Multiscale modelling of biopolymers - UTU Research Portal

A2 Refereed review article in a scientific journal

Multiscale modelling of biopolymers

Authors: Scacchi, A.; Vuorte, M.; Sammalkorpi, M.

Publisher: Taylor and Francis Ltd.

Publication year: 2024

Journal: Advances in Physics: X

Journal name in source: Advances in Physics: X

Article number: 2358196

Volume: 9

Issue: 1

eISSN: 2374-6149

DOI: https://doi.org/10.1080/23746149.2024.2358196

Web address : https://www.tandfonline.com/doi/full/10.1080/23746149.2024.2358196

Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/457246497

Abstract

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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Multiscale modelling of biopolymers.pdf

Funding information in the publication:
This work was supported by the Academy of Finland through project no. [359180] (M.S.) and its Centres of Excellence Programme (2022-2029, LIBER) under project no. [346111] (M.S.), by the Novo Nordisk Foundation under project no. [NNF22OC0074060] (M.S.) and [NNF22OC0079084] (A.S.), and by the Swiss National Science Foundation under the project no. [P500PT_206916] (A.S.).