Determination of solution structures of proteins up to 40 kDa using CS-Rosetta with sparse NMR data from deuterated samples

By Oliver F. Lange, P. Rossi, Nikolaos G. Sgourakis, Yifan Song, Hsiau-Wei Lee, J. Aramini, A. Ertekin, R. Xiao, T. Acton, Gaetano T. Montelione and 1 more. 2012

202 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy, Computational Biology & Bioinformatics

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Citations in the corpus

Protein structure prediction from sequence variation (2012, background): “Such approaches have worked favorably in cases for smaller proteins that have fewer than ~90 amino acids 7 and need to be combined with experimental data for larger proteins 8,9 .”
Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information (2014, methodology): “The restraints were introduced between C β atoms ( C α in the case of glycine) in the reduced-atom representation of Rosetta (centroid mode) and as ambiguous distance restraints ( Lange et al., 2012 ) between side-chain heavy atoms (cutoff of 5.5 and slope of 4) in the full-atom stage of Rosetta.”
Automatic NOESY assignment in CS-RASREC-Rosetta (2014, methodology): “2010a) or that an initial fold can be determined with CYANA (Lange et al. 2012).”
Integrative NMR for biomolecular research (2016, unknown): “…(Bahrami et al. 2009), PONDEROSA-C/S for automated structure determination, TALOS-N for shift based torsion angle restraints (Shen and Bax 2013), the PACSY database (Lee et al. 2012), and the CS-Rosetta (Lange et al. 2012) compute server at the Biological Magnetic Resonance data Bank (BMRB).”
Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction (2015, methodology): “To reduce the influence of potentially incorrect restraints in this set, we furthermore combined random pairs into ambiguous restraints [6].”
CS-ROSETTA (2018, methodology): “Both the structure calculations were setup using NMR chemical shift-guided fragments and previously measured NOE restraints (Lange et al., 2012) (BMRB ID 16806).”
Chemical shift-based methods in NMR structure determination (2018, methodology): “In particular, RASREC-Rosetta was used together with sparse NOE data recorded for 11 protein targets of sizes up to 40 kDa [87].”
Web‐accessible molecular modeling with Rosetta: The Rosetta Online Server that Includes Everyone (ROSIE) (2018, background): “…interactions, 3,4 protein–peptide interactions, 5,6 and protein–small molecule interactions, 7,8 to the use of nuclear magnetic resonance 9,10 and electron density information 11,12 in structure prediction and refinement, to the design of novel protein folds, 13,14 protein–protein…”
Integrative protein modeling in RosettaNMR from sparse paramagnetic restraints (2019, background): “side-chain NOEs from deuterated protein samples and improving conformational sampling algorithms increased the application limit of CS-Rosetta to proteins up to 40 kDa (23) and enabled prediction of helical membrane protein structures (24).”
Computational modeling of membrane proteins (2014, unknown): “163 In half of the cases, the Rosetta model was closer to the crystal structure than the NMR structure.”