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Titlebook: Computational Peptide Science; Methods and Protocol Thomas Simonson Book 2022 The Editor(s) (if applicable) and The Author(s), under exclus

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Computational and Experimental Protocols to Study Cyclo-dihistidine Self- and Co-assembly: Minimaliinescence and their ability to self-encapsulate epirubicin, a chemotherapy drug. Here, we provide a detailed description of computational and experimental methodology for the study of cyclo-HH self- and co-assembling mechanisms, photoluminescence, and drug encapsulation properties. We outline the ex
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Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interacti severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines compu
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,Rapid Rational Design of Cyclic Peptides Mimicking Protein–Protein Interfaces,terfaces. The method selects cyclic peptides that structurally match backbone structures of short segments at a protein–protein interface. In a second step, the cyclic peptides act as templates for designed binders by adapting the amino acid side chains to the side chains found in the target complex
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Molecular Simulation of Stapled Peptides,cule drugs, and of designed antibodies. Because of their modest size, the rational design of such peptides is becoming increasingly amenable to computer simulation; multi-microsecond molecular dynamic (MD) simulations are now routinely possible on consumer-grade graphical processors (GPUs). Here, we
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Computational Evolution Protocol for Peptide Design,y is describing accurately the peptide–target interactions at the molecular level. We here review a computational peptide design protocol whose key feature is the use of all-atom explicit solvent molecular dynamics for describing the different peptide–target complexes explored during the optimizatio
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Computational Design of Miniprotein Binders,onal antibodies, they can be designed to bind to therapeutic targets with high affinity, but they are more stable and easier to produce and to administer. In this chapter, we present a structure-based computational generic approach for miniprotein inhibitor design. Specifically, we describe step-by-
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