R value: Difference between revisions

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The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref><ref>Kleywegt, GJ. 2000. Validation of protein crystal structures. Acta. Crystallogr. D. Biol. Crystallogr. 56:249-265</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed]</ref>.

However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed].</ref>.

One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.

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==Content Donors==

~~This~~ page ~~was~~ adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz|Eric Martz]].

Portions of this page were adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz|Eric Martz]].

==Literature==

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-The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref><ref>Kleywegt, GJ. 2000. Validation of protein crystal structures. Acta. Crystallogr. D. Biol. Crystallogr. 56:249-265</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.
+The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.
 As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.
-However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed]</ref>.
+However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed].</ref>.
 One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.
@@ Line 9: / Line 9: @@
 ==Content Donors==
-This page was adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz|Eric Martz]].
+Portions of this page were adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz|Eric Martz]].
 ==Literature==
 <references />