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Title: Maximum-likelihood density modification using pattern recognition of structural motifs

Journal Article · · Acta Crystallographica. Section D: Biological Crystallography
 [1]
  1. Bioscience Division, Mail Stop M888, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

A likelihood-based density-modification method is extended to include pattern recognition of structural motifs. The likelihood-based approach to density modification [Terwilliger (2000 ▶), Acta Cryst. D56, 965–972] is extended to include the recognition of patterns of electron density. Once a region of electron density in a map is recognized as corresponding to a known structural element, the likelihood of the map is reformulated to include a term that reflects how closely the map agrees with the expected density for that structural element. This likelihood is combined with other aspects of the likelihood of the map, including the presence of a flat solvent region and the electron-density distribution in the protein region. This likelihood-based pattern-recognition approach was tested using the recognition of helical segments in a largely helical protein. The pattern-recognition method yields a substantial phase improvement over both conventional and likelihood-based solvent-flattening and histogram-matching methods. The method can potentially be used to recognize any common structural motif and incorporate prior knowledge about that motif into density modification.

OSTI ID:
22347963
Journal Information:
Acta Crystallographica. Section D: Biological Crystallography, Vol. 57, Issue Pt 12; Other Information: PMCID: PMC2745886; PMID: 11717487; PUBLISHER-ID: gr2164; OAI: oai:pubmedcentral.nih.gov:2745886; Copyright (c) International Union of Crystallography 2001; This is an open-access article distributed under the terms described at http://journals.iucr.org/services/termsofuse.html.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0907-4449
Country of Publication:
Denmark
Language:
English

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