Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides

Eric J M Lang; Emily G Baker; Dek N Woolfson; Adrian J Mulholland

doi:10.1021/acs.jctc.1c01172

Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides

Eric J M Lang^*, Emily G Baker, Dek N Woolfson, Adrian J Mulholland^*

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

We test a range of standard generalized Born (GB) models and protein force fields for a set of five experimentally characterized, designed peptides comprising alternating blocks of glutamate and lysine, which have been shown to differ significantly in α-helical content. Sixty-five combinations of force fields and GB models are evaluated in >800 μs of molecular dynamics simulations. GB models generally do not reproduce the experimentally observed α-helical content, and none perform well for all five peptides. These results illustrate that these models are not usefully predictive in this context. These peptides provide a useful test set for simulation methods.

Original language	English
Pages (from-to)	4070−4076
Number of pages	7
Journal	Journal of Chemical Theory and Computation
Volume	18
Issue number	7
Early online date	10 Jun 2022
DOIs	https://doi.org/10.1021/acs.jctc.1c01172
Publication status	E-pub ahead of print - 10 Jun 2022

Bibliographical note

Funding Information:
E.J.M.L., A.J.M., and D.N.W. were funded by the BBSRC/EPSRC Synthetic Biology Research Centre, BrisSynBio (BB/L01386 X/1). A.J.M. also thanks the EPSRC for support (EP/M022609/1). D.N.W. held a Royal Society Wolfson Research Merit Award (WM140008). The authors thank Robert E. Arbon for help with the statistical analysis of the MD data. This work was carried out using the computational facilities (BlueCrystal Phase 4) of the Advanced Computing Research Centre, University of Bristol ( http://www.bris.ac.uk/acrc/ ). We thank Prof. Thomas Simonson for useful discussions.

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© 2022 American Chemical Society.

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@article{98ca6d4d5e104726a0b4c70c2fa15286,

title = "Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides",

abstract = "We test a range of standard generalized Born (GB) models and protein force fields for a set of five experimentally characterized, designed peptides comprising alternating blocks of glutamate and lysine, which have been shown to differ significantly in α-helical content. Sixty-five combinations of force fields and GB models are evaluated in >800 μs of molecular dynamics simulations. GB models generally do not reproduce the experimentally observed α-helical content, and none perform well for all five peptides. These results illustrate that these models are not usefully predictive in this context. These peptides provide a useful test set for simulation methods.",

author = "Lang, {Eric J M} and Baker, {Emily G} and Woolfson, {Dek N} and Mulholland, {Adrian J}",

note = "Funding Information: E.J.M.L., A.J.M., and D.N.W. were funded by the BBSRC/EPSRC Synthetic Biology Research Centre, BrisSynBio (BB/L01386 X/1). A.J.M. also thanks the EPSRC for support (EP/M022609/1). D.N.W. held a Royal Society Wolfson Research Merit Award (WM140008). The authors thank Robert E. Arbon for help with the statistical analysis of the MD data. This work was carried out using the computational facilities (BlueCrystal Phase 4) of the Advanced Computing Research Centre, University of Bristol ( http://www.bris.ac.uk/acrc/ ). We thank Prof. Thomas Simonson for useful discussions. Publisher Copyright: {\textcopyright} 2022 American Chemical Society.",

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AU - Mulholland, Adrian J

N1 - Funding Information: E.J.M.L., A.J.M., and D.N.W. were funded by the BBSRC/EPSRC Synthetic Biology Research Centre, BrisSynBio (BB/L01386 X/1). A.J.M. also thanks the EPSRC for support (EP/M022609/1). D.N.W. held a Royal Society Wolfson Research Merit Award (WM140008). The authors thank Robert E. Arbon for help with the statistical analysis of the MD data. This work was carried out using the computational facilities (BlueCrystal Phase 4) of the Advanced Computing Research Centre, University of Bristol ( http://www.bris.ac.uk/acrc/ ). We thank Prof. Thomas Simonson for useful discussions. Publisher Copyright: © 2022 American Chemical Society.

PY - 2022/6/10

Y1 - 2022/6/10

N2 - We test a range of standard generalized Born (GB) models and protein force fields for a set of five experimentally characterized, designed peptides comprising alternating blocks of glutamate and lysine, which have been shown to differ significantly in α-helical content. Sixty-five combinations of force fields and GB models are evaluated in >800 μs of molecular dynamics simulations. GB models generally do not reproduce the experimentally observed α-helical content, and none perform well for all five peptides. These results illustrate that these models are not usefully predictive in this context. These peptides provide a useful test set for simulation methods.

AB - We test a range of standard generalized Born (GB) models and protein force fields for a set of five experimentally characterized, designed peptides comprising alternating blocks of glutamate and lysine, which have been shown to differ significantly in α-helical content. Sixty-five combinations of force fields and GB models are evaluated in >800 μs of molecular dynamics simulations. GB models generally do not reproduce the experimentally observed α-helical content, and none perform well for all five peptides. These results illustrate that these models are not usefully predictive in this context. These peptides provide a useful test set for simulation methods.

U2 - 10.1021/acs.jctc.1c01172

DO - 10.1021/acs.jctc.1c01172

M3 - Article (Academic Journal)

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JO - Journal of Chemical Theory and Computation

JF - Journal of Chemical Theory and Computation

IS - 7

ER -

Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides

Abstract

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