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E-grāmata: High Performance Computing for Drug Discovery and Biomedicine

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  • Formāts: EPUB+DRM
  • Sērija : Methods in Molecular Biology 2716
  • Izdošanas datums: 13-Sep-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781071634493
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High Performance Computing for Drug Discovery and BiomedicinePalielināt
  • Formāts: EPUB+DRM
  • Sērija : Methods in Molecular Biology 2716
  • Izdošanas datums: 13-Sep-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781071634493
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This volume explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. The first section collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. The second section delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step and readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. 

Authoritative and practical, High Performance Computing for Drug Discovery and Biomedicine allows a diverse audience, including computer scientists, computational and medicinal chemists, biologists, clinicians, pharmacologists and drug designers, to navigate the complex landscape of what is currently possible and to understand the challenges and future directions of HPC-based technologies.
Introduction to Computational Biomedicine.- Introduction to High
Performance Computing.- Computational Biomedicine (CompBioMed) Centre of
Excellence: Selected Key Achievements.- In Silico Clinical Trials: Is It
Possible?.- Bayesian Optimization in Drug Discovery.- Automated Virtual
Screening.- The Future of Drug Development with Quantum Computing.- Edge,
Fog, and Cloud Against Disease: The Potential of High-Performance Cloud
Computing for Pharma Drug Discovery.- Knowledge Graphs and Their Applications
in Drug Discovery.- Natural Language Processing for Drug Discovery Knowledge
Graphs: Promises and Pitfalls.- Alchemical Free Energy Workflows for the
Computation of Protein-Ligand Binding Affinities.- Molecular Dynamics and
Other HPC Simulations for Drug Discovery.- High Throughput Structure-Based
Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital
Calculations, and Molecular Dynamic Techniques.- HPC Framework for Performing
In Silico Trials Using a 3D Virtual Human Cardiac Population as Means to
Assess Drug-Induced Arrhythmic Risk.- Effect of Muscle Forces on Femur during
Level Walking Using a Virtual Population of Older Women.- Cellular Blood Flow
Modeling with HemoCell.- A Blood Flow Modeling Framework for Stroke
Treatments.- Efficient and Reliable Data Management for Biomedical
Applications.- Accelerating COVID-19 Drug Discovery with High-Performance
Computing.- Teaching Medical Students to Use Supercomputers: A Personal
Reflection.
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