Phytochemistry, Computational Tools, and Databases in Drug Discovery: Drug Discovery Update
Editat de Chukwuebuka Egbuna, Mithun Rudrapal, Habibu Tijjanien Limba Engleză Paperback – 4 dec 2022
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.
- Provides the various databases, methods and procedures for computational drug discovery in plants
- Includes insights into the predictors for properties of phytochemicals against different diseases
- Discusses the applications of computational tools and their databases
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Specificații
ISBN-13: 9780323905930
ISBN-10: 0323905935
Pagini: 490
Dimensiuni: 152 x 229 mm
Greutate: 0.65 kg
Editura: ELSEVIER SCIENCE
Seria Drug Discovery Update
ISBN-10: 0323905935
Pagini: 490
Dimensiuni: 152 x 229 mm
Greutate: 0.65 kg
Editura: ELSEVIER SCIENCE
Seria Drug Discovery Update
Public țintă
Drug developers, medicinal chemists, toxicologists, phytochemists, plant biochemists, chemical ecologists, analytical chemists; Industrialists, students, teachers, regulatory agenciesCuprins
1. Phytochemistry, history and progress in drug discovery 2. Trends in modern-day drug discovery and development: a glance in the present millennium 3. Computational phytochemistry, databases and tools 4. Computational approaches in drug discovery from phytochemicals 5. Informatics and database for phytochemical drug discovery 6. In silico approaches in repurposing of bioactive natural products for drug discovery 7. Virtual screening of phytochemicals for drug discovery 8. Roles of metagenomics and metabolomics in computational drug discovery 9. Molecular docking and molecular dynamics in natural products-based drug discovery 10. Computational screening of phytochemicals for antibacterial drug discovery 11. Computational screening of phytochemicals for antiviral drug discovery 12. Computational screening of phytochemicals for antiparasitic drug discovery 13. Computational screening of phytochemicals for antidiabetic drug discovery 14. Computational screening of phytochemicals for anticancer drug discovery 15. Application of artificial intelligence and machine learning in natural products-based drug discovery 16. Roles of AI and machine learning approach in natural products-based drug discovery 17. Application of density functional theory (DFT) and response surface methodology (RSM) in drug discovery 18. Therapeutic potentials of medicinal plants and significance of computational tools in anticancer drug discovery