Knowledge-Graph-Based Drug Repositioning Against COVID-19 by Graph Convolutional Network with Attention Mechanism
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WO 2018/005909 Al 04 January 2018 (04.01.2018) W !P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2018/005909 Al 04 January 2018 (04.01.2018) W !P O PCT (51) International Patent Classification: A61P 31/12 (2006 .01) A61K 31/505 (2006 .0 1) A61K 31/4985 (2006.01) (21) International Application Number: PCT/US20 17/040 175 (22) International Filing Date: 30 June 2017 (30.06.2017) (25) Filing Language: English (26) Publication Language: English (30) Priority Data: 62/357,458 0 1 July 2016 (01 .07.2016) US (71) Applicant: VIIV HEALTHCARE COMPANY [US/US]; 25 1 Little Falls Drive, Wilmington, DE 19808 (US). (72) Inventor: SPREEN, William, R.; 5 Moore Drive, Re search Triangle Park, NC 27709-3398 (US). (74) Agent: HAN, William, T. et al; Glaxosmithkline, Glob al Patents, UW2220, 709 Swedeland Road, P.O. Box 1539, King of Prussia, PA 19406-0939 (US). (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. -
Therapeutic Potential of Nicotinamide Adenine Dinucleotide (NAD) T ∗ Marta Arenas-Jala,B, , J.M
European Journal of Pharmacology 879 (2020) 173158 Contents lists available at ScienceDirect European Journal of Pharmacology journal homepage: www.elsevier.com/locate/ejphar Therapeutic potential of nicotinamide adenine dinucleotide (NAD) T ∗ Marta Arenas-Jala,b, , J.M. Suñé-Negrea, Encarna García-Montoyaa a Pharmacy and Pharmaceutical Technology Department (Faculty of Pharmacy and Food Sciences), University of Barcelona, Barcelona, Spain b ICN2 – Catalan Institute of Nanoscience and Nanotechnology (Autonomous University of Barcelona), Bellaterra (Barcelona), Spain ARTICLE INFO ABSTRACT Keywords: Nicotinamide adenine nucleotide (NAD) is a small ubiquitous hydrophilic cofactor that participates in several NAD aspects of cellular metabolism. As a coenzyme it has an essential role in the regulation of energetic metabolism, Metabolism but it is also a cosubstrate for enzymes that regulate fundamental biological processes such as transcriptional Therapeutic potential regulation, signaling and DNA repairing among others. The fluctuation and oxidative state of NAD levels reg- Drug discovery ulate the activity of these enzymes, which is translated into marked effects on cellular function. While alterations Supplementation in NAD homeostasis are a common feature of different conditions and age-associated diseases, in general, in- creased NAD levels have been associated with beneficial health effects. Due to its therapeutic potential, the interest in this molecule has been renewed, and the regulation of NAD metabolism has become an attractive target for drug discovery. In fact, different approaches to replenish or increase NAD levels have been tested, including enhancement of biosynthesis and inhibition of NAD breakdown. Despite further research is needed, this review provides an overview and update on NAD metabolism, including the therapeutic potential of its regulation, as well as pharmacokinetics, safety, precautions and formulation challenges of NAD supplementa- tion. -
Metabolic-Hydroxy and Carboxy Functionalization of Alkyl Moieties in Drug Molecules: Prediction of Structure Influence and Pharmacologic Activity
molecules Review Metabolic-Hydroxy and Carboxy Functionalization of Alkyl Moieties in Drug Molecules: Prediction of Structure Influence and Pharmacologic Activity Babiker M. El-Haj 1,* and Samrein B.M. Ahmed 2 1 Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, University of Science and Technology of Fujairah, Fufairah 00971, UAE 2 College of Medicine, Sharjah Institute for Medical Research, University of Sharjah, Sharjah 00971, UAE; [email protected] * Correspondence: [email protected] Received: 6 February 2020; Accepted: 7 April 2020; Published: 22 April 2020 Abstract: Alkyl moieties—open chain or cyclic, linear, or branched—are common in drug molecules. The hydrophobicity of alkyl moieties in drug molecules is modified by metabolic hydroxy functionalization