Cyclic Peptides, Volume 721 covers peptide structures and their enhancement, stability, specificity, and overall functionality. As a growing suite of computational and experimental tools support the discovery and optimization of these molecules, ranging from well-established modeling platforms to emerging deep-learning algorithms that expand design possibilities, this book aims to provide a comprehensive overview of cyclic peptide research, covering fundamental principles, production strategies, and the latest technological advances in both synthetic and computational realms.
Cyclic peptides are a powerful approach to constraining peptide structures, enhancing their stability, specificity, and overall functionality. They can be generated through diverse techniques—including chemical synthesis, mRNA display, and DNA display—that enable the creation of tailored peptide libraries.
1. 1 Introduction - p. 300 2. 2 Software overview - p. 304 3. 3 Extending existing software with Masala: Masala for Rosetta - p. 333 4. 4 Computational benchmarks - p. 349 5. 5 Future extensibility: The roadmap beyond Masala 1.0 - p. 358 6. 6 Conclusion - p. 360 7. Acknowledgements - p. 361 8. References - p. 420 9. Chapter Fourteen: Enzyme-free biochemical production of seamlessly N-to-C cyclized peptides from natural or recombinant proteins - p. 427 10. Chapter Fifteen: Computational cyclic peptide design machine learning & Rosetta based methods - p. 455 11. Chapter Sixteen: Using solution-phase NMR spectroscopy to study the folding and supramolecular assembly of conformationally constrained β-sheet peptides - p. 477
Cyclic Peptides, Volume 721 covers peptide structures and their enhancement, stability, specificity, and overall functionality. As a growing suite of computational and experimental tools support the discovery and optimization of these molecules, ranging from well-established modeling platforms to emerging deep-learning algorithms that expand design possibilities, this book aims to provide a comprehensive overview of cyclic peptide research, covering fundamental principles, production strategies, and the latest technological advances in both synthetic and computational realms.
Cyclic peptides are a powerful approach to constraining peptide structures, enhancing their stability, specificity, and overall functionality. They can be generated through diverse techniques—including chemical synthesis, mRNA display, and DNA display—that enable the creation of tailored peptide libraries.
1. 1 Introduction - p. 300 2. 2 Software overview - p. 304 3. 3 Extending existing software with Masala: Masala for Rosetta - p. 333 4. 4 Computational benchmarks - p. 349 5. 5 Future extensibility: The roadmap beyond Masala 1.0 - p. 358 6. 6 Conclusion - p. 360 7. Acknowledgements - p. 361 8. References - p. 420 9. Chapter Fourteen: Enzyme-free biochemical production of seamlessly N-to-C cyclized peptides from natural or recombinant proteins - p. 427 10. Chapter Fifteen: Computational cyclic peptide design machine learning & Rosetta based methods - p. 455 11. Chapter Sixteen: Using solution-phase NMR spectroscopy to study the folding and supramolecular assembly of conformationally constrained β-sheet peptides - p. 477
