Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics.
1. Computational Approaches in Drug Discovery, Development and Systems Pharmacology - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iv 5. Copyright - p. Page v 6. Contributors - p. Page v 7. Editors biography - p. Page viii 8. List of Illustrations - p. Page x 9. List of Tables - p. Page xi 10. Chapter 1 : In silico pharmacology - p. Page xi 11. Chapter 2 : Computational approaches in drug discovery and design - p. Page 43 12. Chapter 3 : Alternative biological screening methods - p. Page 84 13. Chapter 4 : Artificial intelligence (AI) and machine learning in the treatment of various diseases - p. Page 124 14. Chapter 5 : Pharmacophore modeling - p. Page 156 15. Chapter 6 : Target identification for potential drug discovery - p. Page 176 16. Chapter 7 : New drug discovery pipeline - p. Page 194 17. Chapter 8 : Virtual screening - p. Page 219 18. Chapter 9 : Success stories in computer-aided drug design - p. Page 232 19. Chapter 10 : Computer-aided drug design-based system pharmacology applications for the treatment of diabetes mellitus - p. Page 250 20. Chapter 11 : Computer-aided drug designing illuminate polypharmacology of natural products against multiple estrogen receptor - p. Page 274 21. Index - p. Page 325
Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics.
1. Computational Approaches in Drug Discovery, Development and Systems Pharmacology - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iv 5. Copyright - p. Page v 6. Contributors - p. Page v 7. Editors biography - p. Page viii 8. List of Illustrations - p. Page x 9. List of Tables - p. Page xi 10. Chapter 1 : In silico pharmacology - p. Page xi 11. Chapter 2 : Computational approaches in drug discovery and design - p. Page 43 12. Chapter 3 : Alternative biological screening methods - p. Page 84 13. Chapter 4 : Artificial intelligence (AI) and machine learning in the treatment of various diseases - p. Page 124 14. Chapter 5 : Pharmacophore modeling - p. Page 156 15. Chapter 6 : Target identification for potential drug discovery - p. Page 176 16. Chapter 7 : New drug discovery pipeline - p. Page 194 17. Chapter 8 : Virtual screening - p. Page 219 18. Chapter 9 : Success stories in computer-aided drug design - p. Page 232 19. Chapter 10 : Computer-aided drug design-based system pharmacology applications for the treatment of diabetes mellitus - p. Page 250 20. Chapter 11 : Computer-aided drug designing illuminate polypharmacology of natural products against multiple estrogen receptor - p. Page 274 21. Index - p. Page 325
