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Lars Andersen Bratholm edited subsection_NMR_calculations_and_protein__.tex
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\subsection{NMR calculations and protein structures used}
In this paper we benchmark the NMR chemical shift predictions on Ubiquitin and GB3. The structures are geometry optimized using PM6-D3H+ \cite{25024918} using the PCM solvation model and the CHARMM22/CMAP force field \cite{Mackerell_2004} using the GB/SA solvation model \cite{Qiu_1997} with the 1UBQ \cite{3041007} and 2OED \cite{15369375} structures as starting points. The PM6-D3H+ optimizations are done using the GAMESS program and a convergence criterion of 5 $\times$ 10$^{-4}$ atomic units, while the CHARMM22/CMAP optimizations are done using TINKER with default convergence criterion 0.01 kcal/mole/angstom. In addition the following NMR-derived structural ensembles are used without further refinement: 1D3Z \cite{Cornilescu_1998}, 2K39 \cite{Lange_2008}, 1XQQ \cite{Lindorff_Larsen_2005}, 2LJ5 \cite{Montalvao_2012}, 2KOX \cite{Fenwick_2011}. In all calculation we used charged protonation states for the acidic and basic side chains including histidine.
OBPE/6-31G(d,p)//PM6-D3H+ GIAO NMR shielding calculations were performed with Gaussian09 using the CPCM solvation model. ProCS15 calculations were done using a
program module written for the protein simulation framework PHAISTOS \cite{Boomsma_2013}. The module was specifically written for this
paper which paper, and can be downloaded at xx. CheShift-2 calculations are performed using
either the web interface at cheshift.com
xx?. or the PyMOL-plugin \cite{PyMOL} found at github.com/aloctavodia/cheshift. CamShift, PPM\_One, Sparta+, shAIC, and ShiftX2 calculations are performed using
the stand-alone
codes downloaded and installed on a local cluster. predictors. The NMR chemical shielding and shifts are compared to shifts measured for
ubiquitin Ubiquitin \cite{Cornilescu_1998} (BMRB ID
17769) 17769 ) and GB3 \cite{V_geli_2012} (BMRB ID 18531), respectively. Much of the variation in some of the chemical shifts comes from the nature of the side-chain itself and the side chains before and after in the sequence, which can lead to inflated R values. To separate the contributions of the sequence and the structure we subtract the measured sequence corrected random coil values \cite{Tamiola_2010} from all predicted and experimental values. Note that this does not affect the computed RMSD values.
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