A database of calculated solution parameters for the AlphaFold predicted protein structures.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
05 05 2022
05 05 2022
Historique:
received:
23
12
2021
accepted:
07
04
2022
entrez:
5
5
2022
pubmed:
6
5
2022
medline:
10
5
2022
Statut:
epublish
Résumé
Recent spectacular advances by AI programs in 3D structure predictions from protein sequences have revolutionized the field in terms of accuracy and speed. The resulting "folding frenzy" has already produced predicted protein structure databases for the entire human and other organisms' proteomes. However, rapidly ascertaining a predicted structure's reliability based on measured properties in solution should be considered. Shape-sensitive hydrodynamic parameters such as the diffusion and sedimentation coefficients ([Formula: see text], [Formula: see text]) and the intrinsic viscosity ([η]) can provide a rapid assessment of the overall structure likeliness, and SAXS would yield the structure-related pair-wise distance distribution function p(r) vs. r. Using the extensively validated UltraScan SOlution MOdeler (US-SOMO) suite, a database was implemented calculating from AlphaFold structures the corresponding [Formula: see text], [Formula: see text], [η], p(r) vs. r, and other parameters. Circular dichroism spectra were computed using the SESCA program. Some of AlphaFold's drawbacks were mitigated, such as generating whenever possible a protein's mature form. Others, like the AlphaFold direct applicability to single-chain structures only, the absence of prosthetic groups, or flexibility issues, are discussed. Overall, this implementation of the US-SOMO-AF database should already aid in rapidly evaluating the consistency in solution of a relevant portion of AlphaFold predicted protein structures.
Identifiants
pubmed: 35513443
doi: 10.1038/s41598-022-10607-z
pii: 10.1038/s41598-022-10607-z
pmc: PMC9072687
doi:
Substances chimiques
Proteome
0
Banques de données
Dryad
['10.5061/dryad.jq2bvq89s']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7349Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM120600
Pays : United States
Organisme : NIH HHS
ID : GM120600
Pays : United States
Informations de copyright
© 2022. The Author(s).
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