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Overview of refinement procedures within REFMAC 5: utilizing data from different sources
Author(s) -
Kovalevskiy Oleg,
Nicholls Robert A.,
Long Fei,
Carlon Azzurra,
Murshudov Garib N.
Publication year - 2018
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s2059798318000979
Subject(s) - computer science , consistency (knowledge bases) , algorithm , process (computing) , data mining , artificial intelligence , operating system
Refinement is a process that involves bringing into agreement the structural model, available prior knowledge and experimental data. To achieve this, the refinement procedure optimizes a posterior conditional probability distribution of model parameters, including atomic coordinates, atomic displacement parameters ( B factors), scale factors, parameters of the solvent model and twin fractions in the case of twinned crystals, given observed data such as observed amplitudes or intensities of structure factors. A library of chemical restraints is typically used to ensure consistency between the model and the prior knowledge of stereochemistry. If the observation‐to‐parameter ratio is small, for example when diffraction data only extend to low resolution, the Bayesian framework implemented in REFMAC 5 uses external restraints to inject additional information extracted from structures of homologous proteins, prior knowledge about secondary‐structure formation and even data obtained using different experimental methods, for example NMR. The refinement procedure also generates the `best' weighted electron‐density maps, which are useful for further model (re)building. Here, the refinement of macromolecular structures using REFMAC 5 and related tools distributed as part of the CCP 4 suite is discussed.

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