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      The BioGRID database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions

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          Abstract

          The BioGRID (Biological General Repository for Interaction Datasets, thebiogrid.org) is an open‐access database resource that houses manually curated protein and genetic interactions from multiple species including yeast, worm, fly, mouse, and human. The ~1.93 million curated interactions in BioGRID can be used to build complex networks to facilitate biomedical discoveries, particularly as related to human health and disease. All BioGRID content is curated from primary experimental evidence in the biomedical literature, and includes both focused low‐throughput studies and large high‐throughput datasets. BioGRID also captures protein post‐translational modifications and protein or gene interactions with bioactive small molecules including many known drugs. A built‐in network visualization tool combines all annotations and allows users to generate network graphs of protein, genetic and chemical interactions. In addition to general curation across species, BioGRID undertakes themed curation projects in specific aspects of cellular regulation, for example the ubiquitin‐proteasome system, as well as specific disease areas, such as for the SARS‐CoV‐2 virus that causes COVID‐19 severe acute respiratory syndrome. A recent extension of BioGRID, named the Open Repository of CRISPR Screens (ORCS, orcs.thebiogrid.org), captures single mutant phenotypes and genetic interactions from published high throughput genome‐wide CRISPR/Cas9‐based genetic screens. BioGRID‐ORCS contains datasets for over 1,042 CRISPR screens carried out to date in human, mouse and fly cell lines. The biomedical research community can freely access all BioGRID data through the web interface, standardized file downloads, or via model organism databases and partner meta‐databases.

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          A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing

          SUMMARY The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption 1,2 . There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.
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            DrugBank 5.0: a major update to the DrugBank database for 2018

            Abstract DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year’s update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education.
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              Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.

              Blockade of programmed death 1 (PD-1), an inhibitory receptor expressed by T cells, can overcome immune resistance. We assessed the antitumor activity and safety of BMS-936558, an antibody that specifically blocks PD-1. We enrolled patients with advanced melanoma, non-small-cell lung cancer, castration-resistant prostate cancer, or renal-cell or colorectal cancer to receive anti-PD-1 antibody at a dose of 0.1 to 10.0 mg per kilogram of body weight every 2 weeks. Response was assessed after each 8-week treatment cycle. Patients received up to 12 cycles until disease progression or a complete response occurred. A total of 296 patients received treatment through February 24, 2012. Grade 3 or 4 drug-related adverse events occurred in 14% of patients; there were three deaths from pulmonary toxicity. No maximum tolerated dose was defined. Adverse events consistent with immune-related causes were observed. Among 236 patients in whom response could be evaluated, objective responses (complete or partial responses) were observed in those with non-small-cell lung cancer, melanoma, or renal-cell cancer. Cumulative response rates (all doses) were 18% among patients with non-small-cell lung cancer (14 of 76 patients), 28% among patients with melanoma (26 of 94 patients), and 27% among patients with renal-cell cancer (9 of 33 patients). Responses were durable; 20 of 31 responses lasted 1 year or more in patients with 1 year or more of follow-up. To assess the role of intratumoral PD-1 ligand (PD-L1) expression in the modulation of the PD-1-PD-L1 pathway, immunohistochemical analysis was performed on pretreatment tumor specimens obtained from 42 patients. Of 17 patients with PD-L1-negative tumors, none had an objective response; 9 of 25 patients (36%) with PD-L1-positive tumors had an objective response (P=0.006). Anti-PD-1 antibody produced objective responses in approximately one in four to one in five patients with non-small-cell lung cancer, melanoma, or renal-cell cancer; the adverse-event profile does not appear to preclude its use. Preliminary data suggest a relationship between PD-L1 expression on tumor cells and objective response. (Funded by Bristol-Myers Squibb and others; ClinicalTrials.gov number, NCT00730639.).
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                Author and article information

                Contributors
                dolinski@princeton.edu
                md.tyers@umontreal.ca
                Journal
                Protein Sci
                Protein Sci
                10.1002/(ISSN)1469-896X
                PRO
                Protein Science : A Publication of the Protein Society
                John Wiley & Sons, Inc. (Hoboken, USA )
                0961-8368
                1469-896X
                23 November 2020
                January 2021
                23 November 2020
                : 30
                : 1 , Tools 2021 ( doiID: 10.1002/pro.v30.1 )
                : 187-200
                Affiliations
                [ 1 ] Lewis‐Sigler Institute for Integrative Genomics Princeton University Princeton New Jersey USA
                [ 2 ] The Lunenfeld‐Tanenbaum Research Institute Mount Sinai Hospital Toronto Ontario Canada
                [ 3 ] Arthur and Sonia Labatt Brain Tumor Research Center and Developmental and Stem Cell Biology The Hospital for Sick Children Toronto Ontario Canada
                [ 4 ] Institute for Research in Immunology and Cancer Université de Montréal Quebec Canada
                Author notes
                [*] [* ] Correspondence

                Kara Dolinski, Lewis‐Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544.

                Email: dolinski@ 123456princeton.edu

                Mike Tyers, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Quebec H3C 3J7, Canada

                Author information
                https://orcid.org/0000-0002-7010-0264
                https://orcid.org/0000-0002-9713-9994
                Article
                PRO3978
                10.1002/pro.3978
                7737760
                33070389
                799ae8fd-ff3f-472e-8f7b-e5c4aa80879e
                © 2020 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 August 2020
                : 09 October 2020
                : 13 October 2020
                Page count
                Figures: 4, Tables: 4, Pages: 14, Words: 9131
                Funding
                Funded by: Canada Research Chair in Systems and Synthetic Biology
                Funded by: Stand Up To Cancer Canada
                Funded by: Genomics Technology Platform Award
                Funded by: Rapid Response Initiative Award
                Funded by: Genome Canada and Genome Quebec
                Funded by: Canadian Institutes of Health Research , open-funder-registry 10.13039/501100000024;
                Award ID: FDN‐167277
                Funded by: National Center For Advancing Translational Sciences of the National Institutes of Health
                Award ID: OT3TR002026
                Funded by: National Institutes of Health Office of Research Infrastructure Programs
                Award ID: R01OD010929
                Categories
                Tools for Protein Science
                Tools for Protein Science
                Custom metadata
                2.0
                January 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.5 mode:remove_FC converted:15.12.2020

                Biochemistry
                biological network,chemical interaction,covid‐19,crispr screen,drug target,genetic interaction,phenotype,post‐translational modification,protein interaction,ubiquitin‐proteasome system

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