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Author: Subhadra Thapa
Publisher:
ISBN:
Category : Molecular dynamics
Languages : en
Pages : 0
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Book Description
Peptide self-assembly plays an important role in biomedical and material discovery, offering a promising insight for development of nanostructures, serving as bio-materials for drug delivery. The tendency of peptide aggregating to certain nanostructures help in forming the basis for tissue engineering scaffolds and enabling the development of innovative diagnostic and therapeutic biologics. The designing of peptide through experiment is expensive and time consuming. The virtual screening of natural tendency of peptide aggregation is cost effective to evaluate numerous designs and prioritize synthesis and characterization efforts. We have characterized the propensity of peptide aggregation utilizing the all-atom (AA), and coarse-grained (CG) simulations. We have studied the widely explored di-phenylalanine (FF) and di-Glycine (GG) as a toy model to benchmark the AA and CG simulation. Furthermore, we have investigated the intrinsic properties such as the system size, terminal modification and salinity and their effects in peptide aggregation. We have used the aggregation propensity (AP) metrics to differentiate between the aggregated and non-aggregated structure. We have also proposed the new AP metrics called APcontact which is also able to differentiate between the aggregated and non-aggregated structure.The second project includes the top-down approach to screen the peptideâs tendency to aggregate to the hydrogel like structure. We started with predicting the AP scores for each amino acid using the optimization method, L-BFGS-B, to refine our initially assigned AP values. The initial AP values was assigned based on the physiochemical properties of the amino acids, such as hydrophobicity, aromaticity, polarity, tendency of forming beta-sheets, alpha-helix etc. This allows us to screen the various peptides of varying length and their tendency to aggregate. We further simulate those top list using CG simulation followed by all-atom simulation and the top list of the peptides from the all-atom simulation were further selected for synthesis. The final stage of this research involves the co-assembly of peptides with optimized AP scores to explore the formation of diverse nanostructures These discoveries establish a foundation for prospective virtual screening of nanostructures assembled by peptides and the computer-aided design of biologics.
Author: Subhadra Thapa
Publisher:
ISBN:
Category : Molecular dynamics
Languages : en
Pages : 0
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Book Description
Peptide self-assembly plays an important role in biomedical and material discovery, offering a promising insight for development of nanostructures, serving as bio-materials for drug delivery. The tendency of peptide aggregating to certain nanostructures help in forming the basis for tissue engineering scaffolds and enabling the development of innovative diagnostic and therapeutic biologics. The designing of peptide through experiment is expensive and time consuming. The virtual screening of natural tendency of peptide aggregation is cost effective to evaluate numerous designs and prioritize synthesis and characterization efforts. We have characterized the propensity of peptide aggregation utilizing the all-atom (AA), and coarse-grained (CG) simulations. We have studied the widely explored di-phenylalanine (FF) and di-Glycine (GG) as a toy model to benchmark the AA and CG simulation. Furthermore, we have investigated the intrinsic properties such as the system size, terminal modification and salinity and their effects in peptide aggregation. We have used the aggregation propensity (AP) metrics to differentiate between the aggregated and non-aggregated structure. We have also proposed the new AP metrics called APcontact which is also able to differentiate between the aggregated and non-aggregated structure.The second project includes the top-down approach to screen the peptideâs tendency to aggregate to the hydrogel like structure. We started with predicting the AP scores for each amino acid using the optimization method, L-BFGS-B, to refine our initially assigned AP values. The initial AP values was assigned based on the physiochemical properties of the amino acids, such as hydrophobicity, aromaticity, polarity, tendency of forming beta-sheets, alpha-helix etc. This allows us to screen the various peptides of varying length and their tendency to aggregate. We further simulate those top list using CG simulation followed by all-atom simulation and the top list of the peptides from the all-atom simulation were further selected for synthesis. The final stage of this research involves the co-assembly of peptides with optimized AP scores to explore the formation of diverse nanostructures These discoveries establish a foundation for prospective virtual screening of nanostructures assembled by peptides and the computer-aided design of biologics.
Author: Andrea Magno
Publisher:
ISBN:
Category :
Languages : en
Pages : 153
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Book Description
Author: Riccardo Pellarin
Publisher:
ISBN:
Category :
Languages : en
Pages : 211
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Book Description
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.
