Literature DB >> 25581292

Estimation of the quality of refined protein crystal structures.

Jimin Wang1.   

Abstract

Crystallographic R work and R free values, which are measures of the ability of the models of macromolecular structures to explain the crystallographic data on which they are based, are often used to assess structure quality. It is widely known, and confirmed here that both are sensitive to the methods used to compute them, and can be manipulated to improve the apparent quality of the model. As an alternative it is proposed here that the quality of crystallographic models should be assessed using a global goodness-of-fit metric RO2A /R work where RO2A is the number of reflections used for refinement divided by the number of nonhydrogen atoms in the structure, and R work is the working R-factor of the refined structure. Also, analysis of structures in the Protein Data Bank suggests that many data sets have been truncated at high resolution, thereby improving the R-factor statistics. To discourage this practice, it is proposed that the resolution of a dataset be defined as the resolution of the shell of data where <I/σI > falls to 1. The proposed goodness-of-fit metric encourages investigators to use all the data available rather than a truncated subset.
© 2015 The Protein Society.

Keywords:  data truncation; free R-factors; protein quality; resolution; statistical gaming; statistical manipulation; working R-factors

Mesh:

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Year:  2015        PMID: 25581292      PMCID: PMC4420517          DOI: 10.1002/pro.2639

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


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