Computational Peptide Science

This volume details current and new computational methodologies to study peptides. Chapters guide readers through antimicrobial peptides, foldability, amyloid sheet formation, membrane-active peptides, organized peptide assemblies, protein-peptide interfaces, prediction of peptide-MHC complexes, advanced free energy simulations for peptide binding, and methods for high throughput peptide or miniprotein design. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials, software, and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.

Authoritative and cutting-edge, Computational Peptides Science: Methods and Protocols aims to provide concepts, methods, and guidelines to help both novices and experienced workers benefit from today's new opportunities and challenges.

Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts

Résumé
Chapters guide readers through antimicrobial peptides, foldability, amyloid sheet formation, membrane-active peptides, organized peptide assemblies, protein-peptide interfaces, prediction of peptide-MHC complexes, advanced free energy simulations for peptide binding, and methods for high throughput peptide or miniprotein design.

Contenu
Machine Learning Prediction of Antimicrobial Peptides.- Tools for Characterizing Proteins: Circular Variance, Mutual Proximity, Chameleon Sequences and Subsequence Propensities.- Exploring the Peptide Potential Of Genomes.- Computational Identification and Design of Complementary -strand Sequences.- Dynamics of Amyloid Formation from Simplified Representation to Atomistic Simulations.- Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes.- Coarse-grain simulations of membrane-adsorbed helical peptides.- Peptide dynamics and metadynamics: leveraging enhanced sampling molecular dynamics to robustly model long-timescale transitions.- Metadynamics Simulations to Study the Structural Ensembles and Binding Processes of Intrinsically Disordered Proteins.- Computational and Experimental Protocols to Study Cyclo-Dihistidine Self- and Co-Assembly: Minimalistic Bio-assemblies with Enhanced Fluorescence and Drug Encapsulation Properties.- Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions.- Rapid Rational Design of Cyclic Peptides Mimicking Protein-Protein Interfaces.- Structural prediction of peptide-MHC binding modes.- Molecular Simulation of Stapled Peptides.- Free Energy-Based Computational Methods for the Study of Protein-Peptide Binding Equilibria.- Computational Evolution Protocol for Peptide Design.-Computational design of miniprotein binders.- Computational Design of LD Motif-Peptides with Improved Recognition of the Focal Adhesion Kinase FAT Domain.- Knowledge-based unfolded state model for protein design.