via free-radical intermediates to give primary, secondary, or tertiary alcohols depending on the class of the substrate carbon. The hydroxymethyl groups resulting from the functionalization of methyl groups are mostly oxidized further to carboxyl groups to give carboxy metabolites. As observed from the surveyed cases in this review, hydroxy functionalization leads to loss, attenuation, or retention of pharmacologic activity with respect to the parent drug. On the other hand, carboxy functionalization leads to a loss of activity with the exception of only a few cases in which activity is retained. The exceptions are those groups in which the carboxy functionalization occurs at a position distant from a well-defined primary pharmacophore. Some hydroxy metabolites, which are equiactive with their parent drugs, have been developed into ester prodrugs while carboxy metabolites, which are equiactive to their parent drugs, have been developed into drugs as per se. -
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Kan Lu, PharmD New Antiretrovirals for Based on a presentation at prn by Roy M. Gulick, md, mph the Treatment of HIV: Kan Lu, PharmD | Drug Development Fellow University of North Carolina School of Pharmacy Chapel Hill, North Carolina The View in 2006 Roy M. Gulick, md, mph Reprinted from The prn Notebook® | october 2006 | Dr. James F. Braun, Editor-in-Chief Director, Cornell Clinical Trials Unit | Associate Professor of Medicine, Meri D. Pozo, PhD, Managing Editor. Published in New York City by the Physicians’ Research Network, Inc.® Weill Medical College of Cornell University | New York, New York John Graham Brown, Executive Director. For further information and other articles available online, visit http://www.prn.org | All rights reserved. ©october 2006 substantial progress continues to be made in the arena of cokinetics and a long extracellular half-life of approximately 10 hours antiretroviral drug development. prn is again proud to present its annual (Zhu, 2003). During apricitabine’s development, a serious drug interac- review of the experimental agents to watch for in the coming months and tion with lamivudine (Epivir) was noted. Although the plasma years. This year’s review is based on a lecture by Dr. Roy M. Gulick, a long- concentrations of apricitabine were unaffected by coadministration of time friend of prn, and no stranger to the antiretroviral development lamivudine, the intracellular concentrations of apricitabine were reduced pipeline. by approximately sixfold. Additionally, the 50% inhibitory concentration To date, twenty-two antiretrovirals have been approved by the Food (ic50) of apricitabine against hiv with the M184V mutation was increased and Drug Administration (fda) for the treatment of hiv infection. -
Ep 2531027 B1
(19) TZZ ¥_Z _T (11) EP 2 531 027 B1 (12) EUROPEAN PATENT SPECIFICATION (45) Date of publication and mention (51) Int Cl.: of the grant of the patent: A61K 31/4985 (2006.01) A61K 31/52 (2006.01) 06.05.2015 Bulletin 2015/19 A61K 31/536 (2006.01) A61K 31/513 (2006.01) A61K 38/55 (2006.01) A61P 31/18 (2006.01) (21) Application number: 11737484.3 (86) International application number: (22) Date of filing: 24.01.2011 PCT/US2011/022219 (87) International publication number: WO 2011/094150 (04.08.2011 Gazette 2011/31) (54) Therapeutic combination comprising dolutegravir, abacavir and lamivudine Therapeutische Zusammensetzung enthaltend Dolutegravir, Abacavir und Lamivudine Combinaison thérapeutique comprenant du dolutégravir, de l’abacavir et de la lamivudine (84) Designated Contracting States: (74) Representative: Gladwin, Amanda Rachel AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GlaxoSmithKline GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO Global Patents (CN925.1) PL PT RO RS SE SI SK SM TR 980 Great West Road Designated Extension States: Brentford, Middlesex TW8 9GS (GB) BA ME (56) References cited: (30) Priority: 27.01.2010 US 298589 P WO-A1-2010/011812 WO-A2-2009/148600 US-A1- 2006 084 627 US-A1- 2006 084 627 (43) Date of publication of application: US-A1- 2008 