554 research outputs found
Map-likelihood phasing
A map-likelihood function is described that can yield phase probabilities with very low model bias
The success of structural genomics
The International Conference on Structural Genomics (ICSG 2011, http://www.icsg2011.org), held in Toronto Canada May 10–14, 2011 was a rich and exciting demonstration of how far structural genomics has come. Structural genomics has now matured into a field that includes both structure and the biology that structure enables. This has allowed targeting based on systematic approaches and on known biological importance and allows biochemical studies to be closely tied to structure determination. The wealth of purified proteins, clones, and chemical probes produced by structural genomics groups will enable a vast amount of follow-on research. The technologies, the structures, and the biology that were described at the meeting were at the cutting edge of science. Structural genomics has become a success
Reciprocal-space solvent flattening
A procedure is described for improvement of crystallographic phases by reciprocal-space maximization of a likelihood function including experimental phases and characteristics of the electron-density map
Statistical density modification with non-crystallographic symmetry
Statistical density modification can make use of NCS in a crystal and can include estimates of the deviations from perfect NCS
σ2 R, a reciprocal-space measure of the quality of macromolecular electron-density maps
A reciprocal-space measure of the quality of macromolecular crystallographic phases based on the variance of the local roughness of the map is presented
Rapid automatic NCS identification using heavy-atom substructures
A rapid algorithm for identifying NCS in heavy-atom sites is described
Statistical density modification using local pattern matching
Statistical density modification can make use of local patterns of density found in protein structures to improve crystallographic phases
Maximum-likelihood density modification using pattern recognition of structural motifs
A likelihood-based density-modification method is extended to include pattern recognition of structural motifs
Automated side-chain model building and sequence assignment by template matching
A method for automated macromolecular side-chain model building and for aligning the sequence to the map is described
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