AUREMOL-RFAC-3D, combination of R-factors and their use for automated quality assessment of protein solution structures

Abstract

We present here the computer program AUREMOL-RFAC-3D that is a generalization of the previously published program RFAC for the fully automated estimation of residual indices (R-factors) from 2D NOESY spectra. It is part of the larger AUREMOL software package (www.auremol.de). RFAC-3D calculates R-factors directly from two-dimensional homonuclear NOESY spectra as well as from three-dimensional (15)N or (13)C edited NOESY-HSQC spectra and thus extends the application range to larger proteins. The fully automated method includes automated peak picking and integration, a Bayesian noise and artifact recognition and the use of the complete relaxation matrix formalism. To enhance the reliability of the calculated R-factors the method is also generalized to calculate combined R-factors from a set of 2D and 3D-spectra. For an optimal combination of the information derived from different sources a plausible formalism had to be derived. In addition, we present a novel direct R-factors based measure that correlates an R-factors as defined in this paper to the root mean square deviation of the actual structure from the optimal structure. The new program has been successfully tested on the histidine containing phosphocarrier protein (HPr) from Staphylococcus carnosus and on the Ras-binding domain (RBD) of the Ral guanine-nucleotide dissociation stimulation factor (RalGDS).

Structure of the Leech Protein Saratin and Characterization of Its Binding to Collagen

“…The experimental restraints and structural statistics for the 10 accepted lowest energy structures after refinement in explicit water 25,26 are summarized in Table 1. The experimental restraints are well fulfilled as can also be seen from the combined NMR R-factor (R-PWAUR) 27 of 0.415 calculated from the homonuclear NOE spectroscopy (NOESY) and the 3D NOESY-heteronuclear single quantum coherence (HSQC) of a 15 N-enriched sample. Glu4-Cys82 adopt a well-defined tertiary structure with an RMSD for the C α atoms of 0.065 nm to the mean structure.…”

“…33 The agreement of the NOESY data with the calculated structures was calculated from a 2D NOESY and a 3D NOESY-1 H, 15 N-HSQC with AUREMOL-RFAC-3D. 27 …”

Ca2+-dependent Conformational Changes in a C-terminal Cytosolic Domain of Polycystin-2

“…The agreement of the NOESY data with the calculated structures was calculated from a two-dimensional-NOESY and a three-dimensional-NOESY-1 H, 15 N-HSQC with AUREMOL-RFAC-3D (19). Diffusion Measurements-Longitudinal eddy current delaystimulated echo (LED-STE) diffusion measurements (20) were performed with gradient sandwiches (21) (gradient lengths, 2 ms).…”

A method for validating the accuracy of NMR protein structures

“…The most obvious input data for NMR structures is the spectra. There have been attempts to do this 18,19 but there are major difficulties: there is no good way of accurately calculating chemical shifts from structures; dynamics in solution have big effects on spectra; there are many experimental artifacts in NMR spectra; and the number and variety of input spectra used in structure calculations makes it hard to define or measure what should be compared. Hence, we have here used backbone chemical shifts as our input data.…”