076 738 US-A1- 2009 318 421 12.12.2012 Bulletin 2012/50 US-A1- 2009 318 421 US-B1- 6 544 961 (73) Proprietor: VIIV Healthcare Company • SONG1 et al: "The Effect of Ritonavir-Boosted Research Triangle Park, NC 27709 (US) ProteaseInhibitors on the HIV Integrase Inhibitor, S/GSK1349572,in Healthy Subjects", INTERNET , (72) Inventor: UNDERWOOD, Mark, Richard 15 September 2009 (2009-09-15), XP002697436, Research Triangle Park Retrieved from the Internet: URL:http: North Carolina 27709 (US) //www.natap.org/2009/ICCAC/ICCAC_ 52.htm [retrieved on 2013-05-21] Note: Within nine months of the publication of the mention of the grant of the European patent in the European Patent Bulletin, any person may give notice to the European Patent Office of opposition to that patent, in accordance with the Implementing Regulations. -
PHARMACEUTICAL APPENDIX to the TARIFF SCHEDULE 2 Table 1
Harmonized Tariff Schedule of the United States (2020) Revision 19 Annotated for Statistical Reporting Purposes PHARMACEUTICAL APPENDIX TO THE HARMONIZED TARIFF SCHEDULE Harmonized Tariff Schedule of the United States (2020) Revision 19 Annotated for Statistical Reporting Purposes PHARMACEUTICAL APPENDIX TO THE TARIFF SCHEDULE 2 Table 1. This table enumerates products described by International Non-proprietary Names INN which shall be entered free of duty under general note 13 to the tariff schedule. The Chemical Abstracts Service CAS registry numbers also set forth in this table are included to assist in the identification of the products concerned. For purposes of the tariff schedule, any references to a product enumerated in this table includes such product by whatever name known. -
Drugbank 3.0: a Comprehensive Resource for 'Omics' Research On
Published online 8 November 2010 Nucleic Acids Research, 2011, Vol. 39, Database issue D1035–D1041 doi:10.1093/nar/gkq1126 DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs Craig Knox1, Vivian Law2, Timothy Jewison1, Philip Liu3, Son Ly2, Alex Frolkis1, Allison Pon1, Kelly Banco2, Christine Mak2, Vanessa Neveu1, Yannick Djoumbou3, Roman Eisner1, An Chi Guo1 and David S. Wishart1,2,3,4,* 1Department of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8, 2Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada T6G 2N8, 3Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8 and 4National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, AB, Canada T6G 2M9 Received September 15, 2010; Revised October 20, 2010; Accepted October 21, 2010 ABSTRACT drug target, drug description and drug action data. DrugBank (http://www.drugbank.ca) is a richly DrugBank 3.0 represents the result of 2 years annotated database of drug and drug target infor- of manual annotation work aimed at making mation. It contains extensive data on the nomencla- the database much more useful for a wide ture, ontology, chemistry, structure, function, range of ‘omics’ (i.e. pharmacogenomic, action, pharmacology, pharmacokinetics, metabol- pharmacoproteomic, pharmacometabolomic and ism and pharmaceutical properties of both small even pharmacoeconomic) applications. molecule and large molecule (biotech) drugs. It also contains comprehensive information on the INTRODUCTION target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, Historically most of the known information on drugs, DrugBank has become widely used by pharmacists, drug targets and drug action has resided in books, medicinal chemists, pharmaceutical researchers, journals and expensive commercial databases. -
Smart Drugs: a Review
