117.109397 This article has not been copyedited and formatted. The final version may differ from this version. MOL #109397 Suramin inhibits osteoarthritic cartilage degradation by increasing extracellular levels of chondroprotective tissue inhibitor of metalloproteinases 3 (TIMP-3). Anastasios Chanalaris, Christine Doherty, Brian D. Marsden, Gabriel Bambridge, Stephen P. Wren, Hideaki Nagase, Linda Troeberg Arthritis Research UK Centre for Osteoarthritis Pathogenesis, Kennedy Institute of Downloaded from Rheumatology, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7FY, UK (A.C., C.D., G.B., H.N., L.T.); Alzheimer’s Research UK Oxford Drug Discovery Institute, University of Oxford, Oxford, OX3 7FZ, UK (S.P.W.); Structural Genomics Consortium, molpharm.aspetjournals.org University of Oxford, Old Road Campus Research Building, Old Road Campus, Roosevelt Drive, Headington, Oxford, OX3 7DQ (BDM). at ASPET Journals on September 29, 2021 1 Molecular Pharmacology Fast Forward. Published on August 10, 2017 as DOI: 10.1124/mol.117.109397 This article has not been copyedited and formatted. The final version may differ from this version. MOL #109397 Running title: Repurposing suramin to inhibit osteoarthritic cartilage loss. Corresponding author: Linda Troeberg Address: Kennedy Institute of Rheumatology, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7FY, UK Phone number: +44 (0)1865 612600 E-mail: [email protected] Downloaded -
64-194 Projekt Parallelrechnerevaluation Abschlussbericht
64-194 Projekt Parallelrechnerevaluation Abschlussbericht Automatisierte Build-Tests für Spack Sarah Lubitz Malte Fock [email protected] [email protected] Studiengang: LA Berufliche Schulen – Informatik Studiengang LaGym - Informatik Matr.-Nr. 6570465 Matr.-Nr. 6311966 Inhaltsverzeichnis i Inhaltsverzeichnis 1 Einleitung1 1.1 Motivation.....................................1 1.2 Vorbereitungen..................................2 1.2.1 Spack....................................2 1.2.2 Python...................................2 1.2.3 Unix-Shell.................................3 1.2.4 Slurm....................................3 1.2.5 GitHub...................................4 2 Code 7 2.1 Automatisiertes Abrufen und Installieren von Spack-Paketen.......7 2.1.1 Python Skript: install_all_packets.py..................7 2.2 Batch-Jobskripte..................................9 2.2.1 Test mit drei Paketen........................... 10 2.3 Analyseskript................................... 11 2.3.1 Test mit 500 Paketen........................... 12 2.3.2 Code zur Analyse der Error-Logs, forts................. 13 2.4 Hintereinanderausführung der Installationen................. 17 2.4.1 Wrapper Skript.............................. 19 2.5 E-Mail Benachrichtigungen........................... 22 3 Testlauf 23 3.1 Durchführung und Ergebnisse......................... 23 3.2 Auswertung und Schlussfolgerungen..................... 23 3.3 Fazit und Ausblick................................ 24 4 Schulische Relevanz 27 Literaturverzeichnis -
Investigation of COVID-19 Comorbidities Reveals Genes and Pathways Coincident with the SARS-Cov-2 Viral Disease
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.21.306720; this version posted September 21, 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-ND 4.0 International license. Title: Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease. Authors: Mary E. Dolan1*,2, David P. Hill1,2, Gaurab Mukherjee2, Monica S. McAndrews2, Elissa J. Chesler2, Judith A. Blake2 1 These authors contributed equally and should be considered co-first authors * Corresponding author [email protected] 2 The Jackson Laboratory, 600 Main St, Bar Harbor, ME 04609, USA Abstract: The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID- 19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. -
ABCB5 Recombinant Protein Cat
