Assessing the quality of solution nuclear magnetic resonance structures by complete cross-validation

Abstract

Structure determination of macromolecules in solution by nuclear magnetic resonance (NMR) spectroscopy involves the fitting of atomic models to the observed nuclear Overhauser effect (NOE) data. Complete cross-validation has been used to define reliable and unbiased criteria for the quality of solution NMR structures. The method is based on the partitioning of NOE data into test sets and the cross-validation of statistical quantities for each of the test sets. A high correlation between cross-validated measures of fit, such as distance bound violations and NMR R values, and the quality of solution NMR structures was observed. Less complete data resulted in poorer satisfaction of the cross-validated measures of fit. Optimization of cross-validated measures of fit will likely produce solution NMR structures with maximal information content.