SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets
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Ali F. Alsulami | T. Blundell | Ismail Moghul | Arian Jamasb | P. Torres | Christopher A. Beaudoin | Liviu Copoiu | Sherine E. Thomas | Bridget P. Bannerman | S. Vedithi | S. E. Thomas
[1] R. Vyas,et al. Molecular docking and simulation studies on SARS-CoV-2 Mpro reveals Mitoxantrone, Leucovorin, Birinapant, and Dynasore as potent drugs against COVID-19 , 2020, Journal of biomolecular structure & dynamics.
[2] N. Campillo,et al. COVID-19: Drug Targets and Potential Treatments , 2020, Journal of medicinal chemistry.
[3] Mayya Sedova,et al. Coronavirus3D: 3D structural visualization of COVID-19 genomic divergence , 2020, Bioinform..
[4] S. Hasnain,et al. SARS-CoV-2 and COVID-19: A genetic, epidemiological, and evolutionary perspective , 2020, Infection, Genetics and Evolution.
[5] Thomas Becker,et al. Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2 , 2020, Science.
[6] Fang Li,et al. Cell entry mechanisms of SARS-CoV-2 , 2020, Proceedings of the National Academy of Sciences.
[7] R. Berisio,et al. A Structural View of SARS-CoV-2 RNA Replication Machinery: RNA Synthesis, Proofreading and Final Capping , 2020, Cells.
[8] Benjamin J. Polacco,et al. A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug-Repurposing , 2020, Nature.
[9] Dimitry Tegunov,et al. Structure of replicating SARS-CoV-2 polymerase , 2020, Nature.
[10] L. Guddat,et al. Structure of the RNA-dependent RNA polymerase from COVID-19 virus , 2020, Science.
[11] A. Kumari,et al. Identification of potential molecules against COVID-19 main protease through structure-guided virtual screening approach , 2020, Journal of biomolecular structure & dynamics.
[12] Hualiang Jiang,et al. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors , 2020, Nature.
[13] Shangen Zheng,et al. Evaluation of Nucleocapsid and Spike Protein-Based Enzyme-Linked Immunosorbent Assays for Detecting Antibodies against SARS-CoV-2 , 2020, Journal of Clinical Microbiology.
[14] Jon Cohen,et al. Race to find COVID-19 treatments accelerates. , 2020, Science.
[15] A. Walls,et al. Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein , 2020, Cell.
[16] MingKun Li,et al. Genomic diversity of SARS-CoV-2 in Coronavirus Disease 2019 patients , 2020, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
[17] G. Herrler,et al. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor , 2020, Cell.
[18] Kai Zhao,et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin , 2020, Nature.
[19] E. Holmes,et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding , 2020, The Lancet.
[20] David T. Jones,et al. Improved protein structure prediction using potentials from deep learning , 2020, Nature.
[21] K. To,et al. SARS-CoV-2 nsp13, nsp14, nsp15 and orf6 function as potent interferon antagonists , 2020, Emerging microbes & infections.
[22] Marcin J. Skwark,et al. Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation , 2019, Nucleic Acids Res..
[23] J. Gough,et al. The SCOP database in 2020: expanded classification of representative family and superfamily domains of known protein structures , 2019, Nucleic Acids Res..
[24] Astrid Gall,et al. Ensembl 2020 , 2019, Nucleic Acids Res..
[25] Simon C. Potter,et al. The EMBL-EBI search and sequence analysis tools APIs in 2019 , 2019, Nucleic Acids Res..
[26] Entedar A J Alsaadi,et al. Membrane binding proteins of coronaviruses , 2019, Future virology.
[27] Liping He,et al. DeepDDG: Predicting the Stability Change of Protein Point Mutations Using Neural Networks , 2019, J. Chem. Inf. Model..
[28] Ian Sillitoe,et al. CATH: expanding the horizons of structure-based functional annotations for genome sequences , 2018, Nucleic Acids Res..
[29] The UniProt Consortium,et al. UniProt: a worldwide hub of protein knowledge , 2018, Nucleic Acids Res..
[30] Dennis A. Benson,et al. GenBank , 2018, Nucleic Acids Res..
[31] Yutaka Akiyama,et al. Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem , 2018, Comput. Biol. Chem..
[32] Yan Li,et al. Structural model of the SARS coronavirus E channel in LMPG micelles , 2018, Biochimica et Biophysica Acta (BBA) - Biomembranes.
[33] Dominique Douguet,et al. Data Sets Representative of the Structures and Experimental Properties of FDA-Approved Drugs. , 2018, ACS medicinal chemistry letters.
[34] C. Chou,et al. Disulfiram can inhibit MERS and SARS coronavirus papain-like proteases via different modes , 2017, Antiviral Research.
[35] I. Lindberg,et al. Optimization of Substrate‐Analogue Furin Inhibitors , 2017, ChemMedChem.
[36] Yoshimasa Tanaka,et al. TMPRSS2: A potential target for treatment of influenza virus and coronavirus infections , 2017, Biochimie.
[37] Ke Chen,et al. ssbio: A Python Framework for Structural Systems Biology , 2017, bioRxiv.
[38] David Baker,et al. Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta , 2017, Bioinform..
[39] Yuelong Shu,et al. GISAID: Global initiative on sharing all influenza data – from vision to reality , 2017, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.
[40] Dima Kozakov,et al. The ClusPro web server for protein–protein docking , 2017, Nature Protocols.
[41] Timothy P. Levine,et al. Using HHsearch to tackle proteins of unknown function: A pilot study with PH domains , 2016, Traffic.