ABCB5 Recombinant Protein Cat. No.: 92-176 ABCB5 Recombinant Protein Specifications SPECIES: Human SOURCE SPECIES: E. coli SEQUENCE: Ile141-Val247 FUSION TAG: N-Trx tag TESTED APPLICATIONS: APPLICATIONS: This recombinant protein can be used for biological assays. For research use only. PREDICTED MOLECULAR 29.4 kD WEIGHT: Properties Greater than 95% as determined by reducing SDS-PAGE. PURITY: Endotoxin level less than 0.1 ng/ug (1 IEU/ug) as determined by LAL test. PHYSICAL STATE: Lyophilized Lyophilized from a 0.2 um filtered solution of 20mM PB,150mM NaCl,pH7.4. It is not BUFFER: recommended to reconstitute to a concentration less than 100 ug/ml. Dissolve the lyophilized protein in ddH2O. September 23, 2021 1 https://www.prosci-inc.com/abcb5-recombinant-protein-92-176.html Lyophilized protein should be stored at -20˚C, though stable at room temperature for 3 weeks. STORAGE CONDITIONS: Reconstituted protein solution can be stored at 4-7˚C for 2-7 days. Aliquots of reconstituted samples are stable at -20˚C for 3 months. Additional Info OFFICIAL SYMBOL: ABCB5 ALTERNATE NAMES: ATP-binding cassette sub-family B member 5, P-glycoprotein ABCB5, ABCB5 P-gp, ABCB5 ACCESSION NO.: Q2M3G0 GENE ID: 340273 Background and References ATP-binding cassette sub-family B member 5(ABCB5) is a plasma membrane-spanning protein. ABCB5 is principally expressed in physiological skin and human malignant melanoma. ABCB5 has been suggested to regulate skin progenitor cell fusion and mediate chemotherapeutic drug resistance in stem-like tumor cell subpopulations in BACKGROUND: human malignant melanoma. It is commonly over-expressed on circulating melanoma tumour cells. -
Identification of Gene Expression and DNA Methylation of SERPINA5 and TIMP1 As Novel Prognostic Markers in Lower-Grade Gliomas
Identification of gene expression and DNA methylation of SERPINA5 and TIMP1 as novel prognostic markers in lower-grade gliomas Wen-Jing Zeng1,2,3,4, Yong-Long Yang5, Zhi-Peng Wen1,2, Peng Chen1,2, Xiao-Ping Chen1,2 and Zhi-Cheng Gong3,4 1 Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, Hunan, China 2 Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha, Hunan, China 3 Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, Hunan, China 4 National Clinical Research Center for Geriatric Disorders (XIANGYA), Xiangya Hospital, Central South University, Changsha, Hunan, China 5 Department of Clinical Pharmacology Research Center, Changsha Carnation Geriatrics Hospital, Changsha, Hunan, China ABSTRACT Background. Lower-grade gliomas (LGGs) is characteristic with great difference in prognosis. Due to limited prognostic biomarkers, it is urgent to identify more molecular markers to provide a more objective and accurate tumor classification system for LGGs. Methods. In the current study, we performed an integrated analysis of gene expression data and genome-wide methylation data to determine novel prognostic genes and methylation sites in LGGs. Results. To determine genes that differentially expressed between 44 short-term survivors (<2 years) and 48 long-term survivors (≥2 years), we searched LGGs TCGA RNA-seq dataset and identified 106 differentially expressed genes. SERPINA5 and Submitted 11 October 2019 Accepted 9 May 2020 TIMP1 were selected for further study. Kaplan–Meier plots showed that SERPINA5 Published 3 June 2020 and TIMP1 expression were significantly correlated with overall survival (OS) and Corresponding authors relapse-free survival (RFS) in TCGA LGGs patients. -
TIMP1 Polyclonal Antibody Gene Summary: This Gene Belongs to the TIMP Gene Family
TIMP1 polyclonal antibody Gene Summary: This gene belongs to the TIMP gene family. The proteins encoded by this gene family are Catalog Number: PAB19116 natural inhibitors of the matrix metalloproteinases (MMPs), a group of peptidases involved in degradation Regulatory Status: For research use only (RUO) of the extracellular matrix. In addition to its inhibitory role against most of the known MMPs, the encoded protein is Product Description: Rabbit polyclonal antibody raised able to promote cell proliferation in a wide range of cell against synthetic peptide of TIMP1. types, and may also have an anti-apoptotic function. Transcription of this gene is highly inducible in response Immunogen: A synthetic peptide corresponding to to many cytokines and hormones. In addition, the C-terminus of human TIMP1. expression from some but not all inactive X chromosomes suggests that this gene inactivation is Host: Rabbit polymorphic in human females. This gene is located Reactivity: Human within intron 6 of the synapsin I gene and is transcribed in the opposite direction. [provided by RefSeq] Applications: IHC-P, WB-Re (See our web site product page for detailed applications information) Protocols: See our web site at http://www.abnova.com/support/protocols.asp or product page for detailed protocols Form: Lyophilized Purification: Immunoaffinity purification Isotype: IgG Recommend Usage: Western Blot (1 ug/mL) Immunohistochemistry (Formalin/PFA-fixed paraffin-embedded sections) (1 ug/mL) The optimal working dilution should be determined by the end user. Storage Buffer: Lyophilized from 0.9 mg NaCl, 0.2 mg Na2HPO4 (5 mg BSA, 0.05 mg sodium azide, 0.05 mg Thimerosal) Storage Instruction: Store at -20°C on dry atmosphere. -
