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Oprea TI, Bologa C, Holmes J, Mathias S, Metzger VT, Waller A, Yang JJ, Leach AR, Jensen LJ, Kelleher KJ, Sheils TK, Mathé E, Avram S, Edwards JS. Overview of the Knowledge Management Center for Illuminating the Druggable Genome. Drug Discov Today 2024; 29:103882. [PMID: 38218214 PMCID: PMC10939799 DOI: 10.1016/j.drudis.2024.103882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 12/22/2023] [Accepted: 01/09/2024] [Indexed: 01/15/2024]
Abstract
The Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) project aims to aggregate, update, and articulate protein-centric data knowledge for the entire human proteome, with emphasis on the understudied proteins from the three IDG protein families. KMC collates and analyzes data from over 70 resources to compile the Target Central Resource Database (TCRD), which is the web-based informatics platform (Pharos). These data include experimental, computational, and text-mined information on protein structures, compound interactions, and disease and phenotype associations. Based on this knowledge, proteins are classified into different Target Development Levels (TDLs) for identification of understudied targets. Additional work by the KMC focuses on enriching target knowledge and producing DrugCentral and other data visualization tools for expanding investigation of understudied targets.
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Affiliation(s)
- Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Cristian Bologa
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Jayme Holmes
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Stephen Mathias
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Vincent T Metzger
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Anna Waller
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Jeremy J Yang
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Keith J Kelleher
- National Center for Advancing Translational Sciences (NCATS), NIH, Bethesda, MD, USA
| | - Timothy K Sheils
- National Center for Advancing Translational Sciences (NCATS), NIH, Bethesda, MD, USA
| | - Ewy Mathé
- National Center for Advancing Translational Sciences (NCATS), NIH, Bethesda, MD, USA
| | - Sorin Avram
- Coriolan Dragulescu Institute of Chemistry, Timisoara, Romania
| | - Jeremy S Edwards
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, USA; Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, NM, USA.
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2
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Thakur M, Buniello A, Brooksbank C, Gurwitz KT, Hall M, Hartley M, Hulcoop DG, Leach AR, Marques D, Martin M, Mithani A, McDonagh EM, Mutasa-Gottgens E, Ochoa D, Perez-Riverol Y, Stephenson J, Varadi M, Velankar S, Vizcaino JA, Witham R, McEntyre J. EMBL's European Bioinformatics Institute (EMBL-EBI) in 2023. Nucleic Acids Res 2024; 52:D10-D17. [PMID: 38015445 PMCID: PMC10767983 DOI: 10.1093/nar/gkad1088] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/23/2023] [Accepted: 10/30/2023] [Indexed: 11/29/2023] Open
Abstract
The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the latest developments in the services provided by EMBL-EBI data resources to scientific communities globally. These developments aim to ensure EMBL-EBI resources meet the current and future needs of these scientific communities, accelerating the impact of open biological data for all.
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Affiliation(s)
- Matthew Thakur
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Annalisa Buniello
- Open Targets, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Catherine Brooksbank
- Training Team, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Kim T Gurwitz
- Training Team, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Matthew Hall
- Industry Partnerships, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Matthew Hartley
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - David G Hulcoop
- Open Targets, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Andrew R Leach
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
- Industry Partnerships, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Diana Marques
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Maria Martin
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Aziz Mithani
- Training Team, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Ellen M McDonagh
- Open Targets, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Euphemia Mutasa-Gottgens
- Industry Partnerships, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - David Ochoa
- Open Targets, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Yasset Perez-Riverol
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - James Stephenson
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Mihaly Varadi
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Sameer Velankar
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Juan Antonio Vizcaino
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Rick Witham
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Johanna McEntyre
- Data Services Teams, EMBL’s European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK
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3
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Bosc N, Felix E, Gardner JMF, Mills J, Timmerman M, Asveld D, Rensen K, Mukherjee P, Das R, Chenu E, Besson D, Burrows JN, Duffy J, Laleu B, Guantai EM, Leach AR. MAIP: An Open-Source Tool to Enrich High-Throughput Screening Output and Identify Novel, Druglike Molecules with Antimalarial Activity. ACS Med Chem Lett 2023; 14:1733-1741. [PMID: 38116432 PMCID: PMC10726451 DOI: 10.1021/acsmedchemlett.3c00369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/30/2023] [Accepted: 11/06/2023] [Indexed: 12/21/2023] Open
Abstract
Efforts to tackle malaria must continue for a disease that threatens half of the global population. Parasite resistance to current therapies requires new chemotypes that are able to demonstrate effectiveness and safety. Previously, we developed a machine-learning-based approach to predict compound antimalarial activity, which was trained on the compound collections of several organizations. The resulting prediction platform, MAIP, was made freely available to the scientific community and offers a solution to prioritize molecules of interest in virtual screening and hit-to-lead optimization. Here, we experimentally validate MAIP and demonstrate how the approach was used in combination with a robust compound selection workflow and a recently introduced innovative high-throughput screening (HTS) cascade to select and purchase compounds from a public library for subsequent experimental screening. We observed a 12-fold enrichment compared with a randomly selected set of molecules, and the eight hits we ultimately selected exhibit good potency and absorption, distribution, metabolism, and excretion (ADME) profiles.
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Affiliation(s)
- Nicolas Bosc
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Eloy Felix
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - J. Mark F. Gardner
- AMG
Consultants Ltd, Discovery
Park House, Discovery Park, Sandwich, Kent CT13 9ND, United Kingdom
| | - James Mills
- Sandexis
Medicinal Chemistry Ltd, Innovation House, Discovery Park, Sandwich, Kent CT13 9FF, United Kingdom
| | - Martijn Timmerman
- Pivot
Park Screening Centre, Pivot Park (Frederick Banting Building), Kloosterstraat 9, 5349 AB Oss, The Netherlands
| | - Dennis Asveld
- Pivot
Park Screening Centre, Pivot Park (Frederick Banting Building), Kloosterstraat 9, 5349 AB Oss, The Netherlands
| | - Kim Rensen
- Pivot
Park Screening Centre, Pivot Park (Frederick Banting Building), Kloosterstraat 9, 5349 AB Oss, The Netherlands
| | - Partha Mukherjee
- TCG
Life Sciences, Bengal Intelligent Park Limited, Block EP & GP, Salt Lake Electronics
Complex, Sector V, Kolkata, West Bengal 700091, India
| | - Rishi Das
- TCG
Life Sciences, Bengal Intelligent Park Limited, Block EP & GP, Salt Lake Electronics
Complex, Sector V, Kolkata, West Bengal 700091, India
| | - Elodie Chenu
- Medicines
for Malaria Ventures, 1215 Geneva, Switzerland
| | | | | | - James Duffy
- Medicines
for Malaria Ventures, 1215 Geneva, Switzerland
| | - Benoît Laleu
- Medicines
for Malaria Ventures, 1215 Geneva, Switzerland
| | - Eric M. Guantai
- Department
of Pharmacy, Faculty of Health Sciences, University of Nairobi, 00202 Nairobi, Kenya
| | - Andrew R. Leach
- European
Molecular Biology Laboratory, European Bioinformatics
Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
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4
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Leach AR, Ondrus AE. Editorial overview: Restructuring drug design and development. Curr Opin Struct Biol 2023; 83:102727. [PMID: 37944397 DOI: 10.1016/j.sbi.2023.102727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Affiliation(s)
- Andrew R Leach
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.
| | - Alison E Ondrus
- Departments of Chemistry and Pharmaceutical Sciences, University of Illinois Chicago, Chicago, Illinois, USA.
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5
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West CE, Karim M, Falaguera MJ, Speidel L, Green CJ, Logie L, Schwartzentruber J, Ochoa D, Lord JM, Ferguson MAJ, Bountra C, Wilkinson GF, Vaughan B, Leach AR, Dunham I, Marsden BD. Integrative GWAS and co-localisation analysis suggests novel genes associated with age-related multimorbidity. Sci Data 2023; 10:655. [PMID: 37749083 PMCID: PMC10520009 DOI: 10.1038/s41597-023-02513-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/22/2023] [Indexed: 09/27/2023] Open
Abstract
Advancing age is the greatest risk factor for developing multiple age-related diseases. Therapeutic approaches targeting the underlying pathways of ageing, rather than individual diseases, may be an effective way to treat and prevent age-related morbidity while reducing the burden of polypharmacy. We harness the Open Targets Genetics Portal to perform a systematic analysis of nearly 1,400 genome-wide association studies (GWAS) mapped to 34 age-related diseases and traits, identifying genetic signals that are shared between two or more of these traits. Using locus-to-gene (L2G) mapping, we identify 995 targets with shared genetic links to age-related diseases and traits, which are enriched in mechanisms of ageing and include known ageing and longevity-related genes. Of these 995 genes, 128 are the target of an approved or investigational drug, 526 have experimental evidence of binding pockets or are predicted to be tractable, and 341 have no existing tractability evidence, representing underexplored genes which may reveal novel biological insights and therapeutic opportunities. We present these candidate targets for exploration and prioritisation in a web application.
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Affiliation(s)
- Clare E West
- Centre for Medicines Discovery, University of Oxford, Oxford, UK.
