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Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining

Fagerberg, Eric LU and Skepö, Marie LU (2023) In Journal of Chemical Information and Modeling 63(13). p.4079-4087
Abstract

Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold... (More)

Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Chemical Information and Modeling
volume
63
issue
13
pages
4079 - 4087
publisher
The American Chemical Society (ACS)
external identifiers
  • scopus:85164271852
  • pmid:37339604
ISSN
1549-960X
DOI
10.1021/acs.jcim.3c00113
language
English
LU publication?
yes
id
2b6befca-5a7f-4e43-abd0-144d7b2d038e
date added to LUP
2023-06-26 15:26:59
date last changed
2024-04-19 23:06:34
@article{2b6befca-5a7f-4e43-abd0-144d7b2d038e,
  abstract     = {{<p>Coarse-graining is commonly used to decrease the computational cost of simulations. However, coarse-grained models are also considered to have lower transferability, with lower accuracy for systems outside the original scope of parametrization. Here, we benchmark a bead-necklace model and a modified Martini 2 model, both coarse-grained models, for a set of intrinsically disordered proteins, with the different models having different degrees of coarse-graining. The SOP-IDP model has earlier been used for this set of proteins; thus, those results are included in this study to compare how models with different levels of coarse-graining compare. The sometimes naive expectation of the least coarse-grained model performing best does not hold true for the experimental pool of proteins used here. Instead, it showed the least good agreement, indicating that one should not necessarily trust the otherwise intuitive notion of a more advanced model inherently being better in model choice.</p>}},
  author       = {{Fagerberg, Eric and Skepö, Marie}},
  issn         = {{1549-960X}},
  language     = {{eng}},
  month        = {{06}},
  number       = {{13}},
  pages        = {{4079--4087}},
  publisher    = {{The American Chemical Society (ACS)}},
  series       = {{Journal of Chemical Information and Modeling}},
  title        = {{Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining}},
  url          = {{http://dx.doi.org/10.1021/acs.jcim.3c00113}},
  doi          = {{10.1021/acs.jcim.3c00113}},
  volume       = {{63}},
  year         = {{2023}},
}