Computational Approaches in Drug Discovery, Development and Systems Pharmacology
- 1st Edition - January 26, 2023
- Editors: Rupesh Kumar Gautam, Mohammad Amjad Kamal, Pooja Mittal
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 9 1 3 7 - 7
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 9 3 7 3 - 9
Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discov… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteComputational 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.
- Explains computer use in pharmacology using real-life case studies
- Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research
- Describes the role of AI in pharmacology and applications of CADD in various diseases
Researchers and academics working in the area of CADD, pharmacology and Bioinformatics
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Editors biography
- Chapter 1: In silico pharmacology
- Abstract
- 1: Introduction to in silico studies
- 2: History and evolution of in silico approaches
- 3: In silico local QSAR modeling
- 4: Quantitative structure-activity relationships
- 5: Descriptor-based methods
- 6: Rule-based methods
- 7: In silico pharmacology in target identification
- 8: In silico identification of drug-target interactions
- 9: Software-based calculations of molecular descriptors
- 10: Knowledge-based approaches
- 11: Testing of virtual ligands
- 12: Methods based on ligands
- 13: Target-based methods
- 14: Affinity profiling
- 15: Ligand-based methods
- 16: Methods based on the goal
- 17: Data visualization
- 18: Examples of in silico pharmacology
- 19: Complex property modeling
- 20: Establishing the boundaries of a computer model's usefulness
- 21: Anecdotes and cautionary tales
- 22: Scope, limitations, and current trends
- 23: Applications of in silico pharmacology
- 24: Conclusion and future perspective
- References
- Chapter 2: Computational approaches in drug discovery and design
- Abstract
- 1: Drug discovery and computer-aided drug design
- 2: Introduction to CADD
- 3: Current approaches used in drug designing by using CADD
- 4: CADD concepts and technologies
- 5: Prediction of protein structures through CADD
- 6: Illumination of phytopharmacology of natural products through CADD
- 7: CADD in illustration of phytopharmacology
- 8: CADD in the treatment of diseases
- 9: Assessment of early stage drug toxicity through CADD
- 10: Challenges and problems in CADD- based drug design and discovery
- 11: Conclusion
- Appendix: Supplementary material
- Appendix: Supplementary material
- References
- Chapter 3: Alternative biological screening methods
- Abstract
- 1: Introduction
- 2: High-throughput screening methods
- 3: Docking as an alternative to biological screening
- 4: De novo drug design
- 5: In silico pharmacological drug screening
- 6: Pharmacophore modeling as an alternative approach
- 7: Chemogenomics approaches in drug screening
- 8: Genomics and proteomics in drug discovery and designing
- 9: Conclusion
- References
- Chapter 4: Artificial intelligence (AI) and machine learning in the treatment of various diseases
- Abstract
- 1: Introduction
- 2: Types of artificial intelligence with respect to healthcare
- 3: Role of AI in drug research and development
- 4: Role of AI in detection of diseases
- 5: AI and ML in clinical trial research
- 6: Epidemic outbreak predictions via AI
- 7: Challenges in adopting the AI in healthcare
- 8: Conclusion
- References
- Chapter 5: Pharmacophore modeling
- Abstract
- 1: Introduction to pharmacophore modeling
- 2: Types of pharmacophores
- 3: Selection of pharmacophores
- 4: Pharmacophore-based ligand profiling
- 5: Applications of pharmacophore modeling
- 6: Conclusion and future perspectives
- References
- Chapter 6: Target identification for potential drug discovery
- Abstract
- 1: Introduction
- 2: Strategies for identification of targets
- 3: Advancements in identification of targets
- 4: Application of machine learning for target-drug interaction
- 5: Steps for the in silico target identification
- 6: Target deconvolution for target discovery
- 7: Affinity chromatography methods
- 8: Expression-cloning methods
- 9: Conclusion and future perspective
- References
- Chapter 7: New drug discovery pipeline
- Abstract
- 1: Introduction
- 2: Phases of drug discovery
- 3: Product lifecycle management
- 4: Phases of drug discovery to market
- 5: Why drug development is costly?