- Open Targets, Wellcome Genome Campus, Hinxton, UK.
| | - Mohd Karim
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Maria J Falaguera
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Leo Speidel
- Francis Crick Institute, London, UK
- Genetics Institute, University College London, London, UK
| | | | - Lisa Logie
- Drug Discovery Unit, University of Dundee, Dundee, UK
- Medicines Discovery Catapult, 35 Mereside Alderley Park, Macclesfield, Cheshire, UK
| | - Jeremy Schwartzentruber
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - David Ochoa
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Janet M Lord
- MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | | | - Chas Bountra
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | - Graeme F Wilkinson
- Medicines Discovery Catapult, 35 Mereside Alderley Park, Macclesfield, Cheshire, UK
| | - Beverley Vaughan
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
| | - Andrew R Leach
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Ian Dunham
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Brian D Marsden
- Centre for Medicines Discovery, University of Oxford, Oxford, UK
- Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
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6
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Sanz F, Pognan F, Steger-Hartmann T, Díaz C, Asakura S, Amberg A, Bécourt-Lhote N, Blomberg N, Bosc N, Briggs K, Bringezu F, Brulle-Wohlhueter C, Brunak S, Bueters R, Callegaro G, Capella-Gutierrez S, Centeno E, Corvi J, Cronin MTD, Drew P, Duchateau-Nguyen G, Ecker GF, Escher S, Felix E, Ferreiro M, Frericks M, Furlong LI, Geiger R, George C, Grandits M, Ivanov-Draganov D, Kilgour-Christie J, Kiziloren T, Kors JA, Koyama N, Kreuchwig A, Leach AR, Mayer MA, Monecke P, Muster W, Nakazawa CM, Nicholson G, Parry R, Pastor M, Piñero J, Oberhauser N, Ramírez-Anguita JM, Rodrigo A, Smajic A, Schaefer M, Schieferdecker S, Soininen I, Terricabras E, Trairatphisan P, Turner SC, Valencia A, van de Water B, van der Lei JL, van Mulligen EM, Vock E, Wilkinson D. eTRANSAFE: data science to empower translational safety assessment. Nat Rev Drug Discov 2023; 22:605-606. [PMID: 37316648 DOI: 10.1038/d41573-023-00099-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
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7
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Rasooly D, Peloso GM, Pereira AC, Dashti H, Giambartolomei C, Wheeler E, Aung N, Ferolito BR, Pietzner M, Farber-Eger EH, Wells QS, Kosik NM, Gaziano L, Posner DC, Bento AP, Hui Q, Liu C, Aragam K, Wang Z, Charest B, Huffman JE, Wilson PWF, Phillips LS, Whittaker J, Munroe PB, Petersen SE, Cho K, Leach AR, Magariños MP, Gaziano JM, Langenberg C, Sun YV, Joseph J, Casas JP. Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure. Nat Commun 2023; 14:3826. [PMID: 37429843 PMCID: PMC10333277 DOI: 10.1038/s41467-023-39253-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 06/05/2023] [Indexed: 07/12/2023] Open
Abstract
We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.
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Affiliation(s)
- Danielle Rasooly
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02130, USA.
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA.
| | - Gina M Peloso
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave Crosstown Centre, Boston, MA, 02118, USA
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, Av Dr Eneas de Carvalho Aguiar 54, São Paulo, 5403000, Brazil
- Genetics Department, Harvard Medical School, Harvard University, 77 Avenue Louis Pasteur, Boston, MA, 02115, USA
| | - Hesam Dashti
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02130, USA
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA, 02142, USA
| | - Claudia Giambartolomei
- Health Data Science Centre, Human Technopole, V.le Rita Levi-Montalcini, 1, Milan, 20157, Italy
- Central RNA Lab, Non-coding RNAs and RNA-based Therapeutics, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Addenbrookes Hospital, IMS, Box 285, Cambridge, CB2 0QQ, UK
| | - Nay Aung
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Brian R Ferolito
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Addenbrookes Hospital, IMS, Box 285, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Kapelle Ufer 2, Berlin, 10117, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Eric H Farber-Eger
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quinn Stanton Wells
- Vanderbilt University Med. Ctr., Departments of Medicine (Cardiology), Biomedical Informatics, and Pharmacology, Nashville, TN, USA
| | - Nicole M Kosik
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Liam Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - A Patrícia Bento
- Department of Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd NE, Atlanta, GA, 30322, USA
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
| | - Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd NE, Atlanta, GA, 30322, USA
| | - Krishna Aragam
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
- Broad Institute of MIT and Harvard, 415 Main St., Cambridge, MA, 02142, USA
- Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Zeyuan Wang
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd NE, Atlanta, GA, 30322, USA
| | - Brian Charest
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Peter W F Wilson
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, 1639 Pierce Dr NE, Atlanta, GA, 30322, USA
| | - Lawrence S Phillips
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
- Division of Endocrinology, Emory University, 101 Woodruff Circle, WMRB 1027, Atlanta, GA, 30322, USA
| | - John Whittaker
- MRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, United Kingdom
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- National Institute for Health Research, Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Steffen E Petersen
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 68Q, UK
| | - Kelly Cho
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02130, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Andrew R Leach
- Department of Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - María Paula Magariños
- Department of Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - John Michael Gaziano
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02130, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Addenbrookes Hospital, IMS, Box 285, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Kapelle Ufer 2, Berlin, 10117, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd NE, Atlanta, GA, 30322, USA
- Atlanta VA Health Care System, 1670 Clairmont Road, Decatur, GA, 30033, USA
- Department of Biomedical Informatics, Emory University School of Medicine, 1639 Pierce Dr NE, Atlanta, GA, 30332, USA
| | - Jacob Joseph
- Cardiology Section, VA Providence Healthcare System, 830 Chalkstone Avenue, Providence, RI, 02908, USA.
- Department of Medicine, Warren Alpert Medical School of Brown University, 222 Richmond Street, Providence, RI, 02903, USA.
| | - Juan P Casas
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02130, USA
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 150. S. Huntington Ave, Boston, MA, 02130, USA
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8
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Magariños MP, Gaulton A, Félix E, Kiziloren T, Arcila R, Oprea TI, Leach AR. Illuminating the druggable genome through patent bioactivity data. PeerJ 2023; 11:e15153. [PMID: 37151295 PMCID: PMC10162037 DOI: 10.7717/peerj.15153] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 03/10/2023] [Indexed: 05/09/2023] Open
Abstract
The patent literature is a potentially valuable source of bioactivity data. In this article we describe a process to prioritise 3.7 million life science relevant patents obtained from the SureChEMBL database (https://www.surechembl.org/), according to how likely they were to contain bioactivity data for potent small molecules on less-studied targets, based on the classification developed by the Illuminating the Druggable Genome (IDG) project. The overall goal was to select a smaller number of patents that could be manually curated and incorporated into the ChEMBL database. Using relatively simple annotation and filtering pipelines, we have been able to identify a substantial number of patents containing quantitative bioactivity data for understudied targets that had not previously been reported in the peer-reviewed medicinal chemistry literature. We quantify the added value of such methods in terms of the numbers of targets that are so identified, and provide some specific illustrative examples. Our work underlines the potential value in searching the patent corpus in addition to the more traditional peer-reviewed literature. The small molecules found in these patents, together with their measured activity against the targets, are now accessible via the ChEMBL database.
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Affiliation(s)
| | - Anna Gaulton
- EMBL-EBI, Hinxton, United Kingdom
- Exscientia, Oxford, United Kingdom
| | | | | | | | - Tudor I. Oprea
- Translational informatics Division, Department of Internal Medicine, School of Medicine, University of New Mexico, Albuquerque, United States
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9
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Müller S, Ackloo S, Al Chawaf A, Al-Lazikani B, Antolin A, Baell JB, Beck H, Beedie S, Betz UAK, Bezerra GA, Brennan PE, Brown D, Brown PJ, Bullock AN, Carter AJ, Chaikuad A, Chaineau M, Ciulli A, Collins I, Dreher J, Drewry D, Edfeldt K, Edwards AM, Egner U, Frye SV, Fuchs SM, Hall MD, Hartung IV, Hillisch A, Hitchcock SH, Homan E, Kannan N, Kiefer JR, Knapp S, Kostic M, Kubicek S, Leach AR, Lindemann S, Marsden BD, Matsui H, Meier JL, Merk D, Michel M, Morgan MR, Mueller-Fahrnow A, Owen DR, Perry BG, Rosenberg SH, Saikatendu KS, Schapira M, Scholten C, Sharma S, Simeonov A, Sundström M, Superti-Furga G, Todd MH, Tredup C, Vedadi M, von Delft F, Willson TM, Winter GE, Workman P, Arrowsmith CH. Target 2035 - update on the quest for a probe for every protein. RSC Med Chem 2022; 13:13-21. [PMID: 35211674 PMCID: PMC8792830 DOI: 10.1039/d1md00228g] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/21/2021] [Indexed: 01/11/2023] Open
Abstract
Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. The challenge of translating the wealth of new knowledge from genomics into new medicines is that proteins, and not genes, are the primary executers of biological function. Therefore, much of how biology works in health and disease must be understood through the lens of protein function. Accordingly, a subset of human proteins has been at the heart of research interests of scientists over the centuries, and we have accumulated varying degrees of knowledge about approximately 65% of the human proteome. Nevertheless, a large proportion of proteins in the human proteome (∼35%) remains uncharacterized, and less than 5% of the human proteome has been successfully targeted for drug discovery. This highlights the profound disconnect between our abilities to obtain genetic information and subsequent development of effective medicines. Target 2035 is an international federation of biomedical scientists from the public and private sectors, which aims to address this gap by developing and applying new technologies to create by year 2035 chemogenomic libraries, chemical probes, and/or biological probes for the entire human proteome.
