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Modeling Peptide-Protein Interactions

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Cover of 'Modeling Peptide-Protein Interactions'

Table of Contents

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    Book Overview
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    Chapter 1 The Usage of ACCLUSTER for Peptide Binding Site Prediction
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    Chapter 2 Detection of Peptide-Binding Sites on Protein Surfaces Using the Peptimap Server
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    Chapter 3 Peptide Suboptimal Conformation Sampling for the Prediction of Protein-Peptide Interactions
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    Chapter 4 Template-Based Prediction of Protein-Peptide Interactions by Using GalaxyPepDock
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    Chapter 5 Application of the ATTRACT Coarse-Grained Docking and Atomistic Refinement for Predicting Peptide-Protein Interactions
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    Chapter 6 Highly Flexible Protein-Peptide Docking Using CABS-Dock
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    Chapter 7 AnchorDock for Blind Flexible Docking of Peptides to Proteins
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    Chapter 8 Information-Driven, Ensemble Flexible Peptide Docking Using HADDOCK
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    Chapter 9 Modeling Peptide-Protein Structure and Binding Using Monte Carlo Sampling Approaches: Rosetta FlexPepDock and FlexPepBind
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    Chapter 10 Flexible Backbone Methods for Predicting and Designing Peptide Specificity
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    Chapter 11 Simplifying the Design of Protein-Peptide Interaction Specificity with Sequence-Based Representations of Atomistic Models
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    Chapter 12 Binding Specificity Profiles from Computational Peptide Screening
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    Chapter 13 Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design
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    Chapter 14 Investigating Protein–Peptide Interactions Using the Schrödinger Computational Suite
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    Chapter 15 Identifying Loop-Mediated Protein–Protein Interactions Using LoopFinder
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    Chapter 16 Protein-Peptide Interaction Design: PepCrawler and PinaColada
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    Chapter 17 Modeling and Design of Peptidomimetics to Modulate Protein–Protein Interactions
Attention for Chapter 8: Information-Driven, Ensemble Flexible Peptide Docking Using HADDOCK
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Chapter title
Information-Driven, Ensemble Flexible Peptide Docking Using HADDOCK
Chapter number 8
Book title
Modeling Peptide-Protein Interactions
Published in
Methods in molecular biology, February 2017
DOI 10.1007/978-1-4939-6798-8_8
Pubmed ID
Book ISBNs
978-1-4939-6796-4, 978-1-4939-6798-8
Authors

Cunliang Geng, Siddarth Narasimhan, João P. G. L. M. Rodrigues, Alexandre M. J. J. Bonvin

Editors

Ora Schueler-Furman, Nir London

Abstract

Modeling protein-peptide interactions remains a significant challenge for docking programs due to the inherent highly flexible nature of peptides, which often adopt different conformations whether in their free or bound forms. We present here a protocol consisting of a hybrid approach, combining the most frequently found peptide conformations in complexes with representative conformations taken from molecular dynamics simulations of the free peptide. This approach intends to broaden the range of conformations sampled during docking. The resulting ensemble of conformations is used as a starting point for information-driven flexible docking with HADDOCK. We demonstrate the performance of this protocol on six cases of increasing difficulty, taken from a protein-peptide benchmark set. In each case, we use knowledge of the binding site on the receptor to drive the docking process. In the majority of cases where MD conformations are added to the starting ensemble for docking, we observe an improvement in the quality of the resulting models.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 12%
Student > Ph. D. Student 6 11%
Student > Doctoral Student 6 11%
Student > Bachelor 5 9%
Student > Master 5 9%
Other 8 14%
Unknown 20 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 25%
Chemistry 5 9%
Agricultural and Biological Sciences 5 9%
Engineering 3 5%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Other 4 7%
Unknown 23 40%