Cryogenic electron microscopy (cryo-EM) is now yielding atomic or near-atomic resolution structures for proteins and other biological macromolecular complexes via single particle reconstruction (SPR) and tomography. This comes at a price ? cryo-EM structures are noisy and have to be filtered at the appropriate resolution before they can be interpreted. The problem is that particle heterogeneity, errors in image alignment, and the missing wedge in tomography cause the resolution to be non-uniform in the reconstructed density. A recent mathematical theory by the P.I. led to a definition of local resolution and to an algorithm for calculating the local resolution. Called, ResMap, this algorithm has been widely downloaded and is included (or will be included soon) in all widely-used cryo-EM packages such as RELION, EMAN, Xmipp (Scipion) and Frealign. This proposal seeks to substantially extend and harden ResMap. First, it seeks to scale up ResMap to deal with large maps. Second, it seeks to create a notion of local anisotropic resolution. Third, it seeks to create adaptive filters so that the density map can be filtered with a kernel whose size varies with local resolution. All of the developments are requested by current users of ResMap. They will be made available through new versions of ResMap which will be hardened by collaboration with users, package developers, the Protein Data Bank (PDB) and the European Research Strategic Infrastructure (ESRI). The PDB and ESRI will make ResMap available over the web.

Public Health Relevance

Electron microscopy provides detailed pictures of large molecular complexes from cells, but these pictures are noisy, and 3D structures created from them can be misinterpreted. The resolution of a 3D structure is the smallest length at which information in the structure is reliable. This research seeks to extend a widely used package for finding resolutions of structures and using them to make explicit what is reliable in a 3D electron microscopy structure.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM114051-02
Application #
9339709
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Flicker, Paula F
Project Start
2016-09-15
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Yale University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520