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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 14: Investigating Protein–Peptide Interactions Using the Schrödinger Computational Suite
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Chapter title
Investigating Protein–Peptide Interactions Using the Schrödinger Computational Suite
Chapter number 14
Book title
Modeling Peptide-Protein Interactions
Published in
Methods in molecular biology, February 2017
DOI 10.1007/978-1-4939-6798-8_14
Pubmed ID
28236242
Book ISBNs
978-1-4939-6796-4, 978-1-4939-6798-8
Authors

Jas Bhachoo, Thijs Beuming

Editors

Ora Schueler-Furman, Nir London

Abstract

The Schrödinger software suite contains a broad array of computational chemistry and molecular modeling tools that can be used to study the interaction of peptides with proteins. These include molecular docking using Glide and Piper, relative binding free energy predictions with FEP+, conformational searches using MacroModel and Desmond, and structural refinement using Prime and PrimeX. In this review we provide a comprehensive overview of these tools and describe their potential application in the identification and optimization of peptide ligands for proteins.

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Mendeley readers

The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 110 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 14%
Student > Ph. D. Student 13 12%
Student > Bachelor 12 11%
Researcher 12 11%
Student > Doctoral Student 5 5%
Other 6 5%
Unknown 47 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 15%
Chemistry 14 13%
Pharmacology, Toxicology and Pharmaceutical Science 12 11%
Engineering 3 3%
Agricultural and Biological Sciences 3 3%
Other 12 11%
Unknown 50 45%

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