Chapter title |
Modeling Peptide-Protein Structure and Binding Using Monte Carlo Sampling Approaches: Rosetta FlexPepDock and FlexPepBind
|
---|---|
Chapter number | 9 |
Book title |
Modeling Peptide-Protein Interactions
|
Published in |
Methods in molecular biology, February 2017
|
DOI | 10.1007/978-1-4939-6798-8_9 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6796-4, 978-1-4939-6798-8
|
Authors |
Nawsad Alam, Ora Schueler-Furman |
Editors |
Ora Schueler-Furman, Nir London |
Abstract |
Many signaling and regulatory processes involve peptide-mediated protein interactions, i.e., the binding of a short stretch in one protein to a domain in its partner. Computational tools that generate accurate models of peptide-receptor structures and binding improve characterization and manipulation of known interactions, help to discover yet unknown peptide-protein interactions and networks, and bring into reach the design of peptide-based drugs for targeting specific systems of medical interest.Here, we present a concise overview of the Rosetta FlexPepDock protocol and its derivatives that we have developed for the structure-based characterization of peptide-protein binding. Rosetta FlexPepDock was built to generate precise models of protein-peptide complex structures, by effectively addressing the challenge of the considerable conformational flexibility of the peptide. Rosetta FlexPepBind is an extension of this protocol that allows characterizing peptide-binding affinities and specificities of various biological systems, based on the structural models generated by Rosetta FlexPepDock. We provide detailed descriptions and guidelines for the usage of these protocols, and on a specific example, we highlight the variety of different challenges that can be met and the questions that can be answered with Rosetta FlexPepDock. |
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