Phytochemistry, Computational Tools, and Databases in Drug Discovery /

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 su...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Other Authors:	Egbuna, Chukwuebuka (Editor), Rudrapal, Mithun (Editor), Tijjani, Habibu (Editor)
Format:	eBook
Language:	English
Published:	Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2023]
Series:	Drug Discovery Update
Subjects:	Botanical chemistry > Data processing. Artificial intelligence. Drug Discovery Plants, Medicinal Phytotherapy Databases as Topic Computer Simulation Artificial Intelligence Chimie végétale > Informatique. Plantes médicinales. Phytothérapie. Intelligence artificielle. artificial intelligence. Fitoquímica. Disseny de medicaments. Desenvolupament de medicaments. Quimioinformàtica. Simulació per ordinador. Electronic books. Llibres electrònics.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Intro
Phytochemistry, Computational Tools, and Databases in Drug Discovery
Copyright
Contents
Contributors
Chapter 1: Phytochemistry, history, and progress in drug discovery
Abbreviations
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
1.6.1. Anti-diabetic phytochemicals
1.6.2. Rauwolfia alkaloid
1.6.3. The anti-cancer alkaloids
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
1.9.1. Anti-cancer agents
1.9.2. Hepatoprotective agents
1.9.3. Anti-diabetic agents
1.9.4. Anti-microbial agents
1.10. Conclusion and future prospects
References
Chapter 2: Trends in modern drug discovery and development: A glance in the present millennium
Abbreviations
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
Acknowledgments
References
Chapter 3: Computational phytochemistry, databases, and tools
Abbreviations
3.1. Introduction
3.2. Computational phytochemistry
3.3. Phytochemical or natural product databases
3.3.1. COlleCtion of Open Natural prodUcTs (COCONUT)
3.3.2. African natural products database
3.3.3. Dr. Dukes phytochemical and ethnobotanical databases
3.3.4. IMPPAT (Indian Medicinal Plants, Phytochemistry and Therapeutics)
3.3.5. Alkamid
3.3.6. AntiBase
3.3.7. BioPhytMol
3.3.8. CamMedNP
3.3.9. Carotenoids database
3.4. Computational tools used for phytochemical drug discovery
3.5. Conclusion
References
Chapter 4: Computational approaches in drug discovery from phytochemicals
Abbreviations
4.1. Introduction
4.2. Phytochemicals as leads in drug discovery
4.2.1. Alkaloids
4.2.2. Polyphenols
4.2.3. Saponins
4.2.4. Terpenoids
4.2.5. Organometallous compounds
4.2.6. Case study 1
4.3. Computational-based approaches in phytochemical drug discovery
4.3.1. Data mining and chemoinformatic strategies
4.3.2. Virtual screening of phytochemical databases
4.3.3. Structure and ligand-based approaches
4.3.4. Network pharmacology approaches
4.3.5. Case study 2
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