Helical Indexing in Real Space.

ABSTRACT: Biological structures with helical symmetries of distinct twist, rise, and axial symmetry are abundant and span a wide range of organisms and functions. Performing de novo helical indexing remains challenging because of the steep learning curve involved in Fourier space layer lines. The unknown amount of out-of-plane tilt and the existence of multiple conformations of the helices further complicate indexing. In this work, we introduce a real-space indexing method that leverages the prior knowledge of the tilt and in-plane angles of the helical filaments/tubes, robust ab initio 3D reconstruction capabilities in single particle cryo-EM to obtain asymmetric reconstructions, and automatic indexing of helical parameters directly from the asymmetric density maps. We validated this approach using

SUBMITTER: Sun C 

PROVIDER: S-EPMC9114412 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature