Maximum likelihood density modification by pattern recognition of structural motifs
Abstract
An electron density for a crystallographic structure having protein regions and solvent regions is improved by maximizing the log likelihood of a set of structures factors {F.sub.h } using a local log-likelihood function: (x)+p(.rho.(x).vertline.SOLV)p.sub.SOLV (x)+p(.rho.(x).vertline.H)p.sub.H (x)], where p.sub.PROT (x) is the probability that x is in the protein region, p(.rho.(x).vertline.PROT) is the conditional probability for .rho.(x) given that x is in the protein region, and p.sub.SOLV (x) and p(.rho.(x).vertline.SOLV) are the corresponding quantities for the solvent region, p.sub.H (x) refers to the probability that there is a structural motif at a known location, with a known orientation, in the vicinity of the point x; and p(.rho.(x).vertline.H) is the probability distribution for electron density at this point given that the structural motif actually is present. One appropriate structural motif is a helical structure within the crystallographic structure.
- Inventors:
- Issue Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1174811
- Patent Number(s):
- 6721664
- Application Number:
- 09/769,612
- Assignee:
- University Of California, The Regents Of
- DOE Contract Number:
- W-7405-ENG-36
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Terwilliger, Thomas C. Maximum likelihood density modification by pattern recognition of structural motifs. United States: N. p., 2004.
Web.
Terwilliger, Thomas C. Maximum likelihood density modification by pattern recognition of structural motifs. United States.
Terwilliger, Thomas C. Tue .
"Maximum likelihood density modification by pattern recognition of structural motifs". United States. https://www.osti.gov/servlets/purl/1174811.
@article{osti_1174811,
title = {Maximum likelihood density modification by pattern recognition of structural motifs},
author = {Terwilliger, Thomas C.},
abstractNote = {An electron density for a crystallographic structure having protein regions and solvent regions is improved by maximizing the log likelihood of a set of structures factors {F.sub.h } using a local log-likelihood function: (x)+p(.rho.(x).vertline.SOLV)p.sub.SOLV (x)+p(.rho.(x).vertline.H)p.sub.H (x)], where p.sub.PROT (x) is the probability that x is in the protein region, p(.rho.(x).vertline.PROT) is the conditional probability for .rho.(x) given that x is in the protein region, and p.sub.SOLV (x) and p(.rho.(x).vertline.SOLV) are the corresponding quantities for the solvent region, p.sub.H (x) refers to the probability that there is a structural motif at a known location, with a known orientation, in the vicinity of the point x; and p(.rho.(x).vertline.H) is the probability distribution for electron density at this point given that the structural motif actually is present. One appropriate structural motif is a helical structure within the crystallographic structure.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {4}
}
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