How to Print a Crystal Structure Model in 3D Teng-Hao Chen,*A Semin Lee, B Amar H
Electronic Supplementary Material (ESI) for CrystEngComm. This journal is © The Royal Society of Chemistry 2014 How to Print a Crystal Structure Model in 3D Teng-Hao Chen,*a Semin Lee, b Amar H. Flood b and Ognjen Š. Miljanić a a Department of Chemistry, University of Houston, 112 Fleming Building, Houston, Texas 77204-5003, United States b Department of Chemistry, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States Supporting Information Instructions for Printing a 3D Model of an Interlocked Molecule: Cyanostars .................................... S2 Instructions for Printing a "Molecular Spinning Top" in 3D: Triazolophanes ..................................... S3 References ....................................................................................................................................................................... S4 S1 Instructions for Printing a 3D Model of an Interlocked Molecule: Cyanostars Mechanically interlocked molecules such as rotaxanes and catenanes can also be easily printed in 3D. As long as the molecule is correctly designed and modeled, there is no need to assemble and glue the components after printing—they are printed inherently as mechanically interlocked molecules. We present the preparation of a cyanostar- based [3]rotaxane as an example. A pair of sandwiched cyanostars S1 (CS ) derived from the crystal structure was "cleaned up" in the molecular computation software Spartan ʹ10, i.e. disordered atoms were removed. A linear molecule was created and threaded through the cavity of two cyanostars (Figure S1a). Using a space filling view of the molecule, the three components were spaced sufficiently far apart to ensure that they did not make direct contact Figure S1 . ( a) Side and top view of two cyanostars ( CS ) with each other when they are printed. threaded with a linear molecule. ( b) Side and top view of a Bulky stoppers were added to each [3]rotaxane. -
Conformational and Chemical Selection by a Trans-Acting Editing
Correction BIOCHEMISTRY Correction for “Conformational and chemical selection by a trans- acting editing domain,” by Eric M. Danhart, Marina Bakhtina, William A. Cantara, Alexandra B. Kuzmishin, Xiao Ma, Brianne L. Sanford, Marija Kosutic, Yuki Goto, Hiroaki Suga, Kotaro Nakanishi, Ronald Micura, Mark P. Foster, and Karin Musier-Forsyth, which was first published August 2, 2017; 10.1073/pnas.1703925114 (Proc Natl Acad Sci USA 114:E6774–E6783). The authors note that Oscar Vargas-Rodriguez should be added to the author list between Brianne L. Sanford and Marija Kosutic. Oscar Vargas-Rodriguez should be credited with de- signing research, performing research, and analyzing data. The corrected author line, affiliation line, and author contributions appear below. The online version has been corrected. The authors note that the following statement should be added to the Acknowledgments: “We thank Daniel McGowan for assistance with preparing mutant proteins.” Eric M. Danharta,b, Marina Bakhtinaa,b, William A. Cantaraa,b, Alexandra B. Kuzmishina,b,XiaoMaa,b, Brianne L. Sanforda,b, Oscar Vargas-Rodrigueza,b, Marija Kosuticc,d,YukiGotoe, Hiroaki Sugae, Kotaro Nakanishia,b, Ronald Micurac,d, Mark P. Fostera,b, and Karin Musier-Forsytha,b aDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210; bCenter for RNA Biology, The Ohio State University, Columbus, OH 43210; cInstitute of Organic Chemistry, Leopold Franzens University, A-6020 Innsbruck, Austria; dCenter for Molecular Biosciences, Leopold Franzens University, A-6020 Innsbruck, Austria; and eDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan Author contributions: E.M.D., M.B., W.A.C., B.L.S., O.V.-R., M.P.F., and K.M.-F.