International Journal for Innovation Education and Research www.ijier.net Vol:-8 No-11, 2020 Smart Drugs: A Review Sahjesh Soni, Dr Rashmi Srivastava, Ayush Bhandari Mumbai Educational Trust, India Abstracts Smart drugs can change the way our mind functions. Smart drugs are also known as nootropics, which literally means the ability to bend or shape our mind. Smart drugs are classified into two main categories. They are classified based on their pharmacological action and their availability. The stimulant category of drugs is highly used and misused. There has been a rampant increase in the sale of smart drugs, which could be attributed to the rise in competition all over the world. Two major criteria for selecting a good drug are its mechanism of action and bioavailability. Owing to the short-term benefits of smart drugs, many countries have openly accepted this concept. There is still no concrete scientific evidence backing the safety and efficacy of these drugs. Some believe that this is just a fad that will soon pass, while others believe that this is something that will revolutionize our future. Key Words: Smart drugs, Nootropics, Cognitive enhancers, Stimulants, Uses and Side effects. What are Smart Drugs? "Smart drugs" are a group of compounds that can promote brain performance. They have got a lot of attention due to our stressful lifestyle, and these drugs help to boost our memory, focus, creativity, intelligence, and motivation. The origin of the word comes from the Greek language meaning “to bend or shape the mind”.1 These chemicals have many mechanisms of action. -
Drug Knowledge Bases and Their Applications in Biomedical Informatics Research Yongjun Zhu, Olivier Elemento, Jyotishman Pathak and Fei Wang
Briefings in Bioinformatics, 2018, 1–14 doi: 10.1093/bib/bbx169 Paper Drug knowledge bases and their applications in biomedical informatics research Yongjun Zhu, Olivier Elemento, Jyotishman Pathak and Fei Wang Corresponding author: Fei Wang, Division of Health Informatics, Department of Healthcare Policy and Research at Weill Cornell Medicine at Cornell University, 425 East 61st Street, Suite 301, DV-308, New York, NY 10065, USA. E-mail: [email protected] Abstract Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many drug knowledge bases have been constructed. They range from simple ones with specific focuses to comprehensive ones that contain information on almost every aspect of a drug. These curated drug knowledge bases have made significant contributions to the development of efficient and effective health information technologies for better health-care service delivery. Understanding and comparing existing drug knowledge bases and how they are applied in various biomedical studies will help us recognize the state of the art and design better knowledge bases in the future. In addition, researchers can get insights on novel applications of the drug knowledge bases through a review of successful use cases. In this study, we provide a review of existing popular drug knowledge bases and their applications in drug-related studies. We discuss challenges in constructing and using drug knowledge bases as well as future research directions toward a better ecosystem of drug knowledge bases. -
Computational Drug Repurposing Algorithm Targeting TRPA1 Calcium Channel As a Potential Therapeutic Solution for Multiple Sclerosis
Supplementary Materials: Computational Drug Repurposing Algorithm Targeting TRPA1 Calcium Channel as a Potential Therapeutic Solution for Multiple Sclerosis Dragos Paul Mihai, George Mihai Nitulescu *, George Nicolae Daniel Ion, Cosmin Ionut Ciotu, Cornel Chirita, and Simona Negres Table S1. Descriptive statistics for pIC50 and druglikeness-related descriptors for the TRPA1 inhibitors set. Descriptor Range Minimum Maximum Mean ± SD pIC50 (M) 4.48 4.52 9.00 6.57 ± 1.01 ALogP 8.28 −0.71 7.57 4.02 ± 1.34 Molecular weight 482.03 175.10 657.13 389.70 ± 101.73 Polar surface area 193.59 17.82 211.41 82.80 ± 40.83 Rotatable bonds 12 1 13 5.01 ± 2.08 Hydrogen bonds acceptors 8 0 8 2.92 ± 1.46 Hydrogen bonds donors 3 0 3 1.06 ± 0.54 SD – standard deviation. Figure S1. Diagram of similarity/activity cliffs based on flexophores with 80% similarity within TRPA1 inhibitors. Larger dots indicate the presence of an activity cliff. Figure S2. Representative structures for similarity/activity cliffs analysis of TRPA1 inhibitors. Table S2. Highest similarity pairs between TRPA1 inhibitors and screened drugs based on flexophore descriptors data mining procedure. TRPA1 inhibitors Repurposing dataset Entry Similarity (ChEMBL ID) (DrugBank ID) 1 CHEMBL3298238 DB08135 0.9832 2 CHEMBL3220230 DB08561 0.9696 3 CHEMBL3220228 DB08561 0.9614 4 CHEMBL593902 DB07311 0.9553 5 CHEMBL3297780 DB01065 0.9533 6 CHEMBL3220448 DB08561 0.9509 Figure S3. Diagram of similarity/activity cliffs based on flexophores with 80% similarity threshold for merged TRPA1 inhibitors dataset (colored dots) and similar DrugBank entries (grey dots). Table S3. -