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Affiliation(s)
- Susanne Müller
- Institute of Pharmaceutical Chemistry, Goethe University Frankfurt Frankfurt 60438 Germany
- Structural Genomics Consortium, BMLS, Goethe University Frankfurt Frankfurt 60438 Germany
| | - Suzanne Ackloo
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
| | | | - Bissan Al-Lazikani
- Department of Data Science, The Institute of Cancer Research London SM2 5NG UK
- CRUK ICR/Imperial Convergence Science Centre London SM2 5NG UK
| | - Albert Antolin
- Department of Data Science, The Institute of Cancer Research London SM2 5NG UK
- Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research London SM2 5NG UK
| | - Jonathan B Baell
- Monash Institute of Pharmaceutical Sciences, Monash University Parkville Victoria 3052 Australia
- School of Pharmaceutical Sciences, Nanjing Tech University No. 30 South Puzhu Road Nanjing 211816 People's Republic of China
| | - Hartmut Beck
- Research and Development, Bayer AG, Pharmaceuticals 42103 Wuppertal Germany
| | - Shaunna Beedie
- Centre for Medicines Discovery, University of Oxford Old Road Campus Research Building, Roosevelt Drive Oxford OX3 7DQ UK
| | | | - Gustavo Arruda Bezerra
- Centre for Medicines Discovery, University of Oxford Old Road Campus Research Building, Roosevelt Drive Oxford OX3 7DQ UK
| | - Paul E Brennan
- Alzheimer's Research UK Oxford Drug Discovery Institute, Centre for Medicines Discovery, University of Oxford Oxford OX3 7FZ UK
| | - David Brown
- Institut Recherches de Servier 125 Chemin de Ronde 78290 Croissy France
| | - Peter J Brown
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
| | - Alex N Bullock
- Centre for Medicines Discovery, University of Oxford Old Road Campus Research Building, Roosevelt Drive Oxford OX3 7DQ UK
| | - Adrian J Carter
- Discovery Research, Boehringer Ingelheim 55216 Ingelheim am Rhein Germany
| | - Apirat Chaikuad
- Institute of Pharmaceutical Chemistry, Goethe University Frankfurt Frankfurt 60438 Germany
- Structural Genomics Consortium, BMLS, Goethe University Frankfurt Frankfurt 60438 Germany
| | - Mathilde Chaineau
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital, McGill University Montreal QC Canada
| | - Alessio Ciulli
- School of Life Sciences, Division of Biological Chemistry and Drug Discovery, University of Dundee James Black Centre Dundee UK
| | - Ian Collins
- Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research London SM2 5NG UK
| | - Jan Dreher
- Research and Development, Bayer AG, Pharmaceuticals 42103 Wuppertal Germany
| | - David Drewry
- Structural Genomics Consortium, UNC Eshelman School of Pharmacy Chapel Hill NC USA
- Lineberger Comprehensive Cancer Center, Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | - Kristina Edfeldt
- Structural Genomics Consortium, Department of Medicine, Karolinska University Hospital and Karolinska Institutet Stockholm Sweden
| | - Aled M Edwards
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
| | - Ursula Egner
- Nuvisan Innovation Campus Berlin GmbH Müllerstraße 178 13353 Berlin Germany
| | - Stephen V Frye
- Lineberger Comprehensive Cancer Center, Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
- Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | | | - Matthew D Hall
- National Center for Advancing Translational Sciences, National Institutes of Health Rockville Maryland 20850 USA
| | - Ingo V Hartung
- Medicinal Chemistry, Global R&D, Merck Healthcare KGaA Frankfurter Straße 250 64293 Darmstadt Germany
| | - Alexander Hillisch
- Research and Development, Bayer AG, Pharmaceuticals 42103 Wuppertal Germany
| | | | - Evert Homan
- Science for Life Laboratory, Department of Oncology-Pathology Karolinska Institutet Stockholm Sweden
| | - Natarajan Kannan
- Institute of Bioinformatics and Department of Biochemistry and Molecular Biology, University of Georgia Athens GA USA
| | - James R Kiefer
- Genentech, Inc. 1 DNA Way South San Francisco California 94080 USA
| | - Stefan Knapp
- Institute of Pharmaceutical Chemistry, Goethe University Frankfurt Frankfurt 60438 Germany
- Structural Genomics Consortium, BMLS, Goethe University Frankfurt Frankfurt 60438 Germany
| | - Milka Kostic
- Department of Cancer Biology and Chemical Biology Program, Dana-Farber Cancer Institute 450 Brookline Ave Boston MA 02215 USA
| | - Stefan Kubicek
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute Wellcome Genome Campus, Hinxton Cambridgeshire CB10 1SD UK
| | - Sven Lindemann
- Strategic Innovation, Global R&D, Merck Healthcare KGaA Frankfurter Straße 250 64293 Darmstadt Germany
| | - Brian D Marsden
- Centre for Medicines Discovery, University of Oxford Old Road Campus Research Building, Roosevelt Drive Oxford OX3 7DQ UK
- Kennedy Institute of Rheumatology, NDORMS, University of Oxford UK
| | - Hisanori Matsui
- Neuroscience Drug Discovery Unit, Research, Takeda Pharmaceutical Company Limited Fujisawa Kanagawa Japan
| | - Jordan L Meier
- Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health Frederick MD USA
| | - Daniel Merk
- Institute of Pharmaceutical Chemistry, Goethe University Frankfurt Frankfurt 60438 Germany
- LMU Munich, Department of Pharmacy, Chair of Pharmaceutical and Medicinal Chemistry 81377 Munich Germany
| | - Maurice Michel
- Science for Life Laboratory, Department of Oncology-Pathology Karolinska Institutet Stockholm Sweden
| | - Maxwell R Morgan
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
| | | | - Dafydd R Owen
- Discovery Network Group, Pfizer Medicine Design Cambridge MA 02139 USA
| | - Benjamin G Perry
- Drugs for Neglected Diseases initiative 15 Chemin Camille Vidart Geneva 1202 Switzerland
| | | | - Kumar Singh Saikatendu
- Global Research Externalization, Takeda California, Inc. 9625 Towne Center Drive San Diego CA 92121 USA
| | - Matthieu Schapira
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
- Department of Pharmacology & Toxicology, University of Toronto Toronto Ontario M5S 1A8 Canada
| | - Cora Scholten
- Research and Development, Bayer AG, Pharmaceuticals 13353 Berlin Germany
| | - Sujata Sharma
- Structural & Protein Sciences, Discovery Sciences, Janssen Research & Development 1400 McKean Rd Spring House PA 19477 USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health Rockville Maryland 20850 USA
| | - Michael Sundström
- Division of Rheumatology, Department of Medicine Solna, Karolinska University Hospital and Karolinska Institutet Stockholm Sweden
| | - Giulio Superti-Furga
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria
- Center for Physiology and Pharmacology, Medical University of Vienna Vienna Austria
| | - Matthew H Todd
- School of Pharmacy, University College London London WC1N 1AX UK
| | - Claudia Tredup
- Institute of Pharmaceutical Chemistry, Goethe University Frankfurt Frankfurt 60438 Germany
- Structural Genomics Consortium, BMLS, Goethe University Frankfurt Frankfurt 60438 Germany
| | - Masoud Vedadi
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
- Department of Pharmacology & Toxicology, University of Toronto Toronto Ontario M5S 1A8 Canada
| | - Frank von Delft
- Centre for Medicines Discovery, University of Oxford Old Road Campus Research Building, Roosevelt Drive Oxford OX3 7DQ UK
- Diamond Light Source Ltd Harwell Science and Innovation Campus Didcot OX11 0QX UK
- Department of Biochemistry, University of Johannesburg Auckland Park 2006 South Africa
- Research Complex at Harwell Harwell Science and Innovation Campus Didcot OX11 0FA UK
| | - Timothy M Willson
- Lineberger Comprehensive Cancer Center, Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill Chapel Hill NC 27599 USA
| | - Georg E Winter
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria
| | - Paul Workman
- CRUK ICR/Imperial Convergence Science Centre London SM2 5NG UK
- Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research London SM2 5NG UK
| | - Cheryl H Arrowsmith
- Structural Genomics Consortium, University of Toronto Toronto Ontario M5G 1L7 Canada
- Princess Margaret Cancer Centre Toronto Ontario M5G 1L7 Canada
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10
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Schneider M, Radoux CJ, Hercules A, Ochoa D, Dunham I, Zalmas LP, Hessler G, Ruf S, Shanmugasundaram V, Hann MM, Thomas PJ, Queisser MA, Benowitz AB, Brown K, Leach AR. The PROTACtable genome. Nat Rev Drug Discov 2021; 20:789-797. [PMID: 34285415 DOI: 10.1038/s41573-021-00245-x] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/09/2021] [Indexed: 01/23/2023]
Abstract
Proteolysis-targeting chimeras (PROTACs) are an emerging drug modality that may offer new opportunities to circumvent some of the limitations associated with traditional small-molecule therapeutics. By analogy with the concept of the 'druggable genome', the question arises as to which potential drug targets might PROTAC-mediated protein degradation be most applicable. Here, we present a systematic approach to the assessment of the PROTAC tractability (PROTACtability) of protein targets using a series of criteria based on data and information from a diverse range of relevant publicly available resources. Our approach could support decision-making on whether or not a particular target may be amenable to modulation using a PROTAC. Using our approach, we identified 1,067 proteins of the human proteome that have not yet been described in the literature as PROTAC targets that offer potential opportunities for future PROTAC-based efforts.
