Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction
A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an $\alpha$-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone HN pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the C$\alpha$-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 \AA and 3.06 \AA (no NMR data) to 5.73 \AA and 2.18 \AA, respectively.
%0 Journal Article
%1 Ledwitch2023-gm
%A Ledwitch, Kaitlyn V
%A Künze, Georg
%A McKinney, Jacob R
%A Okwei, Elleansar
%A Larochelle, Katherine
%A Pankewitz, Lisa
%A Ganguly, Soumya
%A Darling, Heather L
%A Coin, Irene
%A Meiler, Jens
%D 2023
%J J. Biomol. NMR
%K (IMPs); (PCSs); (ncAAs); Click Integral Non-canonical Pseudocontact Rosetta; Structure acids amino chemistry; membrane prediction proteins shifts topic_lifescience
%N 3
%P 69--82
%T Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction
%V 77
%X A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an $\alpha$-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone HN pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the C$\alpha$-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 \AA and 3.06 \AA (no NMR data) to 5.73 \AA and 2.18 \AA, respectively.
@article{Ledwitch2023-gm,
abstract = {A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an $\alpha$-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone HN pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the C$\alpha$-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 {\AA} and 3.06 {\AA} (no NMR data) to 5.73 {\AA} and 2.18 {\AA}, respectively.},
added-at = {2024-09-10T10:41:24.000+0200},
author = {Ledwitch, Kaitlyn V and K{\"u}nze, Georg and McKinney, Jacob R and Okwei, Elleansar and Larochelle, Katherine and Pankewitz, Lisa and Ganguly, Soumya and Darling, Heather L and Coin, Irene and Meiler, Jens},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2eaf3189712d44855e19a033404cf24be/scadsfct},
interhash = {345d1f47b242c617bad05c98d2a272f9},
intrahash = {eaf3189712d44855e19a033404cf24be},
journal = {J. Biomol. NMR},
keywords = {(IMPs); (PCSs); (ncAAs); Click Integral Non-canonical Pseudocontact Rosetta; Structure acids amino chemistry; membrane prediction proteins shifts topic_lifescience},
language = {en},
month = jun,
number = 3,
pages = {69--82},
timestamp = {2024-09-10T12:00:15.000+0200},
title = {Sparse pseudocontact shift {NMR} data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction},
volume = 77,
year = 2023
}
