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ResProx (Resolution-by-proxy or Res(p)) is a web server that predicts the atomic resolution of NMR protein structures using only PDB coordinate data as input. More specfically, ResProx uses machine learning techniques to accurately estimate (with a correlation coefficient of 0.92 between observed and calculated) the atomic resolution of a protein structure from 25 measurable features that can be derived from its atomic coordinates. Because atomic resolution is a simple and near-universal measure of structure quality (i.e. < 2.0 Å is good, > 4.0 Å is bad), ResProx offers X-ray crystallographers and NMR spectroscopists the opportunity to easily assess the accuracy and quality of their 3D protein structures. It also allows them to assess whether their refinement methods have made their structures better (or worse) than what the experimental data suggests. Furthermore, since coordinate data is common to both X-ray and NMR, ResProx should allow structural biologists to use a single, easily understood number to compare the structures determined by NMR with those determined by X-ray crystallography.

Please cite the following: Mark Berjanskii, Jianjun Zhou, Yongjie Liang, Guohui Lin and David S. Wishart "Resolution-by-Proxy: A Simple Measure for Assessing and Comparing the Overall Quality of NMR Protein Structures", J Biomol NMR. 2012 Jul;53(3):167-80

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