Computational Methods in Protein Evolution

Softcover Nachdruck of the original 1. Auflage 2019
ISBN: 978-1-4939-9378-9
Verlag: Springer

Buch, Englisch, Band 1851, 420 Seiten, Paperback, Format (B × H): 178 mm x 254 mm, Gewicht: 1117 g

Reihe: Methods in Molecular Biology

This volume presents a diverse collection of methodologies used to study various problems at the protein sequence and structure level. The chapters in this book look at issues ranging from broad concepts like protein space to specifics like antibody modeling. Topics include point mutations, gene duplication, de novo emergence of new genes, pairwise correlated mutations, ancestral protein reconstruction, homology modelling, protein stability and dynamics, and protein-protein interactions. The book also covers a wide range of computational approaches, including sequence and structure alignments, phylogenies, physics-based and mathematical approaches, machine learning, and more. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and prerequisites, step-by-step, readily reproducible computational protocols (using command line or graphical user interfaces, sometimes including computer code), and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and authoritative, Computational Methods in Protein Evolution is a valuable resource that offers useful workflows and techniques that will help both novice and expert researchers working with proteins computationally.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Sikosek, Tobias

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Naturwissenschaften Biowissenschaften Proteinforschung
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik

Inhaltsverzeichnis

Predicting the Effect of Mutations on Protein Folding and Protein-Protein Interactions.- Accurate Calculation of Free Energy Changes Upon Amino Acid Mutation.- Protocols for the Molecular Evolutionary Analysis of Membrane Protein Gene Duplicates.- Computational Prediction of De Novo Emerged Protein-Coding Genes.- Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations.- Detecting Amino Acid Coevolution with Bayesian Graphical Models.- Context-Dependent Mutation Effects in Proteins.- High-Throughput Reconstruction of Ancestral Protein Sequence, Structure, and Molecular Function.- Ancestral Sequence Reconstruction as a Tool for the Elucidation of a Stepwise Evolutionary Adaptation.- Enhancing Statistical Multiple Sequence Alignment and Tree Inference using Structural Information.- The Influence of Protein Stability on Sequence Evolution: Applications to Phylogenetic Inference.- Navigating Among Known Structures in Protein Space.- A Graph-Based Approach for Detecting Sequence Homology in Highly Diverged Repeat-Protein Families.- Exploring Enzyme Evolution from Changes in Sequence, Structure, and Function.- Identification of Protein Homologs and Domain Boundaries by Iterative Sequence Alignment.- A Roadmap to Domain Based Proteomics.- Modelling of Protein Tertiary and Quaternary Structures Based on Evolutionary Information.- Interface-Based Structural Prediction of Novel Host-Pathogen Interactions.- Predicting Functions of Disordered Proteins with MoRFpred.- Exploring Protein Conformational Diversity.- High-Throughput Antibody Structure Modelling and Design using ABodyBuilder.- In Silico Directed Evolution using CADEE.