- 6: Conclusion
- References
- Chapter 8: Virtual screening
- Abstract
- 1: Introduction
- 2: Structure-based VS
- 3: Molecular docking
- 4: Receptor 3D structures
- 5: Chemical compound library
- 6: Denovo design
- 7: Ligand-based virtual screening
- 8: A suitable biological assay that can be used to determine the efficacy of a drug
- 9: The “Lead” compound in the assay
- 10: The pharmacophore
- 11: Increasing drug affinity for protein targets
- 12: Pharmacophore mapping
- 13: Target-based virtual screening
- 14: Data visualization
- 15: Recent developments and applications of virtual screening
- 16: Conclusion and future prospective
- References
- Further reading
- Chapter 9: Success stories in computer-aided drug design
- Abstract
- 1: Introduction: Definition of CADD and systems pharmacology, the concept of “success stories”
- 2: Methods
- 3: History and development of CADD
- 4: CADD success stories in systems pharmacology
- 5: CADD market analysis
- 6: Discussion
- 7: Conclusion
- References
- Chapter 10: Computer-aided drug design-based system pharmacology applications for the treatment of diabetes mellitus
- Abstract
- 1: Current statistics of diabetes mellitus and major factor involved in its prevalence
- 2: Status of computational system pharmacology (CSP) for different diseases
- 3: Modern computer-aided drug design-based system pharmacology techniques
- 4: Case studies of computational systems pharmacology for diabetes mellitus
- 5: Identification of antidiabetic potential target and lead compounds by computational pharmacology
- 6: Investigation of drug-target-disease pharmacological networks
- 7: Databases to construct drug-target-disease-related networks
- 8: Databases for diseases drugs, phenotypes, and proteins
- 9: Databases for the interactions among drugs, proteins, and diseases
- 10: Computational system pharmacological analysis of drug and selected target networks
- 11: Network pharmacology (NP) for understanding mechanism of diabetes
- References
- Chapter 11: Computer-aided drug designing illuminate polypharmacology of natural products against multiple estrogen receptor
- Abstract
- 1: Background
- 2: Case studies of polypharmacology of natural product against multiple estrogen receptor
- References
- Index
- No. of pages: 362
- Language: English
- Edition: 1
- Published: January 26, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780323991377
- eBook ISBN: 9780323993739
RG
Rupesh Kumar Gautam
Dr. Rupesh K. Gautam is currently working as Professor and Head, Department of Pharmacology, Indore Institute of Pharmacy, Rau, Indore, India. He has more than 14 years of teaching and research experience. He has more than 65 research and review articles to his credit in various journals of repute. He has also published ten books and eighteen book chapters with Elsevier, Springer, Wiley, Scivener, Bentham, NOVA etc. He has filed two patents and registered fourty two copyrights. He has supervised 21 M. Pharm scholars. Dr. Gautam has also received grants from various government agencies/associations for conducting FDP/seminars/conferences/workshops. He has attended and organized several International and National seminar, conferences and workshops as a team member and organizing secretary/coordinator. He has been Guest Editor of Phytomedicine, Current Pharmaceutical Design, Neuroscience and Biobehavioral Reviews, Evidence-Based Complementary and Alternative Medicine and Biomed Research International.
Affiliations and expertise
Department of Pharmacology, Indore Institute of Pharmacy, IIST Campus, Indore (M.P.), IndiaMA
Mohammad Amjad Kamal
Mohammad Amjad Kamal is Distinguished Adjunct Professor at King Fahd Medical Research Center, King Abdulaziz University, Saudi Arabia. Professor Kamal’s overall biochemical research output has culminated in more than 600 publications in journals of international repute and 61 abstracts in international conferences. His research was pivotal in supporting the development of the novel anti-Alzheimer agents from the laboratory to the clinic via collaboration with Dr Nigel H. Greig (United States). He migrated to Australia in 1998 and was awarded a prestigious U2000 Postdoctoral Fellowship in 2000 by the University of Sydney, School of Molecular and Microbial Biosciences.
Affiliations and expertise
King Fahd Medical Research Center (KFMRC), King Abdulaziz University, Jeddah, Saudi ArabiaPM
Pooja Mittal
Dr. Pooja Mittal is currently working as an Associate Professor at Chitkara College of Pharmacy, Chitkara University, Rajpura,Punjab, India. She has 9+ years of experience in teaching and research. Prior to this, she worked at RIMT University, Mandi Gobindgarh (Punjab), Maharishi Markandeshwar University (Sadopur) Ambala (Haryana) and at Baddi University of Emerging Sciences and Technology, Baddi (Solan). She received the travel grant from DST-SERB in 2016 to attend the International Convention of Controlled Release Society, held at Seattle, USA. She received her Ph.D degree from Department of Pharmaceutical Engineering and Technology, IIT (BHU) Varanasi in 2018. She also received the Young Scientist Award- WF from SPER in 2017.
Affiliations and expertise
Chitkara College of Pharmacy Chitkara University, Rajpura, Punjab, IndiaRead Computational Approaches in Drug Discovery, Development and Systems Pharmacology on ScienceDirect