tructural analyses of proteins by NMR often rely on paramagnetic relaxation enhancement (PRE) data. This is especially true for challenging protein targets, e.g. large, unstable or poorly soluble proteins. To acquire PRE data, protein samples are labeled with a paramagnetic tag, such as MTSL, and the resulting attenuation of peak intensities in the 1HN,15N-HSQC spectra is measured. However, the relationship between the PRE rates and the distances r from paramagnetic center to specific 1HN atoms is subject to considerable uncertainty (mainly due to conformational mobility of the tag). To explore this relationship, we have measured the PRE effect in five MTSL-labeled variants of the popular model protein GB1. We have also recorded MD trajectories of these constructs with the net length of 50 μs. The trajectories were used to calculate PRE rates, which were subsequently compared with the experimental results. Using this combined experimental and theoretical framework, we investigated the approximations that are commonly used in the analyses of the PRE effect, e.g. the assumption that fluctuations of the distance r and angle θ for dipolar interaction between 1HN and electron spin are uncorrelated. We found that in most cases simple Gillespie-Shortle formula provides an adequate tool to extract distances from the PRE data. Specifically, for N8C-, K28C- and T44C-MTSL structural models can be built where the position of paramagnetic center is adjusted such as to reproduce all PRE-extracted distances. On the other hand, K10C- and E15C-MTSL adopt unusual conformations with MTSL tag packed at the periphery of the protein hydrophobic core (accompanied by visible distortions of the fold). This behavior causes poor agreement between the predicted and experimental PREs, suggesting that force-field parameters of the MTSL tag may need an improvement. Support: SPbU grant 51142660.
|Issue number||3 Supp,.1|
|State||Published - 12 Feb 2021|
|Event||65th Annual Meeting of the Biophysical Society - online|
Duration: 22 Feb 2021 → 26 Feb 2021
Scopus subject areas
- Structural Biology