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Affiliation(s)
- Melanie Schneider
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Open Targets, Wellcome Genome Campus, Hinxton, UK
| | - Chris J Radoux
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- Exscientia, Oxford, UK
| | - Andrew Hercules
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Open Targets, Wellcome Genome Campus, Hinxton, UK
| | - David Ochoa
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Open Targets, Wellcome Genome Campus, Hinxton, UK
| | - Ian Dunham
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
- Open Targets, Wellcome Genome Campus, Hinxton, UK
| | - Lykourgos-Panagiotis Zalmas
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Gerhard Hessler
- Integrated Drug Discovery, Sanofi-Aventis Deutschland, Frankfurt am Main, Germany
| | - Sven Ruf
- Integrated Drug Discovery, Sanofi-Aventis Deutschland, Frankfurt am Main, Germany
| | | | - Michael M Hann
- GlaxoSmithKline, GSK Medicines Research Centre, Stevenage, UK
| | - Pam J Thomas
- GlaxoSmithKline, GSK Medicines Research Centre, Stevenage, UK
| | | | | | - Kris Brown
- GlaxoSmithKline, Collegeville, PA, USA
- Agenus, Lexington, MA, USA
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK.
- Open Targets, Wellcome Genome Campus, Hinxton, UK.
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11
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Copley HC, Gragert L, Leach AR, Kosmoliaptsis V. Influence of HLA Class II Polymorphism on Predicted Cellular Immunity Against SARS-CoV-2 at the Population and Individual Level. Front Immunol 2021; 12:669357. [PMID: 34349756 PMCID: PMC8327207 DOI: 10.3389/fimmu.2021.669357] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 06/28/2021] [Indexed: 01/16/2023] Open
Abstract
Development of adaptive immunity after COVID-19 and after vaccination against SARS-CoV-2 is predicated on recognition of viral peptides, presented on HLA class II molecules, by CD4+ T-cells. We capitalised on extensive high-resolution HLA data on twenty five human race/ethnic populations to investigate the role of HLA polymorphism on SARS-CoV-2 immunogenicity at the population and individual level. Within populations, we identify wide inter-individual variability in predicted peptide presentation from structural, non-structural and accessory SARS-CoV-2 proteins, according to individual HLA genotype. However, we find similar potential for anti-SARS-CoV-2 cellular immunity at the population level suggesting that HLA polymorphism is unlikely to account for observed disparities in clinical outcomes after COVID-19 among different race/ethnic groups. Our findings provide important insight on the potential role of HLA polymorphism on development of protective immunity after SARS-CoV-2 infection and after vaccination and a firm basis for further experimental studies in this field.
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Affiliation(s)
- Hannah C. Copley
- Department of Surgery, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
- European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom
| | - Loren Gragert
- Department of Pathology, Tulane University School of Medicine, New Orleans, LA, United States
- Bioinformatics Research, National Marrow Donor Program, Minneapolis, MN, United States
| | - Andrew R. Leach
- European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom
| | - Vasilis Kosmoliaptsis
- Department of Surgery, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
- National Institute of Health Research (NIHR) Blood and Transplant Research Unit in Organ Donation and Transplantation, University of Cambridge, Cambridge, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom
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12
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Abstract
Physicochemical descriptors commonly used to define "drug-likeness" and ligand efficiency measures are assessed for their ability to differentiate marketed drugs from compounds reported to bind to their efficacious target or targets. Using ChEMBL version 26, a data set of 643 drugs acting on 271 targets was assembled, comprising 1104 drug-target pairs having ≥100 published compounds per target. Taking into account changes in their physicochemical properties over time, drugs are analyzed according to their target class, therapy area, and route of administration. Recent drugs, approved in 2010-2020, display no overall differences in molecular weight, lipophilicity, hydrogen bonding, or polar surface area from their target comparator compounds. Drugs are differentiated from target comparators by higher potency, ligand efficiency (LE), lipophilic ligand efficiency (LLE), and lower carboaromaticity. Overall, 96% of drugs have LE or LLE values, or both, greater than the median values of their target comparator compounds.
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Affiliation(s)
- Paul D Leeson
- Paul Leeson Consulting Ltd, The Malt House, Main Street, Congerstone, Nuneaton, Warkwickshire CV13 6LZ, United Kingdom
| | - A Patricia Bento
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Anna Gaulton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Anne Hersey
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Emma J Manners
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Chris J Radoux
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom
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13
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Gaziano L, Giambartolomei C, Pereira AC, Gaulton A, Posner DC, Swanson SA, Ho YL, Iyengar SK, Kosik NM, Vujkovic M, Gagnon DR, Bento AP, Barrio-Hernandez I, Rönnblom L, Hagberg N, Lundtoft C, Langenberg C, Pietzner M, Valentine D, Gustincich S, Tartaglia GG, Allara E, Surendran P, Burgess S, Zhao JH, Peters JE, Prins BP, Angelantonio ED, Devineni P, Shi Y, Lynch KE, DuVall SL, Garcon H, Thomann LO, Zhou JJ, Gorman BR, Huffman JE, O'Donnell CJ, Tsao PS, Beckham JC, Pyarajan S, Muralidhar S, Huang GD, Ramoni R, Beltrao P, Danesh J, Hung AM, Chang KM, Sun YV, Joseph J, Leach AR, Edwards TL, Cho K, Gaziano JM, Butterworth AS, Casas JP. Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19. Nat Med 2021; 27:668-676. [PMID: 33837377 PMCID: PMC7612986 DOI: 10.1038/s41591-021-01310-z] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/05/2021] [Indexed: 12/31/2022]
Abstract
Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.
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Affiliation(s)
- Liam Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Claudia Giambartolomei
- Central RNA Lab, Istituto Italiano di Tecnologia, Genoa, Italy
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo, Brazil
- Genetics Department, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Anna Gaulton
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sonja A Swanson
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sudha K Iyengar
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University and Louis Stoke, Cleveland VA, Cleveland, OH, USA
| | - Nicole M Kosik
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Marijana Vujkovic
- The Corporal Michael J. Crescenz VA Medical Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David R Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - A Patrícia Bento
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | | | - Lars Rönnblom
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Niklas Hagberg
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Claudia Langenberg
- Berlin Institute of Health, Charité University Medicine Berlin, Berlin, Germany
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Dennis Valentine
- Institute of Health Informatics, University College London, London, UK
- Health Data Research, University College London, London, UK
| | | | | | - Elias Allara
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Praveen Surendran
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Jing Hua Zhao
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - James E Peters
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- Centre for Inflammatory Disease, Dept of Immunology and Inflammation, Imperial College, London, UK
| | - Bram P Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Emanuele Di Angelantonio
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Poornima Devineni
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Yunling Shi
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Kristine E Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, Epidemiology, University of Utah, Salt Lake City, UT, USA
| | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Lauren O Thomann
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Jin J Zhou
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - Bryan R Gorman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Jennifer E Huffman
- Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Christopher J O'Donnell
- Cardiology, VA Boston Healthcare System, Boston, MA, USA
- Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Philip S Tsao
- Epidemiology Research and Information Center (ERIC), VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Jean C Beckham
- MIRECC, Durham VA Medical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Saiju Pyarajan
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Grant D Huang
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Adriana M Hung
- VA Tennessee Valley Healthcare System, Nashville, TN, USA
- Nephrology & Hypertension, Vanderbilt University, Nashville, TN, USA
| | - Kyong-Mi Chang
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- The Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Medicine, Cardiovascular, VA Boston Healthcare System and Brigham & Women's Hospital, Boston, MA, USA
| | - Andrew R Leach
- Chemical Biology, European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Todd L Edwards
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Vanderbilt University, Nashville, TN, USA
- Medicine, Epidemiology, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK.
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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14
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Bosc N, Felix E, Arcila R, Mendez D, Saunders MR, Green DVS, Ochoada J, Shelat AA, Martin EJ, Iyer P, Engkvist O, Verras A, Duffy J, Burrows J, Gardner JMF, Leach AR. MAIP: a web service for predicting blood-stage malaria inhibitors. J Cheminform 2021; 13:13. [PMID: 33618772 PMCID: PMC7898753 DOI: 10.1186/s13321-021-00487-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 01/20/2021] [Indexed: 12/17/2022] Open
Abstract
Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/ . MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.
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Affiliation(s)
- Nicolas Bosc
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom.
| | - Eloy Felix
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom
| | - Ricardo Arcila
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom
| | - David Mendez
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom
| | - Martin R Saunders
- Department of Molecular Design, Data and Computational Sciences, GlaxoSmithKline, Gunnels Wood Road, Hertfordshire, SG1 2NY, Stevenage, UK
| | - Darren V S Green
- Department of Molecular Design, Data and Computational Sciences, GlaxoSmithKline, Gunnels Wood Road, Hertfordshire, SG1 2NY, Stevenage, UK
| | - Jason Ochoada
- Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Tennessee, 38105, Memphis, USA
| | - Anang A Shelat
- Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Tennessee, 38105, Memphis, USA
| | - Eric J Martin
- Novartis Institute for Biomedical Research, 5300 Chiron Way, California, 94608- 2916, Emeryville, USA
| | - Preeti Iyer
- Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Ola Engkvist
- Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Andreas Verras
- Schrodinger Inc, 120 West 45th Street, 10036-4041, New York, NY, USA
| | - James Duffy
- Medicines for Malaria Ventures Discovery, 1215, Geneva, Switzerland
| | - Jeremy Burrows
- Medicines for Malaria Ventures Discovery, 1215, Geneva, Switzerland
| | - J Mark F Gardner
- AMG Consultants Ltd, Discovery Park House, Discovery Park, Ramsgate Road, CT13 9ND, Sandwich, Kent, UK
| | - Andrew R Leach
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom.
