TY - JOUR
T1 - Protein Structure Fitting and Refinement Guided by Cryo-EM Density
AU - Topf, Maya
AU - Lasker, Keren
AU - Webb, Ben
AU - Wolfson, Haim
AU - Chiu, Wah
AU - Sali, Andrej
N1 - Funding Information:
We thank Frank Alber, Friedrich Forster, Fred Davis, and Paula Petrone for very helpful discussions. M.T. is supported by an MRC Career Development Award. K.L. is supported in part by a fellowship from the Edmond J. Safra Bioinformatics Program at Tel-Aviv University. H.W. acknowledges support by the Binational U.S.-Israel Science Foundation, Israel Science Foundation (281/05), NIAID, and the Hermann Minkowski-Minerva Center for Geometry at TAU. W.C. is supported by the NIH (P41RR02250). A.S. is supported by the Sandler Family Supporting Foundation, NIH (R01 GM54762, U54 GM074945, P41 RR02250), Hewlett-Packard, NetApps, IBM, and Intel. W.C. and A.S. are supported jointly by NIH (PN2 EY016525) and NSF (EIA-032645 and 1IIS-0705474).
PY - 2008/2/12
Y1 - 2008/2/12
N2 - For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 Å). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At ∼10 Å resolution, Cα rmsd between the initial and final structures was reduced on average by ∼53%. The method is automated and can refine both experimental and predicted atomic structures.
AB - For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 Å). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At ∼10 Å resolution, Cα rmsd between the initial and final structures was reduced on average by ∼53%. The method is automated and can refine both experimental and predicted atomic structures.
KW - PROTEINS
UR - http://www.scopus.com/inward/record.url?scp=38949092920&partnerID=8YFLogxK
U2 - 10.1016/j.str.2007.11.016
DO - 10.1016/j.str.2007.11.016
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C2 - 18275820
AN - SCOPUS:38949092920
SN - 0969-2126
VL - 16
SP - 295
EP - 307
JO - Structure
JF - Structure
IS - 2
ER -