A coarse-grained approach to NMR-data-assisted modeling of protein structures.
NMR-assisted protein-structure modeling
UNRES
ambiguous restraints
coarse-grained models
Journal
Journal of computational chemistry
ISSN: 1096-987X
Titre abrégé: J Comput Chem
Pays: United States
ID NLM: 9878362
Informations de publication
Date de publication:
05 12 2022
05 12 2022
Historique:
revised:
03
08
2022
received:
25
03
2022
accepted:
05
09
2022
pubmed:
23
9
2022
medline:
15
10
2022
entrez:
22
9
2022
Statut:
ppublish
Résumé
The ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically selects consistent restraints. Hamiltonian replica exchange molecular dynamics was used to carry out the conformational search. The method was tested with both unambiguous and ambiguous restraints producing good-quality models with GDT_TS from 7.4 units higher to 14.4 units lower than those obtained with the CYANA or MELD software for protein-structure determination from NMR data at the all-atom resolution. The method can thus be applied in modeling the structures of flexible proteins, for which extensive conformational search enabled by coarse-graining is more important than high modeling accuracy.
Substances chimiques
Peptides
0
Proteins
0
Protons
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2047-2059Subventions
Organisme : Narodowe Centrum Nauki
ID : UMO-2021/40/Q/ST4/00035
Informations de copyright
© 2022 Wiley Periodicals LLC.
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