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15
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Hunter FM, Bento AP, Bosc N, Gaulton A, Hersey A, Leach AR. Drug Safety Data Curation and Modeling in ChEMBL: Boxed Warnings and Withdrawn Drugs. Chem Res Toxicol 2021; 34:385-395. [PMID: 33507738 PMCID: PMC7888266 DOI: 10.1021/acs.chemrestox.0c00296] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Indexed: 12/15/2022]
Abstract
The safety of marketed drugs is an ongoing concern, with some of the more frequently prescribed medicines resulting in serious or life-threatening adverse effects in some patients. Safety-related information for approved drugs has been curated to include the assignment of toxicity class(es) based on their withdrawn status and/or black box warning information described on medicinal product labels. The ChEMBL resource contains a wide range of bioactivity data types, from early "Discovery" stage preclinical data for individual compounds through to postclinical data on marketed drugs; the inclusion of the curated drug safety data set within this framework can support a wide range of safety-related drug discovery questions. The curated drug safety data set will be made freely available through ChEMBL and updated in future database releases.
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Affiliation(s)
- Fiona M.I. Hunter
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
| | - A. Patrícia Bento
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
| | - Nicolas Bosc
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
| | - Anna Gaulton
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
| | - Anne Hersey
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
| | - Andrew R. Leach
- European Bioinformatics Institute, European
Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge
CB10 1SD, United Kingdom
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16
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Bento AP, Hersey A, Félix E, Landrum G, Gaulton A, Atkinson F, Bellis LJ, De Veij M, Leach AR. An open source chemical structure curation pipeline using RDKit. J Cheminform 2020; 12:51. [PMID: 33431044 PMCID: PMC7458899 DOI: 10.1186/s13321-020-00456-1] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 08/24/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The ChEMBL database is one of a number of public databases that contain bioactivity data on small molecule compounds curated from diverse sources. Incoming compounds are typically not standardised according to consistent rules. In order to maintain the quality of the final database and to easily compare and integrate data on the same compound from different sources it is necessary for the chemical structures in the database to be appropriately standardised. RESULTS A chemical curation pipeline has been developed using the open source toolkit RDKit. It comprises three components: a Checker to test the validity of chemical structures and flag any serious errors; a Standardizer which formats compounds according to defined rules and conventions and a GetParent component that removes any salts and solvents from the compound to create its parent. This pipeline has been applied to the latest version of the ChEMBL database as well as uncurated datasets from other sources to test the robustness of the process and to identify common issues in database molecular structures. CONCLUSION All the components of the structure pipeline have been made freely available for other researchers to use and adapt for their own use. The code is available in a GitHub repository and it can also be accessed via the ChEMBL Beaker webservices. It has been used successfully to standardise the nearly 2 million compounds in the ChEMBL database and the compound validity checker has been used to identify compounds with the most serious issues so that they can be prioritised for manual curation.
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Affiliation(s)
- A Patrícia Bento
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
| | - Anne Hersey
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
| | - Eloy Félix
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
| | | | - Anna Gaulton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
| | - Francis Atkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
- The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge, CB2 1EZ, UK
| | - Louisa J Bellis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Marleen De Veij
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridgeshire, UK.
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17
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Bouhaddou M, Memon D, Meyer B, White KM, Rezelj VV, Correa Marrero M, Polacco BJ, Melnyk JE, Ulferts S, Kaake RM, Batra J, Richards AL, Stevenson E, Gordon DE, Rojc A, Obernier K, Fabius JM, Soucheray M, Miorin L, Moreno E, Koh C, Tran QD, Hardy A, Robinot R, Vallet T, Nilsson-Payant BE, Hernandez-Armenta C, Dunham A, Weigang S, Knerr J, Modak M, Quintero D, Zhou Y, Dugourd A, Valdeolivas A, Patil T, Li Q, Hüttenhain R, Cakir M, Muralidharan M, Kim M, Jang G, Tutuncuoglu B, Hiatt J, Guo JZ, Xu J, Bouhaddou S, Mathy CJP, Gaulton A, Manners EJ, Félix E, Shi Y, Goff M, Lim JK, McBride T, O'Neal MC, Cai Y, Chang JCJ, Broadhurst DJ, Klippsten S, De Wit E, Leach AR, Kortemme T, Shoichet B, Ott M, Saez-Rodriguez J, tenOever BR, Mullins RD, Fischer ER, Kochs G, Grosse R, García-Sastre A, Vignuzzi M, Johnson JR, Shokat KM, Swaney DL, Beltrao P, Krogan NJ. The Global Phosphorylation Landscape of SARS-CoV-2 Infection. Cell 2020; 182:685-712.e19. [PMID: 32645325 PMCID: PMC7321036 DOI: 10.1016/j.cell.2020.06.034] [Citation(s) in RCA: 665] [Impact Index Per Article: 166.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/09/2020] [Accepted: 06/23/2020] [Indexed: 02/07/2023]
Abstract
The causative agent of the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected millions and killed hundreds of thousands of people worldwide, highlighting an urgent need to develop antiviral therapies. Here we present a quantitative mass spectrometry-based phosphoproteomics survey of SARS-CoV-2 infection in Vero E6 cells, revealing dramatic rewiring of phosphorylation on host and viral proteins. SARS-CoV-2 infection promoted casein kinase II (CK2) and p38 MAPK activation, production of diverse cytokines, and shutdown of mitotic kinases, resulting in cell cycle arrest. Infection also stimulated a marked induction of CK2-containing filopodial protrusions possessing budding viral particles. Eighty-seven drugs and compounds were identified by mapping global phosphorylation profiles to dysregulated kinases and pathways. We found pharmacologic inhibition of the p38, CK2, CDK, AXL, and PIKFYVE kinases to possess antiviral efficacy, representing potential COVID-19 therapies.
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Affiliation(s)
- Mehdi Bouhaddou
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Danish Memon
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Bjoern Meyer
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | - Kris M White
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Veronica V Rezelj
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | - Miguel Correa Marrero
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Benjamin J Polacco
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - James E Melnyk
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute
| | - Svenja Ulferts
- Institute for Clinical and Experimental Pharmacology and Toxicology, University of Freiburg, Freiburg 79104, Germany
| | - Robyn M Kaake
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jyoti Batra
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Alicia L Richards
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Erica Stevenson
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - David E Gordon
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ajda Rojc
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kirsten Obernier
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jacqueline M Fabius
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Margaret Soucheray
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Lisa Miorin
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Elena Moreno
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Cassandra Koh
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | - Quang Dinh Tran
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | - Alexandra Hardy
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | - Rémy Robinot
- Virus & Immunity Unit, Department of Virology, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France; Vaccine Research Institute, 94000 Creteil, France
| | - Thomas Vallet
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France
| | | | - Claudia Hernandez-Armenta
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Alistair Dunham
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Sebastian Weigang
- Institute of Virology, Medical Center - University of Freiburg, Freiburg 79104, Germany
| | - Julian Knerr
- Institute for Clinical and Experimental Pharmacology and Toxicology, University of Freiburg, Freiburg 79104, Germany
| | - Maya Modak
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Diego Quintero
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yuan Zhou
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Aurelien Dugourd
- Institute for Computational Biomedicine, Bioquant, Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Heidelberg 69120, Germany
| | - Alberto Valdeolivas
- Institute for Computational Biomedicine, Bioquant, Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Heidelberg 69120, Germany
| | - Trupti Patil
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Qiongyu Li
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ruth Hüttenhain
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Merve Cakir
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Monita Muralidharan
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Minkyu Kim
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Gwendolyn Jang
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Beril Tutuncuoglu
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Joseph Hiatt
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jeffrey Z Guo
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jiewei Xu
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Sophia Bouhaddou
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA
| | - Christopher J P Mathy
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Bioengineering & Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Anna Gaulton
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Emma J Manners
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Eloy Félix
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ying Shi
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute
| | - Marisa Goff
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jean K Lim
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | | | | | | | | | | | - Emmie De Wit
- NIH/NIAID/Rocky Mountain Laboratories, Hamilton, MT 59840, USA
| | - Andrew R Leach
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tanja Kortemme
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Bioengineering & Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Brian Shoichet
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA
| | - Melanie Ott
- J. David Gladstone Institutes, San Francisco, CA 94158, USA
| | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Bioquant, Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Heidelberg 69120, Germany
| | - Benjamin R tenOever
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - R Dyche Mullins
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute
| | | | - Georg Kochs
- Institute of Virology, Medical Center - University of Freiburg, Freiburg 79104, Germany; Faculty of Medicine, University of Freiburg, Freiburg 79008, Germany
| | - Robert Grosse
- Institute for Clinical and Experimental Pharmacology and Toxicology, University of Freiburg, Freiburg 79104, Germany; Faculty of Medicine, University of Freiburg, Freiburg 79008, Germany; Centre for Integrative Biological Signalling Studies (CIBSS), Freiburg 79104, Germany.
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA; The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Marco Vignuzzi
- Viral Populations and Pathogenesis Unit, CNRS UMR 3569, Institut Pasteur, 75724 Paris, Cedex 15, France.
| | - Jeffery R Johnson
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Kevan M Shokat
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute.
| | - Danielle L Swaney
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA.
| | - Pedro Beltrao
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
| | - Nevan J Krogan
- QBI COVID-19 Research Group (QCRG), San Francisco, CA 94158, USA; Quantitative Biosciences Institute (QBI), University of California, San Francisco, San Francisco, CA 94158, USA; J. David Gladstone Institutes, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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18
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Gonçalves E, Segura‐Cabrera A, Pacini C, Picco G, Behan FM, Jaaks P, Coker EA, van der Meer D, Barthorpe A, Lightfoot H, Mironenko T, Beck A, Richardson L, Yang W, Lleshi E, Hall J, Tolley C, Hall C, Mali I, Thomas F, Morris J, Leach AR, Lynch JT, Sidders B, Crafter C, Iorio F, Fawell S, Garnett MJ. Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens. Mol Syst Biol 2020; 16:e9405. [PMID: 32627965 PMCID: PMC7336273 DOI: 10.15252/msb.20199405] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 05/14/2020] [Accepted: 05/21/2020] [Indexed: 12/26/2022] Open
Abstract
Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development.
