Phytochemistry, Computational Tools, and Databases in Drug Discovery

1st Edition - November 30, 2022
Imprint: Elsevier
Editors: Chukwuebuka Egbuna, Mithun Rudrapal, Habibu Tijjani
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 5 9 3 - 0
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 7 1 6 - 3

Phytochemistry, Computational Tools and Databases in Drug Discovery presents the state-of-the-art in computational methods and techniques for drug discovery studies from medicinal… Read more

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Phytochemistry, Computational Tools and Databases in Drug Discovery presents the state-of-the-art in computational methods and techniques for drug discovery studies from medicinal plants. Various tools and databases for virtual screening and characterization of plant bioactive compounds and their subsequent predictions on biological targets for the discovery of new drugs against specific diseases are presented, along with computational tools for the prediction of the toxic effects of phytochemicals on living systems. The book also provides in-depth insight on the applications of these computational tools as well as the databases that describe the interactions of phytochemicals with diseases along with predictions for druggable bioactive compounds.

Useful for drug developers, medicinal chemists, toxicologists, phytochemists, plant biochemists and analytical chemists, this book clearly presents the various computational techniques, tools and databases for phytochemical research.

Cover
Title page
Table of Contents
Copyright
Contributors
Chapter 1: Phytochemistry, history, and progress in drug discovery
Abstract
1.1: Introduction
1.2: Origin of phytochemistry
1.3: Major events in the 19th century—Discovery of bioactive compounds
1.4: The emergence and use of aspirin
1.5: The emergence of cardioprotective knowledge of plants
1.6: Discovery of phytochemicals in the 20th century
1.7: Molecular techniques and their interrelationship with phytochemistry
1.8: In-silico techniques for detailed study of phytomolecules
1.9: Advancements in phytochemistry in the 21st century
1.10: Conclusion and future prospects
References
Chapter 2: Trends in modern drug discovery and development: A glance in the present millennium
Abstract
2.1: Introduction
2.2: Drug discovery and development in the 20th century
2.3: Recent trends in drug discovery
2.4: Modern drug discovery in the post-genomics era
2.5: Computer-aided drug design
2.6: Ligand-based drug design
2.7: Virtual screening
2.8: Target identification
2.9: Target validation
2.10: Homology modeling
2.11: Artificial intelligence
2.12: Conclusion
References
Chapter 3: Computational phytochemistry, databases, and tools
Abstract
3.1: Introduction
3.2: Computational phytochemistry
3.3: Phytochemical or natural product databases
3.4: Computational tools used for phytochemical drug discovery
3.5: Conclusion
References
Chapter 4: Computational approaches in drug discovery from phytochemicals
Abstract
4.1: Introduction
4.2: Phytochemicals as leads in drug discovery
4.3: Computational-based approaches in phytochemical drug discovery
4.4: Application of computational tools in phytochemical drug discovery
4.5: Conclusion and future perspective
References
Chapter 5: Informatics and databases for phytochemical drug discovery
Abstract
5.1: Introduction
5.2: Informatics in phytochemical drug discovery
5.3: Conclusion and future perspective
References
Chapter 6: In silico approaches in the repurposing of bioactive natural products for drug discovery
Abstract
6.1: Introduction
6.2: Drug repurposing
6.3: Natural products used in drug discovery
6.4: In silico methods used in drug repurposing
6.5: Applications of drug repurposing
6.6: Conclusion and future perspectives
References
Chapter 7: Virtual screening of phytochemicals for drug discovery
Abstract
7.1: Introduction
7.2: Computational approach
7.3: Artificial neural networks
7.4: Databases
7.5: Drug developmental process
7.6: Hyphenated methods for phytochemicals screening
7.7: Conclusion
References
Chapter 8: Roles of metagenomics and metabolomics in computational drug discovery
Abstract
8.1: Introduction
8.2: Computational methods in metagenomics and metabolomics for drug discovery
8.3: Application of metagenomics in drug discovery
8.4: Applications of metabolomics in drug discovery
8.5: Metabolomics approaches and platforms
8.6: Conclusion
References
Chapter 9: Molecular docking and molecular dynamics in natural products-based drug discovery
Abstract
9.1: Introduction
9.2: Structure-based drug design strategies in natural products
9.3: Success of natural products in drug discovery
9.4: Natural products-based drugs
9.5: Case study
9.6: Conclusion and future perspectives
References
Chapter 10: Computational screening of phytochemicals for anti-bacterial drug discovery
Abstract
10.1: Introduction
10.2: Phytochemicals as anti-bacterial agents
10.3: High-performance computational drug discovery
10.4: Computer-aided anti-bacterial drug discovery of phytochemicals
10.5: Conclusion and future perspectives
References
Chapter 11: Computational screening of phytochemicals for anti-viral drug discovery
Abstract
11.1: Introduction
11.2: The place of computational approaches in drug discovery
11.3: Drug screening and ADMET properties
11.4: Data mining and target preparation
11.5: Computational screening
11.6: Machine learning approaches
11.7: Challenges and opportunities in computational screening of phytochemicals
11.8: Future perspectives
11.9: Conclusion
References
Chapter 12: Computational screening of phytochemicals for anti-parasitic drug discovery
Abstract
12.1: Introduction
12.2: Phytochemicals/plant-derived compounds as sources of anti-parasitic drugs
12.3: In silico screening of phytochemicals for anti-parasitic drugs drug discovery
12.4: Conclusion and future perspectives
References
Chapter 13: Computational screening of phytochemicals for anti-diabetic drug discovery
Abstract
13.1: Introduction
13.2: Diabetes characteristics and drug discovery
13.3: Anti-diabetic properties of phytochemicals from natural sources
13.4: Anti-diabetic mechanisms of phytochemicals
13.5: Computational screening of phytochemicals for anti-diabetic drug discovery
13.6: Conclusion and future perspectives
References
Chapter 14: Computational screening of phytochemicals for anti-cancer drug discovery
Abstract
14.1: Introduction
14.2: Computational screening methods
14.3: Identification of anti-cancer properties of phytochemicals
14.4: Conclusion and future perspectives
References
Chapter 15: Application of artificial intelligence and machine learning in natural products-based drug discovery
Abstract
15.1: Introduction
15.2: Use of computational science in drug discovery of natural products
15.3: AI/ML approaches in drug discovery of natural products
15.4: Future perspectives
15.5: Conclusion
References
Chapter 16: Roles of artificial intelligence and machine learning approach in natural products-based drug discovery
Abstract
16.1: Introduction
16.2: Artificial intelligence, machine learning, and computational drug design
16.3: Combinatorial approach of AI, ML, and CADD in NP-based drug discovery
16.4: AI and ML-based tools/databases
16.5: Conclusion
References
Chapter 17: Application of density functional theory (DFT) and response surface methodology (RSM) in drug discovery
Abstract
17.1: Introduction
17.2: Applications of DFT in drug discovery
17.3: Response surface methodology
17.4: Conclusion
References
Chapter 18: Therapeutic potentials of medicinal plants and significance of computational tools in anti-cancer drug discovery
Abstract
18.1: Introduction
18.2: Historical perspectives of phytochemicals in drug discovery
18.3: Classes of phytochemicals
18.4: Medicinal plants (phytochemicals) in cancer treatment and management
18.5: Effects of plant phytochemicals on cancer hallmarks
18.6: Drug discovery: Advent and uses of computational tools in cancer research
18.7: Conclusion and future perspective
References
Index