[42] Yongwook Choi,et al. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels , 2015, Bioinform..
[43] Liming Yan,et al. Structural basis and functional analysis of the SARS coronavirus nsp14–nsp10 complex , 2015, Proceedings of the National Academy of Sciences.
[44] Eugene Krissinel,et al. Stock-based detection of protein oligomeric states in jsPISA , 2015, Nucleic Acids Res..
[45] P. Lackner,et al. MAESTRO - multi agent stability prediction upon point mutations , 2015, BMC Bioinformatics.
[46] S. Genheden,et al. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities , 2015, Expert opinion on drug discovery.
[47] Tom L. Blundell,et al. CHOPIN: a web resource for the structural and functional proteome of Mycobacterium tuberculosis , 2015, Database J. Biol. Databases Curation.
[48] Yanchen Zhou,et al. Protease inhibitors targeting coronavirus and filovirus entry , 2015, Antiviral Research.
[49] B. de Chassey,et al. Virus-host interactomics: new insights and opportunities for antiviral drug discovery , 2014, Genome Medicine.
[50] R. Hilgenfeld. From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design , 2014, The FEBS journal.
[51] Rolf Hilgenfeld,et al. Accessory proteins of SARS-CoV and other coronaviruses , 2014, Antiviral Research.
[52] B. Neuman,et al. Untangling membrane rearrangement in the nidovirales. , 2014, DNA and cell biology.
[53] Douglas E. V. Pires,et al. mCSM: predicting the effects of mutations in proteins using graph-based signatures , 2013, Bioinform..
[54] François Ferron,et al. SARS-CoV ORF1b-encoded nonstructural proteins 12–16: Replicative enzymes as antiviral targets , 2013, Antiviral Research.
[55] Woody Sherman,et al. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments , 2013, Journal of Computer-Aided Molecular Design.
[56] D. Higgins,et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega , 2011, Molecular systems biology.
[57] C. Cole,et al. COSMIC: the catalogue of somatic mutations in cancer , 2011, Genome Biology.
[58] S. Vajda,et al. Blocking eIF4E-eIF4G Interaction as a Strategy To Impair Coronavirus Replication , 2011, Journal of Virology.
[59] Yang Zhang,et al. I-TASSER: a unified platform for automated protein structure and function prediction , 2010, Nature Protocols.
[60] Vincent B. Chen,et al. Correspondence e-mail: , 2000 .
[61] Shibo Jiang,et al. The spike protein of SARS-CoV — a target for vaccine and therapeutic development , 2009, Nature Reviews Microbiology.
[62] Krishna Shankara Narayanan,et al. Severe Acute Respiratory Syndrome Coronavirus nsp1 Suppresses Host Gene Expression, Including That of Type I Interferon, in Infected Cells , 2008, Journal of Virology.
[63] Kenyon G. Daniel,et al. Computational Validation of the Importance of Absolute Stereochemistry in Virtual Screening , 2008, J. Chem. Inf. Model..
[64] K. Henrick,et al. Inference of macromolecular assemblies from crystalline state. , 2007, Journal of molecular biology.
[65] R. Baric,et al. Severe Acute Respiratory Syndrome Coronavirus Evades Antiviral Signaling: Role of nsp1 and Rational Design of an Attenuated Strain , 2007, Journal of Virology.
[66] Silke Stertz,et al. The intracellular sites of early replication and budding of SARS-coronavirus , 2007, Virology.
[67] P. Palese,et al. Severe Acute Respiratory Syndrome Coronavirus Open Reading Frame (ORF) 3b, ORF 6, and Nucleocapsid Proteins Function as Interferon Antagonists , 2006, Journal of Virology.
[68] Stuart G. Siddell,et al. A Contemporary View of Coronavirus Transcription , 2006, Journal of Virology.
[69] Raymond C Stevens,et al. Severe acute respiratory syndrome coronavirus papain-like protease: structure of a viral deubiquitinating enzyme. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[70] Andrei L. Lomize,et al. OPM: Orientations of Proteins in Membranes database , 2006, Bioinform..
[71] Piero Fariselli,et al. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure , 2005, Nucleic Acids Res..
[72] Piero Fariselli,et al. Predicting protein stability changes from sequences using support vector machines , 2005, ECCB/JBI.
[73] J. Ziebuhr,et al. Human Coronavirus 229E Nonstructural Protein 13: Characterization of Duplex-Unwinding, Nucleoside Triphosphatase, and RNA 5′-Triphosphatase Activities , 2004, Journal of Virology.
[74] Matthew P. Repasky,et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. , 2004, Journal of medicinal chemistry.
[75] Alexander E Gorbalenya,et al. Mechanisms and enzymes involved in SARS coronavirus genome expression. , 2003, The Journal of general virology.
[76] Manuel C. Peitsch,et al. SWISS-MODEL: an automated protein homology-modeling server , 2003, Nucleic Acids Res..
[77] P E Bourne,et al. The Protein Data Bank. , 2002, Nucleic acids research.
[78] T L Blundell,et al. FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties. , 2001, Journal of molecular biology.
[79] Alexander D. MacKerell,et al. All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.
[80] Thomas L. Madden,et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.
[81] T. Blundell,et al. Comparative protein modelling by satisfaction of spatial restraints. , 1993, Journal of molecular biology.
[82] Marcin J. Skwark,et al. Mabellini: a genome-wide database for understanding the structural proteome and evaluating prospective antimicrobial targets of the emerging pathogen Mycobacterium abscessus. , 2019 .