Title |
The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data
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Published in |
Journal of Biomolecular NMR, May 2016
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DOI | 10.1007/s10858-016-0036-y |
Pubmed ID | |
Authors |
Woonghee Lee, Chad M. Petit, Gabriel Cornilescu, Jaime L. Stark, John L. Markley |
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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Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 13 | 30% |
Student > Ph. D. Student | 13 | 30% |
Student > Bachelor | 5 | 11% |
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Student > Master | 2 | 5% |
Other | 2 | 5% |
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Computer Science | 1 | 2% |
Other | 0 | 0% |
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