Protein folding is a process by which a protein structure assumes its functional shape of conformation, and has been the subject of research since the publication of the first software tool for protein structure prediction. Protein folding in silico approaches this issue by introducing an ab initio model that attempts to simulate as far as possible the folding process as it takes place in vivo, and attempts to construct a mechanistic model on the basis of the predictions made. The opening chapters discuss the early stage intermediate and late stage intermediate models, followed by a discussion of structural information that affects the interpretation of the folding process. The second half of the book covers a variety of topics including ligand binding site recognition, the "fuzzy oil drop" model and its use in simulation of the polypeptide chain, and misfolded proteins. The book ends with an overview of a number of other ab initio methods for protein structure predictions and some concluding remarks. Discusses a range of ab initio models for protein structure prediction Introduces a unique model based on experimental observations Describes various methods for the quantitative assessment of the presented models from the viewpoint of information theory
The phenomenon of amyloidosis has attracted the attention of numerous researchers for two main reasons: (1) it involves unexpected changes in protein conformation (without chemical intervention) and (2) has practical implications, such as elucidating the mechanisms which drive neurodegenerative diseases carries. In particular, understanding the process of amyloidosis is a fundamental prerequisite in the search for new, effective drugs and therapies targeting the key area of neurodegenerative diseases. The book proposes a model and a mechanism which explain protein misfolding. The concepts presented are based on a model originally intended to show how proteins attain their native conformations. The model is quantitative in nature and founded upon arguments derived from information theory. It facilitates prediction and simulation of the amyloid fibrillation process. It also identifies progressive changes which occur in native proteins, leading to the emergence of amyloid aggregations.
|Author||: David B. Teplow|
|Publisher||: Academic Press|
|Release Date||: 2020-03-04|
|ISBN 10||: 0128211350|
|Pages||: 300 pages|
Computational Approaches for Understanding Dynamical Systems: Protein Folding and Assembly, Volume 170 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Pairwise-Additive and Polarizable Atomistic Force Fields for Molecular Dynamics Simulations of Proteins, Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers, Enhanced sampling and free energy methods, and much more.
|Author||: Eric J. Sorin|
|Release Date||: 2007|
|Pages||: 348 pages|
The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field.
This book presents applications of bioinformatics tools that experimental research scientists use in "daily practice." Its interdisciplinary approach combines computational and experimental methods to solve scientific problems. The book begins with reviews of computational methods for protein sequence-structure-function analysis, followed by methods that use experimental data obtained in the laboratory to improve functional predictions.
The formation of disulphide bonds is probably the most influential modification of proteins. These bonds are unique among post-translational modifications of proteins as they can covalently link cysteine residues far apart in the primary sequence of a protein. This has the potential to convey stability to otherwise marginally stable structures of proteins. However, the reactivity of cysteines comes at a price: the potential to form incorrect disulphide bonds, interfere with folding, or even cause aggregation. An elaborate set of cellular machinery exists to catalyze and guide this process: facilitating bond formation, inhibiting unwanted pairings and scrutinizing the outcomes. Only in recent years has it become clear how intimately connected this cellular machinery is with protein folding helpers, organellar redox balance and cellular homeostasis as a whole. This book comprehensively covers the basic principles of disulphide bond formation in proteins and describes the enzymes involved in the correct oxidative folding of cysteine-containing proteins. The biotechnological and pharmaceutical relevance of proteins, their variants and synthetic replicates is continuously increasing. Consequently this book is an invaluable resource for protein chemists involved in realted research and production.
Following an overview on proteolytic enzyme assays, this text covers procedures on how to investigate and study proteases. It describes the use of specific restriction proteases as well as inhibitors of proteases to prevent unwanted proteolysis.
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.