Table of Contents
Part I: Computational Techniques and Approaches1. Introduction to Computational Methods in Medicinal Chemistry, Pharmacology and Toxicology
2. Applications of Machine Learning for Advanced Drug Discovery and Design
3. Exploring Deep Learning Applications in Drug Discovery and Design
4. Pattern Recognition, Molecular Descriptors, Quantum Mechanics, and Representation Methods
5. Exploring Databases Supporting Computational Pharmacology and Toxicology Techniques: An Overview
Part II: Computer Applications in Medicinal Chemistry, Pharmacology and Toxicology: Pharmaceutical, Industrial, and Clinical Settings
6. QSAR and Pharmacophore Modeling in Computational Drug Design
7. Docking in Drug Discovery: Principles, Techniques, and Applications
8. In Silico Molecular Dynamics Simulations
9. Computational Techniques for Enhancing PK/PD Modeling and Simulation and ADMET prediction
10. Predictive Modeling in Toxicology: Unveiling Risks and Ensuring Safety
11. Integrated Network Analysis in Pharmacology: Decoding Interactions and Pathways for Therapeutic Insights
Part III: Future Perspectives on New Technologies in Medicinal Chemistry, Pharmacology and Toxicology
12. An Overview of Computational Tools and Approaches for Green Molecular Design to Minimize Toxicological Risk in Chemical Compounds
13. Big Data in Computational Medicinal Chemistry, Pharmacology and Toxicology, Challenges and Opportunities
14. Development of Next-Generation Tools for Advancing Computational Medicinal Chemistry, Pharmacology and Toxicology
15. Ethical Considerations in Machine Learning and AI for Medicinal Chemistry, Pharmacology and Toxicology
Authors
Muhammad Ishfaq Visiting Research Scientist, Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan, USA.Muhammad Ishfaq holds a Doctor of Veterinary Medicine (DVM), a Master's degree (MSc), and a PhD in basic veterinary medicine, specializing in Veterinary Pharmacology and Toxicology. He was previously an associate professor at Huanggang Normal University, Hubei, China. He is currently a visiting research scientist at the Department of Medicinal Chemistry, University of Michigan in Ann Arbor, Michigan, USA. His research areas of interest are in silico pharmacology, machine learning, computational pharmacology and toxicology, drug targets, QSAR/QSPR modeling, and cheminformatics. Dr. Ishfaq has published several research articles in various prestigious international journals. He has also served as a volunteer reviewer for various international prestigious and peer-reviewed journals. He is currently working on the connection of diseases to specific bio-targets using various cell and tissue cultures, proteomics, bioinformatics, imaging studies, machine learning-based drug discovery and design and the development of cutting-edge technology on AI integrating biomedical big data that search for drugs targeting various diseases to save endangered species. More specifically, he works at the interface of veterinary pharmacology, toxicology, medicinal chemistry, and biodiversity conservation.
