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Bayesian estimation of NMR restraint potential and weight: A validation on a representative set of protein structures
Author(s) -
Bernard Aymeric,
Vranken Wim F.,
Bardiaux Benjamin,
Nilges Michael,
Malliavin Thérèse E.
Publication year - 2011
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.22980
Subject(s) - weighting , bayesian probability , mathematics , similarity (geometry) , bayesian statistics , statistics , algorithm , bayesian inference , computer science , statistical physics , artificial intelligence , physics , acoustics , image (mathematics)
The classical procedure for nuclear magnetic resonance structure calculation allocates empirical distance ranges and uses historical values for weighting factors. However, Bayesian analysis suggests that there are more optimal choices for potential shape (bounds‐free log‐harmonic shape) and restraints weights. We compare the classical protocol with the Bayesian approach for more than 300 protein structures. We analyze the conformation similarity to the corresponding X‐ray crystal structure, the distribution of the conformations around their average, and independent validation criteria. On average, the log‐harmonic potential reduces the difference to the X‐ray crystal structure. If the log‐harmonic potential is used, the constant weighting tightens the distribution around the average conformation, with respect to the distributions obtained with Bayesian weighting. Conversely, the structure quality is improved by the Bayesian weighting over the classical procedure, whereas constant weighting worsens some criteria. The quality improvement obtained with the log‐harmonic potential coupled to Bayesian weighting validates this approach on a representative set of protein structures. Proteins 2011. © 2011 Wiley‐Liss, Inc.