RFAC, a program for automated NMR R-factor estimation

A computer program (RFAC) has been developed, which allows the automated es timation of residual indices (R-factors) for protein NMR structures and giv es a reliable measure for the quality of the structures. The R-factor calcu lation is based on the comparison of experimental and simulated H-1 NOESY N MR spectra. The approach comprises an automatic peak picking and a Bayesian analysis of the data, followed by an automated structure based assignment of the NOESY spectra and the calculation of the R-factor. The major differe nce to previously published R-factor definitions is that we take the non-as signed experimental peaks into account as well. The number and the intensit ies of the non-assigned signals are an important measure for the quality of an NMR structure. It turns out that for different problems optimally adapt ed R-factors should be used which are defined in the paper. The program all ows to compute a global R-factor, different R-factors for the intra residua l NOEs, the inter residual NOEs, sequential NOEs, medium range NOEs and lon g range NOEs. Furthermore, R-factors can be calculated for various user def ined parts of the molecule or it is possible to obtain a residue-by-residue R-factor. Another possibility is to sort the R-factors according to their corresponding distances. The summary of all these different R-factors shoul d allow the user to judge the structure in detail. The new program has been successfully tested on two medium sized proteins, the cold shock protein ( TmCsp) from Termotoga maritima and the histidine containing protein (HPr) f rom Staphylococcus carnosus. A comparison with a previously published R-fac tor definition shows that our approach is more sensitive to errors in the c alculated structure.