Model validation: local diagnosis, correction and when to quit.

Published

Journal Article

Traditionally, validation was considered to be a final gatekeeping function, but refinement is smoother and results are better if model validation actively guides corrections throughout structure solution. This shifts emphasis from global to local measures: primarily geometry, conformations and sterics. A fit into the wrong local minimum conformation usually produces outliers in multiple measures. Moving to the right local minimum should be prioritized, rather than small shifts across arbitrary borderlines. Steric criteria work best with all explicit H atoms. `Backrub' motions should be used for side chains and `P-perp' diagnostics to correct ribose puckers. A `water' may actually be an ion, a relic of misfitting or an unmodeled alternate. Beware of wishful thinking in modeling ligands. At high resolution, internally consistent alternate conformations should be modeled and geometry in poor density should not be downweighted. At low resolution, CaBLAM should be used to diagnose protein secondary structure and ERRASER to correct RNA backbone. All atoms should not be forced inside density, beware of sequence misalignment, and very rare conformations such as cis-non-Pro peptides should be avoided. Automation continues to improve, but the crystallographer still must look at each outlier, in the context of density, and correct most of them. For the valid few with unambiguous density and something that is holding them in place, a functional reason should be sought. The expectation is a few outliers, not zero.

Full Text

Duke Authors

Cited Authors

  • Richardson, JS; Williams, CJ; Hintze, BJ; Chen, VB; Prisant, MG; Videau, LL; Richardson, DC

Published Date

  • February 2018

Published In

Volume / Issue

  • 74 / Pt 2

Start / End Page

  • 132 - 142

PubMed ID

  • 29533239

Pubmed Central ID

  • 29533239

Electronic International Standard Serial Number (EISSN)

  • 2059-7983

Digital Object Identifier (DOI)

  • 10.1107/S2059798317009834

Language

  • eng