Determining structures of individual RNA conformers using atomic force microscopy images and deep neural networks.

ABSTRACT: The vast percentage of the human genome is transcribed into RNA, many of which contain various structural elements and are important for functions. RNA molecules are conformationally heterogeneous and functionally dyanmics¹, even when they are structured and well-folded², which limit the applicability of methods such as NMR, crystallography, or cryo-EM. Moreover, because of the lack of a large structure RNA database, and no clear correlation between sequence and structure, approaches like AlphaFold³ for protein structure prediction, do not apply to RNA. Therefore determining the structures of heterogeneous RNA is an unmet challenge. Here we report a novel method of determining RNA three-dimensional topological structures using deep neural networks and atomi

SUBMITTER: Degenhardt MFS 

PROVIDER: S-EPMC10327248 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature