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Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures.
FEBS J. 2008 Jan; 275(1):1-21
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06 May 2011
Review / Commentary
DOI: 10.3410/f.10138956.10913054
This primer on how to critically assess macromolecular crystal structures is even more relevant now than when it was published in 2008. Indeed, the article may be at least as valuable to practicing crystallographers as to biologists and biochemists, as a reminder of the ground rules and potential pitfalls.
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This primer on how to critically assess macromolecular crystal structures is even more relevant now than when it was published in 2008. Indeed, the article may be at least as valuable to practicing crystallographers as to biologists and biochemists, as a reminder of the ground rules and potential pitfalls.
The number of macromolecular structures determined by crystallography has increased dramatically during the more than 50 years since its inception, and, indeed, so has the number of Nobel prizes awarded for studies that are critically dependent upon it. Although steps are continuously taken by the main repositories of structural data to do quality control on the structures they archive, as well as to inform non-expert users, a solid understanding of what to look for in a structure is essential to using it wisely. Wlodawer et al. deliver this without skimping on accuracy, or getting needlessly stuck in detail. Numerous examples of existing structures are (tactfully) used to good effect throughout the paper. Other points are illustrated by the wholly fictitious 'frankenstainase' structure.
Given the worldwide protein data bank (PDB)'s policy of accepting virtually any deposition that is technically valid, there is inevitably a substantial variation in the quality of the entries found there. Added to this, structures are never removed from the data bank, unless shown to be grossly erroneous or fraudulent. A higher resolution structure, even when far more suited to explain observable facts, will never replace legacy entries. Conversely, the highest resolution, or most recent, entry in the database for your favorite protein may not be the most suitable model for your needs. Wlodawer et al. provide the reader with a set of relevant quality indicators, as well as some helpful of rules of thumb, to help with this assessment. As they point out, none of these rules is beyond discussion, but promoting that discussion is another valuable outcome of the paper.
The number of macromolecular structures determined by crystallography has increased dramatically during the more than 50 years since its inception, and, indeed, so has the number of Nobel prizes awarded for studies that are critically dependent upon it. Although steps are continuously taken by the main repositories of structural data to do quality control on the structures they archive, as well as to inform non-expert users, a solid understanding of what to look for in a structure is essential to using it wisely. Wlodawer et al. deliver this without skimping on accuracy, or getting needlessly stuck in detail. Numerous examples of existing structures are (tactfully) used to good effect throughout the paper. Other points are illustrated by the wholly fictitious 'frankenstainase' structure.
Given the worldwide protein data bank (PDB)'s policy of accepting virtually any deposition that is technically valid, there is inevitably a substantial variation in the quality of the entries found there. Added to this, structures are never removed from the data bank, unless shown to be grossly erroneous or fraudulent. A higher resolution structure, even when far more suited to explain observable facts, will never replace legacy entries. Conversely, the highest resolution, or most recent, entry in the database for your favorite protein may not be the most suitable model for your needs. Wlodawer et al. provide the reader with a set of relevant quality indicators, as well as some helpful of rules of thumb, to help with this assessment. As they point out, none of these rules is beyond discussion, but promoting that discussion is another valuable outcome of the paper.
Disclosures
None declared
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Mowbray S and Ericsson D: F1000Prime Recommendation of [Wlodawer A et al., FEBS J 2008, 275(1):1-21]. In F1000Prime, 06 May 2011; DOI: 10.3410/f.10138956.10913054. F1000Prime.com/10138956#eval10913054
F1000Prime Recommendations, Dissents and Comments for [Wlodawer A et al., FEBS J 2008, 275(1):1-21]. In F1000Prime, 21 May 2013; F1000Prime.com/10138956
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The number of macromolecular structures deposited in the Protein Data Bank now exceeds 45,000, with the vast majority determined using crystallographic methods. Thousands of studies describing such structures have been published in the scientific literature, and 14 Nobel prizes in chemistry or medicine have been awarded to protein crystallographers. As important as these structures are for understanding the processes that take place in living organisms and also for practical applications such as drug design, many non-crystallographers still have problems with critical evaluation of the structural literature data. This review attempts to provide a brief outline of technical aspects of crystallography and to explain the meaning of some parameters that should be evaluated by users of macromolecular structures in order to interpret, but not over-interpret, the information present in the coordinate files and in their description. A discussion of the extent of the information that can be gleaned from the coordinates of structures solved at different resolution, as well as problems and pitfalls encountered in structure determination and interpretation are also covered.
DOI: 10.1111/j.1742-4658.2007.06178.x
PMID: 18034855
