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Author: Hongbin Wan
Publisher:
ISBN:
Category :
Languages : en
Pages : 166
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Book Description
Molecular dynamics (MD) simulation is a powerful tool enabling researchers to gain insight into biological processes at the atomic level. There have been many advancements in both hardware and software in the last decade to both accelerate MD simulations and increase their predictive accuracy; however, MD simulations are typically limited to the microsecond timescale, whereas biological motions can take seconds or longer. Because of this, it remains extremely challenging to restrain simulations using ensemble-averaged experimental observables. Among various approaches to elucidate the kinetics of molecular simulations, Markov State Models (MSMs) have proven their ability to extract both kinetic and thermodynamic properties of long-timescale motions using ensembles of shorter MD simulation trajectories. In this dissertation, we have implemented an MSM path-entropy method, based on the idea of maximum-caliber, to efficiently predict the changes in protein folding behavior upon mutation. Next, we explore the accuracy of different MSM estimators applied to trajectory data obtained by adaptive seeding, in which new rounds of short MD simulations are collected from states of interest, and propose a simple method to build accurate models by population re-weighting of the transition count matrix. Finally, we explore ways to reconcile simulated ensembles with Hydrogen/Deuterium exchange (HDX) protection measurements, by constructing multi-ensemble Markov State Models (MEMMs) from biased MD simulations, and reconciling these predictions against the experimental data using the BICePs (Bayesian Inference of Conformational Populations) algorithm. We apply this approach to model the native-state conformational ensemble of apomyoglobin at neutral pH.
Author: Hongbin Wan
Publisher:
ISBN:
Category :
Languages : en
Pages : 166
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Book Description
Molecular dynamics (MD) simulation is a powerful tool enabling researchers to gain insight into biological processes at the atomic level. There have been many advancements in both hardware and software in the last decade to both accelerate MD simulations and increase their predictive accuracy; however, MD simulations are typically limited to the microsecond timescale, whereas biological motions can take seconds or longer. Because of this, it remains extremely challenging to restrain simulations using ensemble-averaged experimental observables. Among various approaches to elucidate the kinetics of molecular simulations, Markov State Models (MSMs) have proven their ability to extract both kinetic and thermodynamic properties of long-timescale motions using ensembles of shorter MD simulation trajectories. In this dissertation, we have implemented an MSM path-entropy method, based on the idea of maximum-caliber, to efficiently predict the changes in protein folding behavior upon mutation. Next, we explore the accuracy of different MSM estimators applied to trajectory data obtained by adaptive seeding, in which new rounds of short MD simulations are collected from states of interest, and propose a simple method to build accurate models by population re-weighting of the transition count matrix. Finally, we explore ways to reconcile simulated ensembles with Hydrogen/Deuterium exchange (HDX) protection measurements, by constructing multi-ensemble Markov State Models (MEMMs) from biased MD simulations, and reconciling these predictions against the experimental data using the BICePs (Bayesian Inference of Conformational Populations) algorithm. We apply this approach to model the native-state conformational ensemble of apomyoglobin at neutral pH.
Author: Jeanmarie Guenot
Publisher:
ISBN:
Category : Molecular biology
Languages : en
Pages : 842
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Book Description
Author: Derek J. Chadwick
Publisher: John Wiley & Sons
ISBN: 0470514159
Category : Science
Languages : en
Pages : 282
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Book Description
How the amino acid sequence of a protein determines its three-dimensional structure is a major problem in biology and chemistry. Leading experts in the fields of NMR spectroscopy, X-ray crystallography, protein engineering and molecular modeling offer provocative insights into current views on the protein folding problem and various aspects for future progress.
