4.7 Article

Assessing PDB macromolecular crystal structure confidence at the individual amino acid residue level

期刊

STRUCTURE
卷 30, 期 10, 页码 1385-+

出版社

CELL PRESS
DOI: 10.1016/j.str.2022.08.004

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资金

  1. National Science Foundation (NSF) [DBI-1832184]
  2. US Department of Energy [DE-SC0019749]
  3. National Cancer Institute of the National Institutes of Health [R01GM133198]
  4. National Institute of Allergy and Infectious Diseases of the National Institutes of Health [R01GM133198]
  5. National Institute of General Medical Sciences of the National Institutes of Health [R01GM133198]
  6. NSF [DBI-2019297, BB/V004247/1, DBI-2129634, BB/W017970/1]
  7. UK Biotechnology and Biological Research Council [DBI-2019297, BB/V004247/1, DBI-2129634, BB/W017970/1]

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This study analyzed the agreement between 3D atomic coordinates and experimental data in PDB MX structures, providing a metric for evaluating structure quality.
Approximately 87% of the more than 190,000 atomic-level three-dimensional (3D) biostructures in the PDB were determined using macromolecular crystallography (MX). Agreement between 3D atomic coordinates and experimental data for >100 million individual amino acid residues occurring within similar to 150,000 PDB MX structures was analyzed in detail. The real-space correlation coefficient (RSCC) calculated using the 3D atomic coordinates for each residue and experimental-data-derived electron density enables outlier detection of unreliable atomic coordinates (particularly important for poorly resolved side-chain atoms) and ready evaluation of local structure quality by PDB users. For human protein MX structures in PDB, comparisons of the per-residue RSCC metric with AlphaFold2-computed structure model confidence (pLDDT-predicted local distance difference test) document (1) that RSCC values and pLDDT scores are correlated (median correlation coefficient similar to 0.41), and (2) that experimentally determined MX structures (3.5 angstrom resolution or better) are more reliable than AlphaFold2-computed structure models and should be used preferentially whenever possible.

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