Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology

Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology PDF Author: Kyle Barlow
Publisher:
ISBN: 9780355386370
Category :
Languages : en
Pages : 99

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Book Description
As the prior state-of-the-art methods for prediction of change in protein-protein interface binding energy post-mutation were not very effective for predicting mutations to side chains other than alanine, I created a new, more general Rosetta method for prediction of these cases. This "flex ddG" method generates and utilizes ensembles of diverse protein conformational states (generated with "backrub" sampling) to predict interface DeltaDeltaG values. Flex ddG is effective for prediction of change in binding free energy post-mutation for mutations to all amino acids, including mutations to alanine, and is particularly effective (when compared to prior methods) for cases of small side chain to large side chain mutations. I show that the method succeeds in these cases due to increased sampling of diverse conformational states, as performance improves (to a threshold) as more diverse states are sampled.

Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology

Increasing the Complexity of Computational Protein Modeling Methodologies for Functional Applications in Biology PDF Author: Kyle Barlow
Publisher:
ISBN: 9780355386370
Category :
Languages : en
Pages : 99

Get Book Here

Book Description
As the prior state-of-the-art methods for prediction of change in protein-protein interface binding energy post-mutation were not very effective for predicting mutations to side chains other than alanine, I created a new, more general Rosetta method for prediction of these cases. This "flex ddG" method generates and utilizes ensembles of diverse protein conformational states (generated with "backrub" sampling) to predict interface DeltaDeltaG values. Flex ddG is effective for prediction of change in binding free energy post-mutation for mutations to all amino acids, including mutations to alanine, and is particularly effective (when compared to prior methods) for cases of small side chain to large side chain mutations. I show that the method succeeds in these cases due to increased sampling of diverse conformational states, as performance improves (to a threshold) as more diverse states are sampled.

Introduction to Protein Structure Prediction

Introduction to Protein Structure Prediction PDF Author: Huzefa Rangwala
Publisher: John Wiley & Sons
ISBN: 111809946X
Category : Science
Languages : en
Pages : 611

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Book Description
A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.

Algorithms in Computational Molecular Biology

Algorithms in Computational Molecular Biology PDF Author: Mourad Elloumi
Publisher: John Wiley & Sons
ISBN: 1118101987
Category : Science
Languages : en
Pages : 1027

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Book Description
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.

Protein Design

Protein Design PDF Author: Raphael Guerois
Publisher: Springer Science & Business Media
ISBN: 1597451169
Category : Science
Languages : en
Pages : 303

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Book Description
Protein Design: Methods and Applications presents the most up-to-date protein design and engineering strategies so that readers can undertake their own projects with a maximum chance of success. The authors present integrated computational approaches that require various degrees of computational complexity, and the major accomplishments that have been achieved in the design and structural characterization of helical peptides and proteins.

Computational Methods for Protein Structure Prediction and Modeling

Computational Methods for Protein Structure Prediction and Modeling PDF Author: Ying Xu
Publisher: Springer Science & Business Media
ISBN: 0387688250
Category : Science
Languages : en
Pages : 335

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Book Description
Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

Computational Protein Design

Computational Protein Design PDF Author: Ilan Samish
Publisher: Humana
ISBN: 9781493966356
Category : Science
Languages : en
Pages : 0

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Book Description
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.

Protein Function Prediction for Omics Era

Protein Function Prediction for Omics Era PDF Author: Daisuke Kihara
Publisher: Springer Science & Business Media
ISBN: 9400708815
Category : Medical
Languages : en
Pages : 316

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Book Description
Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred

Computational Methods for Protein Structure Prediction and Modeling

Computational Methods for Protein Structure Prediction and Modeling PDF Author: Ying Xu
Publisher: Springer Science & Business Media
ISBN: 0387683720
Category : Science
Languages : en
Pages : 408

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Book Description
Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.

Computational Methods for Understanding Complexity: The Use of Formal Methods in Biology

Computational Methods for Understanding Complexity: The Use of Formal Methods in Biology PDF Author: David A. Rosenblueth,
Publisher: Frontiers Media SA
ISBN: 2889450422
Category :
Languages : en
Pages : 115

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Book Description
The complexity of living organisms surpasses our unaided habilities of analysis. Hence, computational and mathematical methods are necessary for increasing our understanding of biological systems. At the same time, there has been a phenomenal recent progress allowing the application of novel formal methods to new domains. This progress has spurred a conspicuous optimism in computational biology. This optimism, in turn, has promoted a rapid increase in collaboration between specialists of biology with specialists of computer science. Through sheer complexity, however, many important biological problems are at present intractable, and it is not clear whether we will ever be able to solve such problems. We are in the process of learning what kind of model and what kind of analysis and synthesis techniques to use for a particular problem. Some existing formalisms have been readily used in biological problems, others have been adapted to biological needs, and still others have been especially developed for biological systems. This Research Topic has examples of cases (1) employing existing methods, (2) adapting methods to biology, and (3) developing new methods. We can also see discrete and Boolean models, and the use of both simulators and model checkers. Synthesis is exemplified by manual and by machine-learning methods. We hope that the articles collected in this Research Topic will stimulate new research.

Multiscale Approaches to Protein Modeling

Multiscale Approaches to Protein Modeling PDF Author: Andrzej Kolinski
Publisher: Springer Science & Business Media
ISBN: 144196889X
Category : Science
Languages : en
Pages : 360

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Book Description
The book gives a comprehensive review of the most advanced multiscale methods for protein structure prediction, computational studies of protein dynamics, folding mechanisms and macromolecular interactions. It approaches span a wide range of the levels of coarse-grained representations, various sampling techniques and variety of applications to biomedical and biophysical problems. This book is intended to be used as a reference book for those who are just beginning their adventure with biomacromolecular modeling but also as a valuable source of detailed information for those who are already experts in the field of biomacromolecular modeling and in related areas of computational biology or biophysics.