Full Description
The AI Frontier in Molecular Modeling and Drug Designing aims to provide a comprehensive guide on the application of AI concepts in drug designing, discovery, and molecular modeling. It delves into machine and deep learning techniques that predict structural properties of molecules, identify druggable pockets, and assess physicochemical properties of targets. The book also explores current and potential computational resources to tackle complex biological challenges. Each chapter is enriched with relevant examples, text boxes, and case studies that illustrate the practical application of AI techniques, their outcomes, and the challenges faced during implementation. This resource is tailored for researchers, students, and professionals in both academia and industry, providing them with the latest methodologies, advancements in technology, and practical insights into AI-driven drug research, structural biology, computational biology, and translational science.
Contents
1. Use of AI for computer aided drug designing
2. Use of AI for analysis of biological and chemical databases for drug discovery
3. Deep learning for protein folding
4. Drug target identification and validation using AI
5. AI based target-ligand binding methods
6. Generative models for molecule generation
7. AI enabled virtual screening
8. Natural Language Processing (NLP) for drug discovery
9. Role of AI in predicting drug efficacy and toxicity
10. AI enabled tools used in drug designing
11. AI driven clinical trials
12. AI, network biology and multiomics data in drug discovery
13. AI driven personalized medicine and biomarker discovery
14. AI powered precision oncology
15. AI emergence in nanomedicine, pharmacogenomics and biotechnology
16. AI in medical image processing and translational science
