Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra
By T. Evangelidis, Santrupti Nerli, J. Nováček, Andrew E. Brereton, P. Karplus, R. R. Dotas, V. Venditti, Nikolaos G. Sgourakis, K. Tripsianes. 2018
36 citations recorded by the source corpus.
Automated methods for NMR structure determination of proteins are continuously becoming more robust. However, current methods addressing larger, more complex targets rely on analyzing 6–10 complementary spectra, suggesting the need for alternative approaches. Here, we describe 4D-CHAINS/autoNOE-Rosetta, a complete pipeline for NOE-driven structure determination of medium- to larger-sized proteins. The 4D-CHAINS algorithm analyzes two 4D spectra recorded using a single, fully protonated protein sample in an iterative ansatz where common NOEs between different spin systems supplement conventional through-bond connectivities to establish assignments of sidechain and backbone resonances at high levels of completeness and with a minimum error rate. The 4D-CHAINS assignments are then used to guide automated assignment of long-range NOEs and structure refinement in autoNOE-Rosetta. Our results on four targets ranging in size from 15.5 to 27.3 kDa illustrate that the structures of proteins can be determined accurately and in an unsupervised manner in a matter of days. Further automation of NMR structure determination is needed to increase the throughput and accessibility of this method. Here the authors present 4D-CHAINS/autoNOE-Rosetta, a complete pipeline that allows rapid and fully automated structure determination from two highly complementary NMR datasets.
Subfields: Molecular Biology, Spectroscopy
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Citations in the corpus
- Chemical shift-based methods in NMR structure determination (2018, methodology): “With this in mind, 4D-CHAINS, an automated procedure, was developed recently to assign backbone and sidechain chemical shifts using two complementary 4D (TOCSY and NOESY) spectra, recorded in fully protonated samples [216].”
- CS-ROSETTA (2018, methodology): “Recently, an automated method, 4D-CHAINS, was developed (Evangelidis et al., 2018).”