Search

Contains fulltext : 34563.pdf (Publisher’s version ) (Open Access) One of the major goals of structural genomics projects is to determine the three-dimensional structure of representative members of as many different fold families as possible. Comparative modeling is expected to fill the remaining gaps by providing structural models of homologs of the experimentally determined proteins. However, for such an approach to be successful it is essential that the quality of the experimentally determined structures is adequate. In an attempt to build a homology model for the protein dynein light chain 2A (DLC2A) we found two potential templates, both experimentally determined nuclear magnetic resonance (NMR) structures originating from structural genomics efforts. Despite their high sequence identity (96%), the folds of the two structures are markedly different. This urged us to perform in-depth analyses of both structure ensembles and the deposited experimental data, the results of which clearly identify one of the two models as largely incorrect. Next, we analyzed the quality of a large set of recent NMR-derived structure ensembles originating from both structural genomics projects and individual structure determination groups. Unfortunately, a visual inspection of structures exhibiting lower quality scores than DLC2A reveals that the seriously flawed DLC2A structure is not an isolated incident. Overall, our results illustrate that the quality of NMR structures cannot be reliably evaluated using only traditional experimental input data and overall quality indicators as a reference and clearly demonstrate the urgent need for a tight integration of more sophisticated structure validation tools in NMR structure determination projects. In contrast to common methodologies where structures are typically evaluated as a whole, such tools should preferentially operate on a per-residue basis.

Contains fulltext : 59140.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 57416.pdf (Publisher’s version ) (Closed access) Several studies have shown that biomolecular NMR structures are often of lower quality when compared to crystal structures, and consequently they are often excluded from structural analyses. We present a publicly available database of re-refined NMR structures, exhibiting significantly improved quality. This database (available at http://www.cmbi.kun.nl/dress/) presents a uniformly refined and validated set of structural models that improves the value of these NMR structures as input for experimental and theoretical studies in many fields of research.

Contains fulltext : 79477.pdf (Publisher’s version ) (Closed access) Biomolecular structures provide the basis for many studies in research areas such as structure-based drug design and homology modeling. In order to use molecular coordinates it is important that they are reliable in terms of accurate description of the experimental data and in terms of the overall and local geometry. Besides these primary quality criteria an indication is needed for the uncertainty in the atomic coordinates that may arise from the dynamic behavior of the considered molecules as well as from experimental- and computational procedures.In contrast to the crystallographic B-factor, a good measure for the uncertainty in NMR-derived atomic coordinates is still not available. It has become clear in recent years that the widely used atomic Root Mean Square Deviation (RMSD), which is a measure for the precision of the data, overestimates the accuracy of NMR structure ensembles and therefore is a problematic measure for the uncertainty in the atomic coordinates.In this study we report a method that yields a more realistic estimate of the uncertainty in the atomic coordinates by maximizing the RMSD of an ensemble of structures, while maintaining the accordance with the experimentally derived data. The results indicate that the RMSD of most NMR structure ensembles can be significantly increased compromising neither geometric quality nor NMR data. This maximized RMSD therefore seems a better estimate of the true uncertainty in the atomic coordinates.