TY - JOUR
T1 - FOLD-EM
T2 - Automated fold recognition in medium-and low-resolution (4-15 Å) electron density maps
AU - Saha, Mitul
AU - Morais, Marc C.
N1 - Funding Information:
Funding: NIH award 1R01GM095516-01A1 to M.C.M. (in part) and the Methodist Hospital Research Institute supported by the Grant DOD/TATRC Alliance for NanoHealth W81XWH-10-2-0125 from the US Department of the Army, to M.C.M.
PY - 2012/12
Y1 - 2012/12
N2 - Motivation: Owing to the size and complexity of large multi-component biological assemblies, the most tractable approach to determining their atomic structure is often to fit high-resolution radiographic or nuclear magnetic resonance structures of isolated components into lower resolution electron density maps of the larger assembly obtained using cryo-electron microscopy (cryo-EM). This hybrid approach to structure determination requires that an atomic resolution structure of each component, or a suitable homolog, is available. If neither is available, then the amount of structural information regarding that component is limited by the resolution of the cryo-EM map. However, even if a suitable homolog cannot be identified using sequence analysis, a search for structural homologs should still be performed because structural homology often persists throughout evolution even when sequence homology is undetectable, As macromolecules can often be described as a collection of independently folded domains, one way of searching for structural homologs would be to systematically fit representative domain structures from a protein domain database into the medium/low resolution cryo-EM map and return the best fits. Taken together, the best fitting non-overlapping structures would constitute a 'mosaic' backbone model of the assembly that could aid map interpretation and illuminate biological function.Result: Using the computational principles of the Scale-Invariant Feature Transform (SIFT), we have developed FOLD-EM-a computational tool that can identify folded macromolecular domains in medium to low resolution (4-15 Å) electron density maps and return a model of the constituent polypeptides in a fully automated fashion. As a by-product, FOLD-EM can also do flexible multi-domain fitting that may provide insight into conformational changes that occur in macromolecular assemblies.Availability and implementation: FOLD-EM is available at: http://cs.stanford.edu/∼mitul/foldEM/, as a free open source software to the structural biology scientific community.
AB - Motivation: Owing to the size and complexity of large multi-component biological assemblies, the most tractable approach to determining their atomic structure is often to fit high-resolution radiographic or nuclear magnetic resonance structures of isolated components into lower resolution electron density maps of the larger assembly obtained using cryo-electron microscopy (cryo-EM). This hybrid approach to structure determination requires that an atomic resolution structure of each component, or a suitable homolog, is available. If neither is available, then the amount of structural information regarding that component is limited by the resolution of the cryo-EM map. However, even if a suitable homolog cannot be identified using sequence analysis, a search for structural homologs should still be performed because structural homology often persists throughout evolution even when sequence homology is undetectable, As macromolecules can often be described as a collection of independently folded domains, one way of searching for structural homologs would be to systematically fit representative domain structures from a protein domain database into the medium/low resolution cryo-EM map and return the best fits. Taken together, the best fitting non-overlapping structures would constitute a 'mosaic' backbone model of the assembly that could aid map interpretation and illuminate biological function.Result: Using the computational principles of the Scale-Invariant Feature Transform (SIFT), we have developed FOLD-EM-a computational tool that can identify folded macromolecular domains in medium to low resolution (4-15 Å) electron density maps and return a model of the constituent polypeptides in a fully automated fashion. As a by-product, FOLD-EM can also do flexible multi-domain fitting that may provide insight into conformational changes that occur in macromolecular assemblies.Availability and implementation: FOLD-EM is available at: http://cs.stanford.edu/∼mitul/foldEM/, as a free open source software to the structural biology scientific community.
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U2 - 10.1093/bioinformatics/bts616
DO - 10.1093/bioinformatics/bts616
M3 - Article
C2 - 23131460
AN - SCOPUS:84870799495
SN - 1367-4803
VL - 28
SP - 3265
EP - 3273
JO - Bioinformatics
JF - Bioinformatics
IS - 24
ER -