Phytochemistry, Computational Tools, and Databases in Drug Discovery /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Egbuna, Chukwuebuka (Editor ), Rudrapal, Mithun (Editor ), Tijjani, Habibu (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2023]
Colección:Drug Discovery Update
Temas:
Botanical chemistry > Data processing.
Chimie v�eg�etale > Informatique.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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

Ejemplares similares