| Description |
1 online resource (96 p.) |
| Series |
SpringerBriefs in applied sciences and technology |
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SpringerBriefs in applied sciences and technology.
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| Contents |
Intro -- Foreword -- Computers as Primary Tools in Drug Discovery -- Reference -- Acknowledgments -- About This Book: How Should This Text be Read -- Contents -- 1 Introduction -- References -- 2 A European Drug-Discovery Platform: From In Silico to Experimental Validation -- 2.1 Potential Benefits of Virtual Screening and In Silico Experimentation -- 2.2 EXSCALATE4CoV and Accelerated Drug Development -- 2.3 The EXSCALATE Platform -- 2.4 Extreme Scale Simulations: The E4C Big Run -- 2.5 In Vitro and Experimental Evidence -- References |
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3 The Drug Repurposing Strategy in the Exscalate4CoV Project: Raloxifene Clinical Trials -- 3.1 Drug Repurposing for COVID-19 -- 3.2 Therapeutic Potential of Raloxifene -- 3.3 Raloxifene Clinical Trials -- 3.4 Summary -- References -- 4 The High-Performance Computing Resources for the EXSCALATE4CoV Project -- 4.1 Supercomputer Resources -- 4.2 HPC-Layer 5 (HPC5) -- 4.3 CINECA Marconi M100 -- 4.4 Uses of HPC in EXSCALATE4CoV -- 4.4.1 HPC Workflow -- 4.4.2 High-Throughput Virtual Screening -- 4.4.3 The Big Run -- 4.4.4 Molecular Dynamics -- 4.5 Analysis -- 4.6 Summary -- References |
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5 The Impact of the Scientific Metaverse on the Biotech Industry: How Virtual Reality Helped Researchers Fight Back Against COVID-19 -- 6 From Genomes to Variant Interpretations Through Protein Structures -- 6.1 Interpreting Genetic Variants in the Context of Protein Structures -- 6.2 Workflows for Identifying Relevant Variants -- 6.3 From Relevant Variants to Relevant Protein Structures -- 6.4 Variants and Structures in the Context of Protein Environment -- 6.5 What is in the Future? -- References |
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7 The Role of Structural Biology Task Force: Validation of the Binding Mode of Repurposed Drugs Against SARS-CoV-2 Protein Targets -- 7.1 Mpro as a Drug Target: Structural Properties -- 7.2 Known Inhibitors of Mpro Bind into the Active Site -- 7.3 Myricetin Binds Covalently with Cys145 in the MPro Active Site -- 7.4 The Peptidomimetic MG-132 Acts as Dual Inhibitor of Mpro and Cathepsin L -- References -- 8 Drug Discovery and Big Data: From Research to the Community -- 8.1 The Evolution of Clinical Data: From Hand-Written Case Reports to Real-World Data -- 8.2 RWD and Real-World Evidence |
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8.3 The Clinical Trial System is Broken -- 8.4 Advantages of Using RWD -- 8.4.1 Various Stakeholders -- 8.4.2 How the Entire Clinical Trial Process is Affected -- 8.5 RWE Supporting Drug Repositioning -- 8.6 Old Challenges, New Opportunities -- 8.7 Healthcare Analytics Hubs -- References -- 9 Exploiting Drug-Discovery Research for Educational Purposes -- References -- 10 Beyond the Exscalate4CoV Project: LIGATE and REMEDI4ALL Projects -- 10.1 LIGATE (www.ligateproject.eu/) -- 10.1.1 Final Objectives and Anticipated Outcomes -- 10.2 REpurposing MEDIcines for All |
| Summary |
This book highlights the different aspects of the research project E4C Horizon 2020 European Project aimed at fighting the coronavirus by combining the best supercomputing resources and artificial intelligence with state-of-the-art experimental facilities up through clinical validation. Coronavirus disease has become an important public issue across the globe since December 2019. There is an urgent need to develop potent anti-COVID-19 agents for the prevention of the outbreak and stop viral infections. To this aim, a publicprivate consortium composed by European and national infrastructures, center of excellence, universities, and a pharmaceutical company started the E4C Horizon 2020 European Project: Its core idea was to use the EXaSCale smArt pLatform Against paThogEns (EXSCALATE) supercomputing platform for a process known as drug repurposing, namely to identify the most promising safe in man drugs for immediate treatment of the already infected population and then novel pan-coronavirus inhibitors to address future emergencies. This ambitious goal exploited a chemical library of 500 billion molecules, thanks to a processing capacity of more than 3 million molecules per second, made available by the computing power of the EXSCALATE platform |
| Notes |
10.2.1 Final Objectives and Anticipated Outcomes |
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Online resource; title from PDF title page (SpringerLink, viewed May 12, 2023) |
| Subject |
Drugs -- Design -- Data processing
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COVID-19 (Disease) -- Chemotherapy -- Research
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High performance computing.
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Artificial intelligence -- Medical applications.
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Artificial intelligence -- Medical applications
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Drugs -- Design -- Data processing
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High performance computing
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| Form |
Electronic book
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| Author |
Coletti, Silvano
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Bernardi, Gabriella
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| ISBN |
9783031306914 |
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3031306910 |
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