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Affiliation(s)
| | - Aldo Segura‐Cabrera
- European Molecular Biology LaboratoryEuropean Bioinformatics InstituteHinxtonUK
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Andrew R Leach
- European Molecular Biology LaboratoryEuropean Bioinformatics InstituteHinxtonUK
| | - James T Lynch
- Research and Early DevelopmentOncology R&DAstraZenecaCambridgeUK
| | - Ben Sidders
- Research and Early DevelopmentOncology R&DAstraZenecaCambridgeUK
| | - Claire Crafter
- Research and Early DevelopmentOncology R&DAstraZenecaCambridgeUK
| | - Francesco Iorio
- Wellcome Sanger InstituteHinxtonUK
- Human TechnopoleMilanoItaly
| | - Stephen Fawell
- Research and Early DevelopmentOncology R&DAstraZenecaWalthamMAUSA
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19
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Mendez D, Gaulton A, Bento AP, Chambers J, De Veij M, Félix E, Magariños MP, Mosquera JF, Mutowo P, Nowotka M, Gordillo-Marañón M, Hunter F, Junco L, Mugumbate G, Rodriguez-Lopez M, Atkinson F, Bosc N, Radoux CJ, Segura-Cabrera A, Hersey A, Leach AR. ChEMBL: towards direct deposition of bioassay data. Nucleic Acids Res 2020; 47:D930-D940. [PMID: 30398643 PMCID: PMC6323927 DOI: 10.1093/nar/gky1075] [Citation(s) in RCA: 944] [Impact Index Per Article: 236.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 10/18/2018] [Indexed: 12/31/2022] Open
Abstract
ChEMBL is a large, open-access bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012, 2014 and 2017 Nucleic Acids Research Database Issues. In the last two years, several important improvements have been made to the database and are described here. These include more robust capture and representation of assay details; a new data deposition system, allowing updating of data sets and deposition of supplementary data; and a completely redesigned web interface, with enhanced search and filtering capabilities.
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Affiliation(s)
- David Mendez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Anna Gaulton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - A Patrícia Bento
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Jon Chambers
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Marleen De Veij
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Eloy Félix
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - María Paula Magariños
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.,Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Juan F Mosquera
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Prudence Mutowo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Michal Nowotka
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - María Gordillo-Marañón
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
| | - Fiona Hunter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Laura Junco
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Grace Mugumbate
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Milagros Rodriguez-Lopez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Francis Atkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Nicolas Bosc
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Chris J Radoux
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.,Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Aldo Segura-Cabrera
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Anne Hersey
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
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20
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Curran PR, Radoux CJ, Smilova MD, Sykes RA, Higueruelo AP, Bradley AR, Marsden BD, Spring DR, Blundell TL, Leach AR, Pitt WR, Cole JC. Hotspots API: A Python Package for the Detection of Small Molecule Binding Hotspots and Application to Structure-Based Drug Design. J Chem Inf Model 2020; 60:1911-1916. [DOI: 10.1021/acs.jcim.9b00996] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Peter R. Curran
- The Cambridge Crystallographic Data Centre (CCDC), 12 Union Road, Cambridge, CB2 1EZ, U.K
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, U.K
| | | | - Mihaela D. Smilova
- Structural Genomic Consortium (SGC), Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Headington, Oxford, OX3 7DQ, U.K
| | - Richard A. Sykes
- The Cambridge Crystallographic Data Centre (CCDC), 12 Union Road, Cambridge, CB2 1EZ, U.K
| | - Alicia P. Higueruelo
- The Cambridge Crystallographic Data Centre (CCDC), 12 Union Road, Cambridge, CB2 1EZ, U.K
| | | | - Brian D. Marsden
- Structural Genomic Consortium (SGC), Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Headington, Oxford, OX3 7DQ, U.K
- Kennedy Institute of Rheumatology, NDORMS, University of Oxford, Headington, Oxford, OX3 7FY, U.K
| | - David R. Spring
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, U.K
| | - Tom L. Blundell
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, U.K
| | - Andrew R. Leach
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, U.K
| | | | - Jason C. Cole
- The Cambridge Crystallographic Data Centre (CCDC), 12 Union Road, Cambridge, CB2 1EZ, U.K
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21
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Bosc N, Atkinson F, Félix E, Gaulton A, Hersey A, Leach AR. Reply to "Missed opportunities in large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery". J Cheminform 2019; 11:64. [PMID: 33430932 PMCID: PMC6831531 DOI: 10.1186/s13321-019-0388-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 10/22/2019] [Indexed: 11/10/2022] Open
Abstract
In response to Krstajic's letter to the editor concerning our published paper, we here take the opportunity to reply, to re-iterate that no errors in our work were identified, to provide further details, and to re-emphasise the outputs of our study. Moreover, we highlight that all of the data are freely available for the wider scientific community (including the aforementioned correspondent) to undertake follow-on studies and comparisons.
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Affiliation(s)
- Nicolas Bosc
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Francis Atkinson
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Eloy Félix
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Anna Gaulton
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Anne Hersey
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Andrew R Leach
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
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22
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Bosc N, Atkinson F, Felix E, Gaulton A, Hersey A, Leach AR. Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery. J Cheminform 2019; 11:4. [PMID: 30631996 PMCID: PMC6690068 DOI: 10.1186/s13321-018-0325-4] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 12/24/2018] [Indexed: 12/22/2022] Open
Abstract
Structure–activity relationship modelling is frequently used in the early stage of drug discovery to assess the activity of a compound on one or several targets, and can also be used to assess the interaction of compounds with liability targets. QSAR models have been used for these and related applications over many years, with good success. Conformal prediction is a relatively new QSAR approach that provides information on the certainty of a prediction, and so helps in decision-making. However, it is not always clear how best to make use of this additional information. In this article, we describe a case study that directly compares conformal prediction with traditional QSAR methods for large-scale predictions of target-ligand binding. The ChEMBL database was used to extract a data set comprising data from 550 human protein targets with different bioactivity profiles. For each target, a QSAR model and a conformal predictor were trained and their results compared. The models were then evaluated on new data published since the original models were built to simulate a “real world” application. The comparative study highlights the similarities between the two techniques but also some differences that it is important to bear in mind when the methods are used in practical drug discovery applications.
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Affiliation(s)
- Nicolas Bosc
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
| | - Francis Atkinson
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Eloy Felix
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Anna Gaulton
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Anne Hersey
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Andrew R Leach
- Chemogenomics Team, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
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23
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Hunter FMI, L Atkinson F, Bento AP, Bosc N, Gaulton A, Hersey A, Leach AR. A large-scale dataset of in vivo pharmacology assay results. Sci Data 2018; 5:180230. [PMID: 30351302 PMCID: PMC6206617 DOI: 10.1038/sdata.2018.230] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 09/03/2018] [Indexed: 12/17/2022] Open
Abstract
ChEMBL is a large-scale, open-access drug discovery resource containing bioactivity
information primarily extracted from scientific literature. A substantial dataset of more
than 135,000 in vivo assays has been collated as a key resource of animal models for
translational medicine within drug discovery. To improve the utility of the in vivo
data, an extensive data curation task has been undertaken that allows the assays to be
grouped by animal disease model or phenotypic endpoint. The dataset contains previously
unavailable information about compounds or drugs tested in animal models and, in conjunction
with assay data on protein targets or cell- or tissue- based systems, allows the
investigation of the effects of compounds at differing levels of biological complexity.
Equally, it enables researchers to identify compounds that have been investigated for a
group of disease-, pharmacology- or toxicity-relevant assays.
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Affiliation(s)
- Fiona M I Hunter
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Francis L Atkinson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - A Patrícia Bento
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Nicolas Bosc
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Anna Gaulton
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Anne Hersey
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Andrew R Leach
- European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
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24
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Oprea TI, Bologa CG, Brunak S, Campbell A, Gan GN, Gaulton A, Gomez SM, Guha R, Hersey A, Holmes J, Jadhav A, Jensen LJ, Johnson GL, Karlson A, Leach AR, Ma’ayan A, Malovannaya A, Mani S, Mathias SL, McManus MT, Meehan TF, von Mering C, Muthas D, Nguyen DT, Overington JP, Papadatos G, Qin J, Reich C, Roth BL, Schürer SC, Simeonov A, Sklar LA, Southall N, Tomita S, Tudose I, Ursu O, Vidovic D, Waller A, Westergaard D, Yang JJ, Zahoránszky-Köhalmi G. Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov 2018; 17:317-332. [PMID: 29472638 PMCID: PMC6339563 DOI: 10.1038/nrd.2018.14] [Citation(s) in RCA: 204] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
A large proportion of biomedical research and the development of therapeutics is focused on a small fraction of the human genome. In a strategic effort to map the knowledge gaps around proteins encoded by the human genome and to promote the exploration of currently understudied, but potentially druggable, proteins, the US National Institutes of Health launched the Illuminating the Druggable Genome (IDG) initiative in 2014. In this article, we discuss how the systematic collection and processing of a wide array of genomic, proteomic, chemical and disease-related resource data by the IDG Knowledge Management Center have enabled the development of evidence-based criteria for tracking the target development level (TDL) of human proteins, which indicates a substantial knowledge deficit for approximately one out of three proteins in the human proteome. We then present spotlights on the TDL categories as well as key drug target classes, including G protein-coupled receptors, protein kinases and ion channels, which illustrate the nature of the unexplored opportunities for biomedical research and therapeutic development.
