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Physics-Based Coarse-Grained Modeling in Bio- and Nanochemistry

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Practical Aspects of Computational Chemistry V

Abstract

Coarse-grained approaches, in which groups of atoms are represented by single interaction sites, are very important in biological and materials sciences because they enable us to cover the size- and time-scales by several orders of magnitude larger than those available all-atom simulations, while largely keeping the details of the systems studied. The coarse-grained approaches differ by the scheme of reduction and by the origin and parameterization of the respective force fields. Both statistical (database-derived) and physics-based potentials are used, the physics-based potentials enabling us to bridge the coarse-grained level with the all-atom level, which is necessary when carrying out the simulations at multiple resolutions (multiscale simulations). The physics-based potentials originate from the potential of mean force (PMF) of a system under study, in which the degrees of freedom that are not considered in the model are averaged out. For tractability and transferability the PMF has to be expressed as a sum of contributions that constitute the effective energy terms. These terms are often assigned analytical expressions imported from all-atom force fields or engineered to reproduce certain structural patterns (e.g., the secondary structures of proteins or nucleic acids). Tabulated (model-free) potentials are also applied. Approaches also exist in which the effective energy terms are derived systematically by splitting the potential of mean force into transferable terms, e.g., by expressing the PMF by the Kubo cluster-cumulant functions. Two approaches, or a combination thereof, are applied in the parameterization of the coarse-grained force fields: the bottom-up one, in which the potentials of mean force are determined from atomistically-detailed calculations and then used to parameterize the respective expressions, and the top-down approach, in which the force field is tuned to fit the experimental data. In this chapter, the theory and parameterization of the physics-based coarse-grained force fields, along with the corresponding methods of conformational search are reviewed. Examples of physics-based coarse-grained force fields applied to study biomolecules and their assemblies and nanosystems are discussed.

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Acknowledgements

This work was supported by grants UMO-2017/25/B/ST4/01026, UMO-2017/27/B/ST4/00926, UMO-2017/26/M/ST4/00044, UMO-2018/30/E/ST4/00037, UMO-2015/17/N/ST4/03935, and UMO-2015/17/N/ST4/03937 from the National Science Center of Poland (Narodowe Centrum Nauki). Calculations were carried out using the computational resources provided by (a) the supercomputer resources at the Centre of Informatics—Tricity Academic Supercomputer & networK (CI TASK) in Gdańsk, (b) the supercomputer resources at the Interdisciplinary Center of Mathematical and Computer Modeling (ICM), University of Warsaw (grant GA71-23), (c) the Polish Grid Infrastructure (PL-GRID; grants unres19, unres2021, and gagstr), and (d) our 488-processor Beowulf cluster at the Faculty of Chemistry, University of Gdańsk.

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Authors and Affiliations

  1. Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland

    Adam Liwo

  2. School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea

    Adam Liwo

  3. Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland

    Adam K. Sieradzan, Sergey A. Samsonov & Cezary Czaplewski

  4. Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland

    Agnieszka S. Karczyńska

  5. Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France

    Agnieszka S. Karczyńska

  6. Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdańsk, Poland

    Emilia A. Lubecka

  7. Institute of Physics, Polish Academy of Sciences, Warsaw, Poland

    Paweł Krupa

  8. Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

    Magdalena Mozolewska

Authors
  1. Adam Liwo
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  2. Adam K. Sieradzan
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  3. Agnieszka S. Karczyńska
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  4. Emilia A. Lubecka
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  5. Sergey A. Samsonov
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  6. Cezary Czaplewski
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  7. Paweł Krupa
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  8. Magdalena Mozolewska
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Corresponding author

Correspondence to Adam Liwo .

Editor information

Editors and Affiliations

  1. Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS, USA

    Jerzy Leszczynski

  2. US Army Engineer Research and Development Center, Vicksburg, MS, USA

    Manoj K. Shukla

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Liwo, A. et al. (2022). Physics-Based Coarse-Grained Modeling in Bio- and Nanochemistry. In: Leszczynski, J., Shukla, M.K. (eds) Practical Aspects of Computational Chemistry V. Springer, Cham. https://doi.org/10.1007/978-3-030-83244-5_2

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