Author: Fabio Trovato
Publisher: Frontiers Media SA
ISBN: 2889740250
Category : Science
Languages : en
Pages : 322
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Book Description
Author: Valentina Tozzini
Publisher: Frontiers Media SA
ISBN: 2889661091
Category : Science
Languages : en
Pages : 235
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Book Description
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Author:
Publisher:
ISBN:
Category : Biophysics
Languages : en
Pages : 504
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Book Description
Author: Wenjie Xia
Publisher: Elsevier
ISBN: 0128230533
Category : Technology & Engineering
Languages : en
Pages : 450
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Book Description
Fundamentals of Multiscale Modeling of Structural Materials provides a robust introduction to the computational tools, underlying theory, practical applications, and governing physical phenomena necessary to simulate and understand a wide-range of structural materials at multiple time and length scales. The book offers practical guidelines for modeling common structural materials with well-established techniques, outlining detailed modeling approaches for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, thin films, and more.Computational approaches based on artificial intelligence and machine learning methods as complementary tools to the physics-based multiscale techniques are discussed as are modeling techniques for additively manufactured structural materials. Special attention is paid to how these methods can be used to develop the next generation of sustainable, resilient and environmentally-friendly structural materials, with a specific emphasis on bridging the atomistic and continuum modeling scales for these materials. Synthesizes the latest cutting-edge computational multiscale modeling techniques for an array of structural materials Emphasizes the foundations of the field and offers practical guidelines for modeling material systems with well-established techniques Covers methods for calculating and analyzing mechanical, thermal and transport properties of various structural materials such as metals, cement/concrete, polymers, composites, wood, and more Highlights underlying theory, emerging areas, future directions and various applications of the modeling methods covered Discusses the integration of multiscale modeling and artificial intelligence
Author: Mingzhen Zhang
Publisher:
ISBN:
Category : Aggregation (Chemistry)
Languages : en
Pages : 195
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Book Description
Amyloid aggregation have been implicated in the pathology of many neurodegenerative diseases, including prion disease, Alzheimer's disease (AD), type II diabetes (T2D), and Parkinson disease. Amyloid peptides undergo the nucleation-polymerization aggregation process, during which amyloid peptides experience structural conversions from unstructured monomers to critical nucleus, and eventually to amyloid fibrils containing dominant ß-sheet structures. Such common misfolding and aggregation characteristics, in some cases, drive cross-seeding interactions between amyloid peptides, which play a major role in the progression and transmission between the neurodegenerative diseases. In the experiments, the cross-seeding interactions between amyloid peptides including ß-amyloid (Aß)-islet amyloid peptides (IAPP), Aß-tau, Aß-prion, human IAPP-rat IAPP, and tau-synuclein amyloids have been extensively implicated. However, high-resolution evidence is still unavailable and little is known about how these two peptides interact with each other. In our research, we perform the multiscale molecular simulations to sysmetically study the cross-seeding interactions between different amyloid peptides at the atomic resolution, with the particular focus on the prediction of the atomic structures, the dynamic behavious in bulk and membrane enviroment, and the interface properties of the hIAPP-rIAPP and Aß-hIAPP cross-seeding assemblies. In Chapter I and II, we model and simulate different heteroassemblies formed by the amyloidogenic hIAPP and the nonamyloidogenic rIAPP peptides. The U-shaped hIAPP monomers and oligomers can interact with conformationally similar rIAPP to form stable complexes and to co-assemble into heterogeneous structures via the interfacial hydrogen bonds and hydrophobic contacts at ß-sheet regions. This work demonstrates the existence of cross-interactions between the two different IAPP peptides at the atomic level, providing an improved fundamental understanding of the cross-seeding of different amyloid sequences towards amyloid aggregation and toxicity mechanisms. In Chapter III, IV and V, we investigate the cross-seeding interactions between Aß and hIAPP using a combination of coarse-grained (CG) replica-exchange molecular dynamics (REMD), all-atom molecular dynamics (MD) simulations and Markov Chain Monte Carlo (MCMC) simulations. We for the first time obtain the full free energy landscape for Aß-hIAPP cross-seeding interactions, by which the atomic structure of Aß-hIAPP cross-seeding assembly is determined. Computational mutagenesis studies reveal that disruption of interfacial salt bridges largely disfavor the ß-sheet-to-ß-sheet association, highlighting the importance of salt bridges in the formation of cross-seeding assemblies. We also probe the behaviors of Aß-hIAPP cross-seeding assemblies on zwitterionic POPC and anionic POPC/POPG membranes, determining the specific orientations and demonstrating that electrostatic interactions are the major forces governing peptide-lipid interactions. This work confirms the cross-seeding interactions between Aß and hIAPP, explaining the potential pathological link between AD and T2D. The atomic insights into the cross-seeding intearctions between amyloid peptides obtained from this work are expected to improve the understanding of the amyloid peptides and inspire the peptide inhibitor design towards the neurodegenerative diseases.
Author: Mai Suan Li
Publisher:
ISBN: 9781071615461
Category : Cell aggregation
Languages : en
Pages : 478
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Book Description
This volume provides computational methods and reviews various aspects of computational studies of protein aggregation. Chapters discuss the relationship between protein misfolding and protein aggregation, methods of prediction of aggregation propensities of protein, peptides, protein structure, results of computer simulations of aggregation, and computational simulations focused on specific diseases such as Alzheimer’s, Parkinson’s, and preeclampsia. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computer Simulations of Aggregation of Proteins and Peptides aims to ensure successful results in the further study of this vital field.
