Comparative Performance of Computer Simulation Models of Intrinsically Disordered Proteins at Different Levels of Coarse-Graining
(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
- Fagerberg, Eric LU and Skepö, Marie LU
- organization
- publishing date
- 2023-06-20
- 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}}, }