Chukwuebuka Egbuna

Chukwuebuka Egbuna (PhD) is a chartered chemist and academic researcher. He is a member of the Institute of Chartered Chemists of Nigeria (ICCON), the Nigerian Society of Biochemistry and Molecular Biology (NSBMB), and the Royal Society of Chemistry (RSC) (United Kingdom). Dr. Egbuna is the founder and editor of the Elsevier book series on Drug Discovery Update. The series includes books, monographs, and edited collections from all areas of drug discovery including emerging therapeutic claims for the treatment of diseases. He has published research articles in many international journals of repute and is ranked among the top 500 Nigerian scientists in SciVal/SCOPUS. He has edited more than 25 books with Elsevier, Springer, Wiley, and Taylor & Francis. His most recent book is the three volume Coronavirus Drug Discovery, published by Elsevier. Dr. Egbuna is the founder and the publishing director of IPS Intelligentsia Publishing Services.

Affiliations and expertise

Africa Centre of Excellence in Public Health and Toxicological Research, University of Port Harcourt, Nigeria

Mithun Rudrapal

Mithun Rudrapal, PhD, FIC, FICS, CChem (India), is Associate Professor at the Department of Pharmaceutical Sciences, School of Biotechnology & Pharmaceutical Sciences, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Guntur, India. Dr. Rudrapal has been actively engaged in teaching and research in the field of Pharmaceutical and Allied Sciences for more than 13 years. He has over a hundred publications in peer-reviewed international journals to his credit and has filed a number of Indian and International patents. In addition, Dr. Rudrapal is the author of dozen published or forthcoming books. Dr. Rudrapal works in the areas of Medicinal Chemistry, CADD, Drug Repurposing, Phytochemistry, Herbal Drugs and Dietary Polyphenols.

Affiliations and expertise

Department of Pharmaceutical Sciences School of Biotechnology and Pharmaceutical Sciences, Vignan’s Foundation for Science, Technology & Research, Guntur, India

Habibu Tijjani

Habibu Tijjani works in the Department of Biochemistry, Natural Product Research Laboratory at Bauchi State University Gadau in Nigeria.

Affiliations and expertise

Department of Biochemistry, Natural Product Research Laboratory, Bauchi State University Gadau, Nigeria

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Phytochemistry, Computational Tools, and Databases in Drug Discovery

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Chukwuebuka Egbuna

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