ArticleJournal of biomolecular NMR2016
The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data.
Article in Journal of biomolecular NMR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Solution structure and dynamics of the mitochondrial-targeted GTPase-activating protein (GAP) VopE by an integrated NMR/SAXS approach.Protein science : a publication of the Protein Society · 2022Article
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- Solution structure of human myeloid-derived growth factor suggests a conserved function in the endoplasmic reticulum.Nature communications · 2019Article
- Emerging solution NMR methods to illuminate the structural and dynamic properties of proteins.Current opinion in structural biology · 2019Review
- Function and solution structure of the Arabidopsis thaliana RALF8 peptide.Protein science : a publication of the Protein Society · 2019Article
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5 authors.
Funding
Abstract
We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27-98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.
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