Multiscale modelling of biopolymers
This review overviews common biopolymer modelling approaches ranging from chemically specific to highly coarse-grained techniques, along with their application ranges, strengths and limitations. Recent modelling applications at each modelling scale are outlined and discussed. The focus is on modelli...
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description | This review overviews common biopolymer modelling approaches ranging from chemically specific to highly coarse-grained techniques, along with their application ranges, strengths and limitations. Recent modelling applications at each modelling scale are outlined and discussed. The focus is on modelling of protein and peptide, nucleic acid and saccharide-based biopolymer systems, excluding lignocellulose materials. The survey focuses on physics-based models. We cover particle-based simulations methods, including all-atom and coarse-grained molecular dynamics (MD), dissipative particle dynamics (DPD) and Langevin and Brownian dynamics (BD) approaches. While these methods capture molecular and particle-level dynamics, a brief overview of also stochastic sampling approaches (Monte Carlo methods) to physics-based models, as well as free energy functional-based methods, i.e. field theory approaches, such as self-consistent field theory (SCFT) and classical density functional theory (cDFT), are provided. |
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While these methods capture molecular and particle-level dynamics, a brief overview of also stochastic sampling approaches (Monte Carlo methods) to physics-based models, as well as free energy functional-based methods, i.e. field theory approaches, such as self-consistent field theory (SCFT) and classical density functional theory (cDFT), are provided.</description><identifier>ISSN: 2374-6149</identifier><identifier>EISSN: 2374-6149</identifier><identifier>DOI: 10.1080/23746149.2024.2358196</identifier><language>eng</language><publisher>Abingdon: Taylor & Francis</publisher><subject>Amino acids ; Bioengineering ; Biopolymer modelling ; Biopolymers ; Carbohydrates ; Chemical bonds ; Chemistry ; Composite materials ; Density functional theory ; Field theory ; Free energy ; Lignocellulose ; Materials science ; Medical equipment ; Modelling ; Molecular dynamics ; Monte Carlo simulation ; Nucleic acids ; Peptides ; Physics ; physics-based models ; Polyesters ; Polymer blends ; polymer materials modelling ; Proteins ; Self consistent fields</subject><ispartof>Advances in physics: X, 2024-12, Vol.9 (1)</ispartof><rights>2024 The Author(s). 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Recent modelling applications at each modelling scale are outlined and discussed. The focus is on modelling of protein and peptide, nucleic acid and saccharide-based biopolymer systems, excluding lignocellulose materials. The survey focuses on physics-based models. We cover particle-based simulations methods, including all-atom and coarse-grained molecular dynamics (MD), dissipative particle dynamics (DPD) and Langevin and Brownian dynamics (BD) approaches. While these methods capture molecular and particle-level dynamics, a brief overview of also stochastic sampling approaches (Monte Carlo methods) to physics-based models, as well as free energy functional-based methods, i.e. field theory approaches, such as self-consistent field theory (SCFT) and classical density functional theory (cDFT), are provided.</description><subject>Amino acids</subject><subject>Bioengineering</subject><subject>Biopolymer modelling</subject><subject>Biopolymers</subject><subject>Carbohydrates</subject><subject>Chemical bonds</subject><subject>Chemistry</subject><subject>Composite materials</subject><subject>Density functional theory</subject><subject>Field theory</subject><subject>Free energy</subject><subject>Lignocellulose</subject><subject>Materials science</subject><subject>Medical equipment</subject><subject>Modelling</subject><subject>Molecular dynamics</subject><subject>Monte Carlo simulation</subject><subject>Nucleic acids</subject><subject>Peptides</subject><subject>Physics</subject><subject>physics-based models</subject><subject>Polyesters</subject><subject>Polymer blends</subject><subject>polymer materials modelling</subject><subject>Proteins</subject><subject>Self consistent fields</subject><issn>2374-6149</issn><issn>2374-6149</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><sourceid>DOA</sourceid><recordid>eNp9kE1LAzEQhoMoWLQ_QSj03JrvTW5K8aNQ8aLnkGSTkpLd1GSL9N-761bx5GmGmXmfd3gBuEFwiaCAt5hUlCMqlxhiusSECST5GZgM88WwOP_TX4JpKTsIIeJVLyYTMH85xC4Uq6ObNal2MYZ2O0t-ZkLap3hsXC7X4MLrWNz0VK_A--PD2-p5sXl9Wq_uNwtLsOwWHAtUM0JN_4njRhvhra0poZQT6Dx2HjJKpXDcMW6EEBVCAgsroPG4loxcgfXIrZPeqX0Ojc5HlXRQ34OUt0rnLtjolPeSYcsNlcZT2UM59cwQyrAXHjrXs-Yja5_Tx8GVTu3SIbf9-4ogiiqMIRL9FRuvbE6lZOd_XRFUQ7zqJ141xKtO8fa6u1EXWp9yoz9TjrXq9DGm7LNubRhs_kV8AQuNfmQ</recordid><startdate>20241231</startdate><enddate>20241231</enddate><creator>Scacchi, A.</creator><creator>Vuorte, M.</creator><creator>Sammalkorpi, M.</creator><general>Taylor & Francis</general><general>Taylor & Francis Ltd</general><general>Taylor & Francis Group</general><scope>0YH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8FD</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>L7M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9652-8608</orcidid><orcidid>https://orcid.org/0000-0003-4606-5400</orcidid><orcidid>https://orcid.org/0000-0002-9248-430X</orcidid></search><sort><creationdate>20241231</creationdate><title>Multiscale modelling of biopolymers</title><author>Scacchi, A. ; 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Recent modelling applications at each modelling scale are outlined and discussed. The focus is on modelling of protein and peptide, nucleic acid and saccharide-based biopolymer systems, excluding lignocellulose materials. The survey focuses on physics-based models. We cover particle-based simulations methods, including all-atom and coarse-grained molecular dynamics (MD), dissipative particle dynamics (DPD) and Langevin and Brownian dynamics (BD) approaches. 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subjects | Amino acids Bioengineering Biopolymer modelling Biopolymers Carbohydrates Chemical bonds Chemistry Composite materials Density functional theory Field theory Free energy Lignocellulose Materials science Medical equipment Modelling Molecular dynamics Monte Carlo simulation Nucleic acids Peptides Physics physics-based models Polyesters Polymer blends polymer materials modelling Proteins Self consistent fields |
title | Multiscale modelling of biopolymers |
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