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High Performance Computing for Drug Discovery and Biomedicine

  • Book
  • © 2024

Overview

Editors:
  1. Alexander Heifetz

    1. In Silico Research and Development, Evotec UK Ltd, Abingdon, UK

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  • Includes cutting-edge techniques
  • Provides step-by-step detail essential for reproducible results
  • Contains key implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 2716)

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Table of contents (20 protocols)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Introduction to Computational Biomedicine

    • Shunzhou Wan, Peter V. Coveney
    Pages 1-13

  3. Introduction to High-Performance Computing

    • Marco Verdicchio, Carlos Teijeiro Barjas
    Pages 15-29

  4. Computational Biomedicine (CompBioMed) Centre of Excellence: Selected Key Achievements

    • Gavin J. Pringle
    Pages 31-49

  5. In Silico Clinical Trials: Is It Possible?

    • Simon Arsène, Yves Parès, Eliott Tixier, Solène Granjeon-Noriot, Bastien Martin, Lara Bruezière et al.
    Pages 51-99

  6. Bayesian Optimization in Drug Discovery

    • Lionel Colliandre, Christophe Muller
    Pages 101-136

  7. Automated Virtual Screening

    • Vladimir Joseph Sykora
    Pages 137-152

  8. The Future of Drug Development with Quantum Computing

    • Bhushan Bonde, Pratik Patil, Bhaskar Choubey
    Pages 153-179

  9. Edge, Fog, and Cloud Against Disease: The Potential of High-Performance Cloud Computing for Pharma Drug Discovery

    • Bhushan Bonde
    Pages 181-202

  10. Knowledge Graphs and Their Applications in Drug Discovery

    • Tim James, Holger Hennig
    Pages 203-221

  11. Natural Language Processing for Drug Discovery Knowledge Graphs: Promises and Pitfalls

    • J. Charles G. Jeynes, Tim James, Matthew Corney
    Pages 223-240

  12. Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities

    • Anna M. Herz, Tahsin Kellici, Inaki Morao, Julien Michel
    Pages 241-264

  13. Molecular Dynamics and Other HPC Simulations for Drug Discovery

    • Martin Kotev, Constantino Diaz Gonzalez
    Pages 265-291

  14. High-Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques

    • Reuben L. Martin, Alexander Heifetz, Mike J. Bodkin, Andrea Townsend-Nicholson
    Pages 293-306

  15. HPC Framework for Performing in Silico Trials Using a 3D Virtual Human Cardiac Population as Means to Assess Drug-Induced Arrhythmic Risk

    • Jazmin Aguado-Sierra, Renee Brigham, Apollo K. Baron, Paula Dominguez Gomez, Guillaume Houzeaux, Jose M. Guerra et al.
    Pages 307-334

  16. Effect of Muscle Forces on Femur During Level Walking Using a Virtual Population of Older Women

    • Zainab Altai, Erica Montefiori, Xinshan Li
    Pages 335-349

  17. Cellular Blood Flow Modeling with HemoCell

    • Gabor Zavodszky, Christian Spieker, Benjamin Czaja, Britt van Rooij
    Pages 351-368

  18. A Blood Flow Modeling Framework for Stroke Treatments

    • Remy Petkantchin, Franck Raynaud, Karim Zouaoui Boudjeltia, Bastien Chopard
    Pages 369-381

  19. Efficient and Reliable Data Management for Biomedical Applications

    • Ivan Pribec, Stephan Hachinger, Mohamad Hayek, Gavin J. Pringle, Helmut Brüchle, Ferdinand Jamitzky et al.
    Pages 383-403

  20. Accelerating COVID-19 Drug Discovery with High-Performance Computing

    • Alexander Heifetz
    Pages 405-411
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Keywords

About this book

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 inMolecular 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.

Editors and Affiliations

  • In Silico Research and Development, Evotec UK Ltd, Abingdon, UK

    Alexander Heifetz

Bibliographic Information

  • Book Title: High Performance Computing for Drug Discovery and Biomedicine

  • Editors: Alexander Heifetz

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-0716-3449-3

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2024

  • Hardcover ISBN: 978-1-0716-3448-6Published: 14 September 2023

  • Softcover ISBN: 978-1-0716-3451-6Due: 15 October 2023

  • eBook ISBN: 978-1-0716-3449-3Published: 13 September 2023

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XIII, 429

  • Topics: Bioinformatics, Pharmacology/Toxicology, Biomedicine, general

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