Virtual Screening and Drug Docking
- 1st Edition, Volume 59 - November 17, 2022
- Imprint: Academic Press
- Editor: Julio Caballero
- Language: English
- Hardback ISBN:9 7 8 - 0 - 3 2 3 - 9 8 5 9 5 - 6
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 8 6 0 5 - 2
Virtual Screening and Drug Docking, Volume 59 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting inter… Read more
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Request a sales quoteVirtual Screening and Drug Docking, Volume 59 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Can docking scoring functions guarantee success in virtual screening?, No dance, no partner! A tale of flexibility in docking and virtual screening, Handling Imbalance Data in Virtual Screening, Rational computational approaches to predict novel drug candidates against leishmaniasis, Virtual screening against Mtb DNA gyrase: Applications and success stories, Using Filters in Virtual Screening: A Brief Guide to Minimize Errors and Maximize Efficiency, and more.
Additional chapters in the new release include Machine Learning and Deep Learning Strategies for Virtual Screening, Applications of the Virtual Screening to find the novel HIV-1 therapeutic agents, and Large-scale screening of small molecules with docking strategies and its impact on drug discovery.
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Annual Reports on Medicinal Chemistry series
- Updated release includes the latest information on Virtual Screening and Drug Docking
Undergraduates, graduates, academics, and researchers in the field of medicinal chemistry
- Cover
- Table of Contents
- Title page
- Copyright
- Contributors
- Preface
- Chapter One: Can docking scoring functions guarantee success in virtual screening?
- Abstract
- 1: Introduction
- 2: Scoring functions
- 3: Classifications of the scoring functions
- 4: Strengths and weaknesses of classical scoring functions
- 5: Comparative studies of scoring functions
- 6: Strategies to improve the performance of scoring functions in virtual screening
- 7: How to choose a scoring function for virtual screening?
- 8: Future perspectives in scoring functions
- 9: Conclusions
- References
- Chapter Two: No dance, no partner! A tale of receptor flexibility in docking and virtual screening
- Abstract
- 1: Introduction
- 2: Theoretical framework
- 3: In silico methods to account for flexibility in molecular recognition
- 4: Conclusions and perspectives
- References
- Chapter Three: Using filters in virtual screening: A comprehensive guide to minimize errors and maximize efficiency
- Abstract
- 1: Introduction
- 2: Chemical space and ligand libraries
- 3: Types of databases for virtual screening
- 4: Ligand library design and selection
- 5: Constructing 3D structures—Ligand preparation
- 6: Druglikeness vs leadlikeness
- 7: Promiscuous inhibitors and frequent hitters
- 8: Knowledge-based filters
- 9: Pre and post VS tools
- 10: Machine learning and future directions
- References
- Chapter Four: Rational computational approaches to predict novel drug candidates against leishmaniasis
- Abstract
- 1: Introduction
- 2: Target-based approaches
- 3: Ligand-based approaches
- 4: Pharmacokinetics simulation
- 5: Conclusion
- Acknowledgments
- References
- Chapter Five: Virtual screening against Mycobacterium tuberculosis DNA gyrase: Applications and success stories
- Abstract
- 1: Introduction
- 2: The Mtb gyrase heterotetramer: Unique catalysis
- 3: Virtual screening in anti-TB drug discovery
- 4: Structure-guided virtual screening
- 5: Ligand-based virtual screening
- 6: Applications of molecular docking: Designing NBTIs
- 7: Docking-based identification of non-fluoroquinolone inhibitors of GyrA
- 8: Conclusion
- References
- Edition: 1
- Volume: 59
- Published: November 17, 2022
- No. of pages (Hardback): 264
- No. of pages (eBook): 264
- Imprint: Academic Press
- Language: English
- Hardback ISBN: 9780323985956
- eBook ISBN: 9780323986052
JC
Julio Caballero
Julio Caballero studied Chemistry at Universidad de La Habana, where he graduated with a Gold Diploma in 2001. In 2002-2004 he worked on protein engineering in the Enzyme Technology Group at Universidad de Matanzas. He began to work on pharmaceutical modeling and artificial intelligence in 2004 and founded the Molecular Modeling Group at the same university. In 2006 he moved to Talca, Chile and began to work at Universidad de Talca. He was incorporated into the Ph.D. program in Applied Sciences in 2008. He completed his Ph.D. degree working in computational biochemistry in 2012 and was appointed as Assistant Professor at Universidad de Talca. Recently, he was promoted to Full Professor at the same university. At this moment Julio Caballero is member of the regular academic staff of Universidad de Talca, head of the department of Bioinformatics, researcher at the ‘Centro de Bioinformática, Simulación y Modelado’ (CBSM), and lecturer of the ‘School of Civil Engineering in Bioinformatics’ at the ‘Faculty of Engineering’ at the same university
Affiliations and expertise
Professor, Universidad de Talca, ChileRead Virtual Screening and Drug Docking on ScienceDirect