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Affiliation(s)
- Tudor I. Oprea
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
- UNM Comprehensive Cancer Center, Albuquerque, NM, USA
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cristian G. Bologa
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Anna Gaulton
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Shawn M. Gomez
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, USA
- Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Rajarshi Guha
- National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA
| | - Anne Hersey
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Jayme Holmes
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Ajit Jadhav
- National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gary L. Johnson
- Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Anneli Karlson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
- Present addresses: SciBite Limited, BioData Innovation Centre, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Andrew R. Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Avi Ma’ayan
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Subramani Mani
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Stephen L. Mathias
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | | | - Terrence F. Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Daniel Muthas
- Respiratory, Inflammation and Autoimmunity Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca R&D Gothenburg, Mölndal, Sweden
| | - Dac-Trung Nguyen
- National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA
| | - John P. Overington
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
- Medicines Discovery Catapult, Alderley Edge, UK
| | - George Papadatos
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
- GlaxoSmithKline, Stevenage, UK
| | - Jun Qin
- Baylor College of Medicine, Houston, TX, USA
| | | | - Bryan L. Roth
- Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Stephan C. Schürer
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA
| | - Larry A. Sklar
- UNM Comprehensive Cancer Center, Albuquerque, NM, USA
- Center for Molecular Discovery, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM, USA
- Department of Pathology, University of New Mexico, Albuquerque, NM, USA
| | - Noel Southall
- National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA
| | - Susumu Tomita
- Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Ilinca Tudose
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK
- Google Germany GmbH, München, Germany
| | - Oleg Ursu
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Dušica Vidovic
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Anna Waller
- Center for Molecular Discovery, University of New Mexico Cancer Center, University of New Mexico, Albuquerque, NM, USA
| | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jeremy J. Yang
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Gergely Zahoránszky-Köhalmi
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA
- NIH-NCATS, Rockville, MD, USA
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Oprea TI, Bologa CG, Brunak S, Campbell A, Gan GN, Gaulton A, Gomez SM, Guha R, Hersey A, Holmes J, Jadhav A, Jensen LJ, Johnson GL, Karlson A, Leach AR, Ma'ayan A, Malovannaya A, Mani S, Mathias SL, McManus MT, Meehan TF, von Mering C, Muthas D, Nguyen DT, Overington JP, Papadatos G, Qin J, Reich C, Roth BL, Schürer SC, Simeonov A, Sklar LA, Southall N, Tomita S, Tudose I, Ursu O, Vidovic D, Waller A, Westergaard D, Yang JJ, Zahoránszky-Köhalmi G. Unexplored therapeutic opportunities in the human genome. Nat Rev Drug Discov 2018; 17:377. [PMID: 29567993 DOI: 10.1038/nrd.2018.52] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
This corrects the article DOI: 10.1038/nrd.2018.14.
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Gaulton A, Hersey A, Nowotka M, Bento AP, Chambers J, Mendez D, Mutowo P, Atkinson F, Bellis LJ, Cibrián-Uhalte E, Davies M, Dedman N, Karlsson A, Magariños MP, Overington JP, Papadatos G, Smit I, Leach AR. The ChEMBL database in 2017. Nucleic Acids Res 2016; 45:D945-D954. [PMID: 27899562 PMCID: PMC5210557 DOI: 10.1093/nar/gkw1074] [Citation(s) in RCA: 1328] [Impact Index Per Article: 166.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 10/21/2016] [Accepted: 10/30/2016] [Indexed: 11/14/2022] Open
Abstract
ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.
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Affiliation(s)
- Anna Gaulton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Anne Hersey
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Michał Nowotka
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - A Patrícia Bento
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.,Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Jon Chambers
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - David Mendez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Prudence Mutowo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Francis Atkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Louisa J Bellis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Elena Cibrián-Uhalte
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Mark Davies
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Nathan Dedman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Anneli Karlsson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - María Paula Magariños
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.,Open Targets, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - John P Overington
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - George Papadatos
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Ines Smit
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Andrew R Leach
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
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Wall ID, Hann MM, Leach AR, Pickett SD. Current Status and Future Direction of Fragment-Based Drug Discovery: A Computational Chemistry Perspective. Fragment-Based Drug Discovery 2015. [DOI: 10.1039/9781782620938-00073] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Fragment-based drug discovery (FBDD) has become a well-established and widely used approach for lead identification. The computational chemistry community has played a central role in developing the ideas behind this area of research and computational tools are important throughout FBDD campaigns. This article discusses the evolution of best practice, on-going areas of debate and gaps in current capabilities from a computational chemistry perspective. In particular, the contribution of computational methods to areas such as fragment library design, screening analysis, data handling and the role of structure- and ligand-based design is discussed. The potential to combine FBDD with other hit-identification methods such as high-throughput screening in a more integrated approach is also highlighted.
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Affiliation(s)
- Ian D. Wall
- GlaxoSmithKline Gunnels Wood Road Stevenage, Hertfordshire, SG1 2NY UK
| | - Michael M. Hann
- GlaxoSmithKline Gunnels Wood Road Stevenage, Hertfordshire, SG1 2NY UK
| | - Andrew R. Leach
- GlaxoSmithKline Gunnels Wood Road Stevenage, Hertfordshire, SG1 2NY UK
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Waring MJ, Arrowsmith J, Leach AR, Leeson PD, Mandrell S, Owen RM, Pairaudeau G, Pennie WD, Pickett SD, Wang J, Wallace O, Weir A. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat Rev Drug Discov 2015; 14:475-86. [PMID: 26091267 DOI: 10.1038/nrd4609] [Citation(s) in RCA: 773] [Impact Index Per Article: 85.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The pharmaceutical industry remains under huge pressure to address the high attrition rates in drug development. Attempts to reduce the number of efficacy- and safety-related failures by analysing possible links to the physicochemical properties of small-molecule drug candidates have been inconclusive because of the limited size of data sets from individual companies. Here, we describe the compilation and analysis of combined data on the attrition of drug candidates from AstraZeneca, Eli Lilly and Company, GlaxoSmithKline and Pfizer. The analysis reaffirms that control of physicochemical properties during compound optimization is beneficial in identifying compounds of candidate drug quality and indicates for the first time a link between the physicochemical properties of compounds and clinical failure due to safety issues. The results also suggest that further control of physicochemical properties is unlikely to have a significant effect on attrition rates and that additional work is required to address safety-related failures. Further cross-company collaborations will be crucial to future progress in this area.
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Affiliation(s)
| | | | | | - Paul D Leeson
- 1] GlaxoSmithKline, Stevenage, Hertfordshire SG1 2NY, UK. [2] Paul Leeson Consulting, The Malt House, Main Street, Congerstone, Nuneaton, Warwickshire CV13 6LZ, UK
| | - Sam Mandrell
- Thomson Reuters, 77 Hatton Garden, London EC1N 8JS, UK
| | | | | | - William D Pennie
- 1] Pfizer, Groton, Connecticut 06340, USA. [2] Takeda Pharmaceuticals, Cambridge, Massachusetts 02139, USA
| | | | - Jibo Wang
- Eli Lilly, Indianapolis, Indiana 46285, USA
| | - Owen Wallace
- 1] Eli Lilly, Indianapolis, Indiana 46285, USA. [2] Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA
| | - Alex Weir
- Thomson Reuters, 77 Hatton Garden, London EC1N 8JS, UK
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Leach AR, Wallace K, Alepee N, Daston G, Humphris C, Manou I, Modi S, Ringeissen S, Whelan M, Kimber I. Characterising hepatic mitochondrial function as a model for systemic toxicity: a commentary. Toxicology 2012; 302:96-9. [PMID: 23126011 DOI: 10.1016/j.tox.2012.06.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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30
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Green DVS, Leach AR, Head MS. Computer-aided molecular design under the SWOTlight. J Comput Aided Mol Des 2011; 26:51-6. [PMID: 22170256 DOI: 10.1007/s10822-011-9514-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2011] [Accepted: 12/02/2011] [Indexed: 12/01/2022]
Affiliation(s)
- Darren V S Green
- GlaxoSmithKline Medicines Research Centre, Stevenage, Hertfordshire, UK.
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31
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Leach AR. Cheminformatics and computational chemistry in lead optimisation. J Cheminform 2011. [PMCID: PMC3083558 DOI: 10.1186/1758-2946-3-s1-o5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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32
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Affiliation(s)
- Andrew R Leach
- Computational and Structural Chemistry, GlaxoSmithKline Research & Development, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, UK.
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33
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Moffat K, Gillet VJ, Whittle M, Bravi G, Leach AR. A Comparison of Field-Based Similarity Searching Methods: CatShape, FBSS, and ROCS. J Chem Inf Model 2008; 48:719-29. [DOI: 10.1021/ci700130j] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kirstin Moffat
- Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom, and GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, United Kingdom
| | - Valerie J. Gillet
- Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom, and GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, United Kingdom
| | - Martin Whittle
- Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom, and GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, United Kingdom
| | - Gianpaolo Bravi
- Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom, and GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, United Kingdom
| | - Andrew R. Leach
- Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom, and GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, United Kingdom
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34
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Senger S, Leach AR. SAR Knowledge Bases in Drug Discovery. ACTA ACUST UNITED AC 2008. [DOI: 10.1016/s1574-1400(08)00011-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
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35
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Leach AR. A Survey of Methods for Searching the Conformational Space of Small and Medium-Sized Molecules. Reviews in Computational Chemistry 2007. [DOI: 10.1002/9780470125793.ch1] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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Affiliation(s)
- Andrew R Leach
- GlaxoSmithKline Pharmaceuticals, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, USA
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37
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Watson NS, Brown D, Campbell M, Chan C, Chaudry L, Convery MA, Fenwick R, Hamblin JN, Haslam C, Kelly HA, King NP, Kurtis CL, Leach AR, Manchee GR, Mason AM, Mitchell C, Patel C, Patel VK, Senger S, Shah GP, Weston HE, Whitworth C, Young RJ. Design and synthesis of orally active pyrrolidin-2-one-based factor Xa inhibitors. Bioorg Med Chem Lett 2006; 16:3784-8. [PMID: 16697194 DOI: 10.1016/j.bmcl.2006.04.053] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2006] [Revised: 04/12/2006] [Accepted: 04/15/2006] [Indexed: 10/24/2022]
Abstract
A series of novel, non-basic 3-(6-chloronaphth-2-ylsulfonyl)aminopyrrolidin-2-one-based factor Xa (fXa) inhibitors, incorporating an alanylamide P4 group, was designed and synthesised. Within this series, the N-2-(morpholin-4-yl)-2-oxoethyl derivative 24 was shown to be a potent, selective fXa inhibitor with good anticoagulant activity. Moreover, 24 possessed highly encouraging rat and dog pharmacokinetic profiles with excellent oral bioavailabilities in both species.
