Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE
Open accessAbstract
AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom-atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.
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High pLDDT at a residue does not always mean the correct rotamer was modeled.
“high pLDDT at a specific residue does not always indicate the correct rotameter has been modeled23”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [23]
For most globular proteins, AF2 gives accurate, reliable models with high pLDDT (>70) or low PAE (<5 Å) that match experimental native structures.
“For the majority of globular proteins, AF2 provides accurate, reliable models with high pLDDT (> 70) or low PAE values (< 5 Å) highlighting confidence in the prediction of the position of the atomic coordinates, which match experimentally determined native structures5,17,23,59”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [23]
Downweighting or removing low-confidence regions can improve the use of AF models in molecular replacement.
“The use of AF models in molecular replacement can be further enhanced by downweighting or removing low confidence regions23.”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [23]
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- Authors
- Oeffner, R. D., Croll, T. I., Millán, C., Poon, B. K., Schlicksup, C. J., Read, R. J., & Terwilliger, T. C.
- Affiliations
- University of Cambridge (GB)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Read, Randy J.
- ORCID
- Venue
- Acta Crystallographica Section D Structural Biology
- Published
- 2022-10-27
- Volume
- 78
- Issue
- 11
- Pages
- 1303-1314
- ISSN
- 2059-7983 (ISSN-L)
- PMC
- PMC9629492
- OpenAlex
- W4307407928
- Cited by
- 63
- References
- 26
- Citations by year
- 2026: 8 · 2025: 15 · 2024: 23 · 2023: 17
- FWCI
- 3.87
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Acta Crystallographica Section D Structural Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- Wellcome Trust Principal Research Fellowship (209407/Z/ 17/Z)
- National Institutes of Health (P01GM063210)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Inorganic Chemistry › Crystal structures of chemical compounds
- Keywords
- AlphaFold, ISOLDE, protein structure prediction, domain decomposition, molecular replacement, structure refinement
- MeSH terms
- Models, Molecular, Protein Conformation, Software, Crystallography, X-Ray, Cryoelectron Microscopy
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