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Full Description
Computational and Experimental Approaches in Protein Engineering and Design offers a one-stop resource for students, researchers, and practitioners. Cutting-edge techniques in AI and machine learning applications are expertly covered in the book, empowering readers with the tools they need to tackle modern challenges in biotechnology and therapeutics. Step-by-step protocols provide readers with actionable guidance to transition smoothly from computational modelling to laboratory implementation. The inclusion of real-world case studies makes the theoretical concepts relatable and actionable and immediately applicable to solving complex problems, such as producing protein-based vaccines for immunotherapy.
The book's focus on synthetic biology positions it at the forefront of innovation, appealing to a broad audience, from those involved in tissue engineering to those exploring next-generation therapeutics. With its forward-looking approach, emphasizing machine-learning-driven protein design and nanobody engineering, this book is an indispensable resource for researchers preparing to navigate the future of biotechnology.
Contents
1. Fundamentals of protein structure and function
2. Introduction to the principles of protein engineering
3. Computational methods and tools for protein design and optimization
4. Experimental methods in protein engineering: techniques and applications
5. Engineering antibodies for therapeutic applications
6. Techniques and applications of directed evolution
7. Machine learning and artificial intelligence in protein design
8. Computational protein design for disease mutations and antimicrobial resistance
9. Case studies in protein engineering: successes and challenges
10. Designing protein-based vaccines for immunotherapy
11. Nanobody engineering for next-generation therapeutics
12. Molecular dynamics simulations in protein design and engineering
13. Biophysical characterization methods for evaluating therapeutic proteins
14. Incorporating non-natural amino acids in protein design and expanding the chemical space of proteins.
15. Methods to enhance protein stability and solubility for improved functional efficacy
16. Engineering allosteric regulation and control mechanisms in proteins
17. Design of protein scaffolds for biomaterials and tissue engineering
18. High-throughput screening techniques for identifying therapeutic proteins
19. Advancements in protein conjugation techniques for engineering and design applications
20. Challenges in AI-based approaches for intrinsically disordered proteins
21. The role of machine learning in drug discovery and therapeutic protein design