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Affiliation(s)
- Nigel S Watson
- GlaxoSmithKline, Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, UK.
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Abstract
There are clearly many different philosophies associated with adapting fragment screening into mainstream Drug Discovery Lead Generation strategies. Scientists at Astex, for instance, focus entirely on strategies involving use of X-ray crystallography and NMR. However, AstraZeneca uses a number of different fragment screening strategies. One approach is to screen a 2000 compound fragment set (with close to "lead-like" complexity) at 100 microM in parallel with every HTS such that the data are obtained on the entire screening collection at 10 microM plus the extra samples at 100 microM; this provides valuable compound potency data in a concentration range that is usually unexplored. The fragments are then screen-specific "privileged structures" that can be searched for in the rest of the HTS output and other databases as well as having synthesis follow-up. A typical workflow for a fragment screen within AstraZeneca is shown below (Figure 24) and highlights the desirability (particularly when screening >100 microM) for NMR and X-ray information to validate weak hits and give information on how to optimise them. In this chapter, we have provided an introduction to the theoretical and practical issues associated with the use of fragment methods and lead-likeness. Fragment-based approaches are still in an early stage of development and are just one of many interrelated techniques that are now used to identify novel lead compounds for drug development. Fragment based screening has some advantages, but like every other drug hunting strategy will not be universally applicable. There are in particular some practical challenges associated with fragment screening that relate to the generally lower level of potency that such compounds initially possess. Considerable synthetic effort has to be applied for post-fragment screening to build the sort of potency that would be expected to be found from a traditional HTS. However, if there are no low-hanging fruit in a screening collection to be found by HTS then the use of fragment screening can help find novelty that may lead to a target not being discarded as intractable. As such, the approach offers some significant advantages by providing less complex molecules, which may have better potential for novel drug optimisation and by enabling new chemical space to be more effectively explored. Many literature examples that cover examples of fragment screening approaches are still at the "proof of concept" stage and although delivering inhibitors or ligands, may still prove to be unsuitable when further ADMET and toxicity profiling is done. The next few years should see a maturing of the area, and as our understanding of how the concepts can be best applied, there are likely to be many more examples of attractive, small molecule hits, leads and candidate drugs derived from the approaches described.
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Affiliation(s)
- Andrew R Leach
- GlaxoSmithKline Research and Development, Gunnels Wood Road, Stevenage, Herts, UK
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41
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Smith R, Hubbard RE, Gschwend DA, Leach AR, Good AC. Analysis and optimization of structure-based virtual screening protocols. (3). New methods and old problems in scoring function design. J Mol Graph Model 2003; 22:41-53. [PMID: 12798390 DOI: 10.1016/s1093-3263(03)00125-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Scoring function research remains a primary focus of current structure-based virtual screening (SVS) technology development. Here, we present an alternative method for scoring function design that attempts to combine crystallographic structural information with data derived from directly within SVS calculations. The technique utilizes a genetic algorithm (GA) to optimize functions based on binding property data derived from multiple virtual screening calculations. These calculations are undertaken on protein data bank (PDB) complex active sites using ligands of known binding mode in conjunction with "noise" compounds. The advantages of such an approach are that the function does not rely on assay data and that it can potentially use the "noise" binding data to recognize the sub-optimal docking interactions inherent in SVS calculations. Initial efforts in technique exploration using DOCK are presented, with comparisons made to existing DOCK scoring functions. An analysis of the problems inherent to scoring function development is also made, including issues in dataset creation and limitations in descriptor utility when viewed from the perspective of docking mode resolution. The future directions such studies might take are also discussed in detail.
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Affiliation(s)
- Ryan Smith
- York Structural Biology Laboratory, Department of Chemistry, University of York, Heslington, York, YO10 4DD, UK
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Abstract
Three commercially available pharmacophore generation programs, Catalyst/HipHop, DISCO and GASP, were compared on their ability to generate known pharmacophores deduced from protein-ligand complexes extracted from the Protein Data Bank. Five different protein families were included Thrombin, Cyclin Dependent Kinase 2, Dihydrofolate Reductase, HIV Reverse Transcriptase and Thermolysin. Target pharmacophores were defined through visual analysis of the data sets. The pharmacophore models produced were evaluated qualitatively through visual inspection and according to their ability to generate the target pharmacophores. Our results show that GASP and Catalyst outperformed DISCO at reproducing the five target pharmacophores.
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Affiliation(s)
- Yogendra Patel
- Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield S10 2TN, United Kingdom
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43
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Leach AR, Smellie AS. A combined model-building and distance-geometry approach to automated conformational analysis and search. ACTA ACUST UNITED AC 2002. [DOI: 10.1021/ci00008a019] [Citation(s) in RCA: 18] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Jordan SN, Leach AR, Bradshaw J. The Application of Neural Networks in Conformational Analysis. 1. Prediction of Minimum and Maximum Interatomic Distances. ACTA ACUST UNITED AC 2002. [DOI: 10.1021/ci00025a035] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Harper G, Bradshaw J, Gittins JC, Green DV, Leach AR. Prediction of biological activity for high-throughput screening using binary kernel discrimination. J Chem Inf Comput Sci 2001; 41:1295-300. [PMID: 11604029 DOI: 10.1021/ci000397q] [Citation(s) in RCA: 65] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
High-throughput screening has made a significant impact on drug discovery, but there is an acknowledged need for quantitative methods to analyze screening results and predict the activity of further compounds. In this paper we introduce one such method, binary kernel discrimination, and investigate its performance on two datasets; the first is a set of 1650 monoamine oxidase inhibitors, and the second a set of 101 437 compounds from an in-house enzyme assay. We compare the performance of binary kernel discrimination with a simple procedure which we call "merged similarity search", and also with a feedforward neural network. Binary kernel discrimination is shown to perform robustly with varying quantities of training data and also in the presence of noisy data. We conclude by highlighting the importance of the judicious use of general pattern recognition techniques for compound selection.
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Affiliation(s)
- G Harper
- GlaxoSmithKline Research and Development, Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, U.K.
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Hann MM, Leach AR, Harper G. Molecular complexity and its impact on the probability of finding leads for drug discovery. J Chem Inf Comput Sci 2001; 41:856-64. [PMID: 11410068 DOI: 10.1021/ci000403i] [Citation(s) in RCA: 570] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Using a simple model of ligand-receptor interactions, the interactions between ligands and receptors of varying complexities are studied and the probabilities of binding calculated. It is observed that as the systems become more complex the chance of observing a useful interaction for a randomly chosen ligand falls dramatically. The implications of this for the design of combinatorial libraries is explored. A large set of drug leads and optimized compounds is profiled using several different properties relevant to molecular recognition. The changes observed for these properties during the drug optimization phase support the hypothesis that less complex molecules are more common starting points for the discovery of drugs. An extreme example of the use of simple molecules for directed screening against thrombin is provided.
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Affiliation(s)
- M M Hann
- Computational Chemistry and Informatics Unit, GlaxoSmithKline Medicines Research Centre, Gunnels Wood Road, Stevenage, SG1 2NY, England.
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49
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Leach AR, Green DVS. Computational Chemistry in Lead Identification, Library Design and Lead Optimisation. Molecular Simulation 2001. [DOI: 10.1080/08927020108024199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Abstract
PLUMS is a new method to perform rational monomer selection for combinatorial chemistry libraries. The algorithm has been developed to optimize focused libraries with specific two-dimensional and/or three-dimensional properties. A preliminary step is the identification of those molecules in the initial virtual library which satisfy the imposed property constraints; we define these molecules as the virtual hits. From the virtual hits, PLUMS generates a starting library, which is the true combinatorial library that includes all the virtual hits. Monomers are then removed in an iterative fashion, thus reducing the size of the library. At each iteration, the worst monomer is removed. Each sublibrary is selected using a global scoring function, which balances effectiveness and efficiency. The iterative process continues until one is left with a library that consists entirely of virtual hits. The optimal library, which is the best compromise between effectiveness and efficiency, can then be selected according to the score. During the iterative process, equivalent solutions may well occur and are taken into account by the algorithm, according to a user-defined parameter. The number of monomers for each substitution site and the size of the library are parameters that can be either optimized or used to constrain the selection. The results obtained on two test libraries are presented. PLUMS was compared with genetic algorithms (GA) and monomer frequency analysis (MFA), which are widely used for monomer selection. For the two test libraries, PLUMS and GA gave equivalent results. MFA is the fastest method, but it can give misleading solutions. Possible advantages and disadvantages of the different methods are discussed.
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Affiliation(s)
- G Bravi
- Computational Chemistry and Informatics, Glaxo Wellcome R&D, Medicines Research Centre, Stevenage, Hertfordshire, UK.
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