Maximum-likelihood density modification using pattern recognition of structural motifs

Journal Article · Sat Dec 01 04:00:00 EST 2001 · Acta Crystallographica. Section D: Biological Crystallography

DOI:https://doi.org/10.1107/S0907444901013737· OSTI ID:22347963

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, Journal Name: Acta Crystallographica. Section D: Biological Crystallography Journal Issue: Pt 12 Vol. 57; ISSN ABCRE6; ISSN 0907-4449
• Country of Publication: Denmark
• Language: English

Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY
DENSITY
DISTRIBUTION
ELECTRON DENSITY
ELECTRONS
MODIFICATIONS
PATTERN RECOGNITION
PROTEINS
SOLVENTS
YIELDS