Author: Valerie Daggett
Publisher: Elsevier
ISBN: 0080493785
Category : Medical
Languages : en
Pages : 477
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Book Description
Protein Simulation focuses on predicting how protein will act in vivo. These studies use computer analysis, computer modeling, and statistical probability to predict protein function. * Force Fields* Ligand Binding* Protein Membrane Simulation* Enzyme Dynamics* Protein Folding and unfolding simulations
Author: Brandon Mac Butler
Publisher:
ISBN:
Category : DNA-protein interactions
Languages : en
Pages : 135
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Book Description
Proteins are essential for most biological processes that constitute life. The function of a protein is encoded within its 3D folded structure, which is determined by its sequence of amino acids. A variation of a single nucleotide in the DNA during transcription (nSNV) can alter the amino acid sequence (i.e., a mutation in the protein sequence), which can adversely impact protein function and sometimes cause disease. These mutations are the most prevalent form of variations in humans, and each individual genome harbors tens of thousands of nSNVs that can be benign (neutral) or lead to disease. The primary way to assess the impact of nSNVs on function is through evolutionary approaches based on positional amino acid conservation. These approaches are largely inadequate in the regime where positions evolve at a fast rate. We developed a method called dynamic flexibility index (DFI) that measures site-specific conformational dynamics of a protein, which is paramount in exploring mechanisms of the impact of nSNVs on function. In this thesis, we demonstrate that DFI can distinguish the disease-associated and neutral nSNVs, particularly for fast evolving positions where evolutionary approaches lack predictive power. We also describe an additional dynamics-based metric, dynamic coupling index (DCI), which measures the dynamic allosteric residue coupling of distal sites on the protein with the functionally critical (i.e., active) sites. Through DCI, we analyzed 200 disease mutations of a specific enzyme called GCase, and a proteome-wide analysis of 75 human enzymes containing 323 neutral and 362 disease mutations. In both cases we observed that sites with high dynamic allosteric residue coupling with the functional sites (i.e., DARC spots) have an increased susceptibility to harboring disease nSNVs. Overall, our comprehensive proteome-wide analysis suggests that incorporating these novel position-specific conformational dynamics based metrics into genomics can complement current approaches to increase the accuracy of diagnosing disease nSNVs. Furthermore, they provide mechanistic insights about disease development. Lastly, we introduce a new, purely sequence-based model that can estimate the dynamics profile of a protein by only utilizing coevolution information, eliminating the requirement of the 3D structure for determining dynamics.
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.
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.
Author: Qiang Cui
Publisher: CRC Press
ISBN: 142003507X
Category : Mathematics
Languages : en
Pages : 448
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Book Description
Rapid developments in experimental techniques continue to push back the limits in the resolution, size, and complexity of the chemical and biological systems that can be investigated. This challenges the theoretical community to develop innovative methods for better interpreting experimental results. Normal Mode Analysis (NMA) is one such technique
Author: Ke-li Han
Publisher: Springer Science & Business Media
ISBN: 3319029703
Category : Medical
Languages : en
Pages : 488
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Book Description
This book discusses how biological molecules exert their function and regulate biological processes, with a clear focus on how conformational dynamics of proteins are critical in this respect. In the last decade, the advancements in computational biology, nuclear magnetic resonance including paramagnetic relaxation enhancement, and fluorescence-based ensemble/single-molecule techniques have shown that biological molecules (proteins, DNAs and RNAs) fluctuate under equilibrium conditions. The conformational and energetic spaces that these fluctuations explore likely contain active conformations that are critical for their function. More interestingly, these fluctuations can respond actively to external cues, which introduces layers of tight regulation on the biological processes that they dictate. A growing number of studies have suggested that conformational dynamics of proteins govern their role in regulating biological functions, examples of this regulation can be found in signal transduction, molecular recognition, apoptosis, protein / ion / other molecules translocation and gene expression. On the experimental side, the technical advances have offered deep insights into the conformational motions of a number of proteins. These studies greatly enrich our knowledge of the interplay between structure and function. On the theoretical side, novel approaches and detailed computational simulations have provided powerful tools in the study of enzyme catalysis, protein / drug design, protein / ion / other molecule translocation and protein folding/aggregation, to name but a few. This work contains detailed information, not only on the conformational motions of biological systems, but also on the potential governing forces of conformational dynamics (transient interactions, chemical and physical origins, thermodynamic properties). New developments in computational simulations will greatly enhance our understanding of how these molecules function in various biological events.
Author: F. Hirata
Publisher: Springer Science & Business Media
ISBN: 1402025904
Category : Science
Languages : en
Pages : 366
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Book Description
Molecular Theory of Solvation presents the recent progress in the statistical mechanics of molecular liquids applied to the most intriguing problems in chemistry today, including chemical reactions, conformational stability of biomolecules, ion hydration, and electrode-solution interface. The continuum model of "solvation" has played a dominant role in describing chemical processes in solution during the last century. This book discards and replaces it completely with molecular theory taking proper account of chemical specificity of solvent. The main machinery employed here is the reference-interaction-site-model (RISM) theory, which is combined with other tools in theoretical chemistry and physics: the ab initio and density functional theories in quantum chemistry, the generalized Langevin theory, and the molecular simulation techniques. This book will be of benefit to graduate students and industrial scientists who are struggling to find a better way of accounting and/or predicting "solvation" properties.