GSK and Vertex Pharmaceuticals Announce Presentation of Data Supporting Development of Investigational HIV Protease Inhibitor Brecanavir
December 16, 2005 GSK and Vertex Pharmaceuticals Announce Presentation of Data Supporting Development of Investigational HIV Protease Inhibitor Brecanavir - Positive Data Presented at 45th Annual ICAAC - Cambridge, MA, December 16, 2005 - GlaxoSmithKline (GSK) and Vertex Pharmaceuticals Incorporated (Nasdaq: VRTX) presented positive results today from a study evaluating the safety, tolerability and antiviral activity of the investigational HIV-1 protease inhibitor (PI), brecanavir* (formerly known as GW640385 or VX-385)1. These data were presented at the 45th Interscience Conference on Antimicrobial Agents and Chemotherapy (ICAAC) held in Washington DC. Interim findings following 24 weeks of dosing demonstrated potent antiviral activity for brecanavir in both PI-sensitive and PI-resistant HIV-infected adults. "These results support the ongoing development program for brecanavir, which is anticipated to enter Phase III development in 2006," said Lynn Marks, MD, Senior Vice President of the Infectious Disease Medicines Development Centre at GSK. "If approved, brecanavir may be useful in treating patients infected with strains of HIV that have become resistant to multiple protease inhibitors, and its clinical advancement underscores GSK's commitment to developing new anti-HIV drugs." Clinical Data on Brecanavir Brecanavir is an HIV protease inhibitor in Phase IIb clinical development. Brecanavir has received fast track designation from the U.S. Food and Drug Administration and is being developed by GSK as part of a collaboration with Vertex Pharmaceuticals. Data presented were from a planned, 24-week analysis of an open-label study (HPR10006) of 48 weeks' duration evaluating the safety, tolerability, antiviral activity and pharmacokinetics of ritonavir-boosted brecanavir. Thirty-one HIV-1 infected adults received 300mg of brecanavir twice-daily boosted with 100mg of ritonavir in combination with two nucleoside reverse transcriptase inhibitors based on patient medical history and viral genotype. -
Package 'Dbparser'
Package ‘dbparser’ August 26, 2020 Title 'DrugBank' Database XML Parser Version 1.2.0 Description This tool is for parsing the 'DrugBank' XML database <https://www.drugbank.ca/>. The parsed data are then returned in a proper 'R' dataframe with the ability to save them in a given database. License MIT + file LICENSE Encoding UTF-8 LazyData true Imports DBI, dplyr, odbc, progress, purrr, readr, RMariaDB, RSQLite, tibble, tools, XML RoxygenNote 7.1.0 Suggests knitr, rmarkdown, testthat VignetteBuilder knitr URL https://docs.ropensci.org/dbparser/, https://github.com/ropensci/dbparser/ BugReports https://github.com/ropensci/dbparser/issues Depends R (>= 2.10) NeedsCompilation no Author Mohammed Ali [aut, cre], Ali Ezzat [aut], Hao Zhu [rev], Emma Mendelsohn [rev] Maintainer Mohammed Ali <[email protected]> Repository CRAN Date/Publication 2020-08-26 12:10:03 UTC 1 2 R topics documented: R topics documented: articles . .3 attachments . .5 books . .8 cett.............................................. 10 cett_actions_doc . 12 cett_doc . 14 cett_ex_identity_doc . 17 cett_go_doc . 19 cett_poly_doc . 21 cett_poly_pfms_doc . 24 cett_poly_syn_doc . 26 dbparser . 28 drugs . 29 drug_affected_organisms . 31 drug_ahfs_codes . 33 drug_atc_codes . 35 drug_calc_prop . 36 drug_categories . 38 drug_classification . 40 drug_dosages . 42 drug_element . 44 drug_element_options . 46 drug_exp_prop . 47 drug_external_links . 49 drug_ex_identity . 51 drug_food_interactions . 53 drug_general_information . 54 drug_groups . 57 drug_interactions . 58 drug_intern_brand