Literature DB >> 29782796

Resolution Measurement from a Single Reconstructed Cryo-EM Density Map with Multiscale Spectral Analysis.

Yu-Jiao Yang1, Shuai Wang1, Biao Zhang1, Hong-Bin Shen1.   

Abstract

As a relatively new technology to solve the three-dimensional (3D) structure of a protein or protein complex, single-particle reconstruction (SPR) of cryogenic electron microscopy (cryo-EM) images shows much superiority and is in a rapidly developing stage. Resolution measurement in SPR, which evaluates the quality of a reconstructed 3D density map, plays a critical role in promoting methodology development of SPR and structural biology. Because there is no benchmark map in the generation of a new structure, how to realize the resolution estimation of a new map is still an open problem. Existing approaches try to generate a hypothetical benchmark map by reconstructing two 3D models from two halves of the original 2D images for cross-reference, which may result in a premature estimation with a half-data model. In this paper, we report a new self-reference-based resolution estimation protocol, called SRes, that requires only a single reconstructed 3D map. The core idea of SRes is to perform a multiscale spectral analysis (MSSA) on the map through multiple size-variable masks segmenting the map. The MSSA-derived multiscale spectral signal-to-noise ratios (mSSNRs) reveal that their corresponding estimated resolutions will show a cliff jump phenomenon, indicating a significant change in the SSNR properties. The critical point on the cliff borderline is demonstrated to be the right estimator for the resolution of the map.

Mesh:

Substances:

Year:  2018        PMID: 29782796     DOI: 10.1021/acs.jcim.8b00149

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  2 in total

Review 1.  Emerging Themes in CryoEM─Single Particle Analysis Image Processing.

Authors:  Jose Luis Vilas; Jose Maria Carazo; Carlos Oscar S Sorzano
Journal:  Chem Rev       Date:  2022-07-04       Impact factor: 72.087

2.  EMNUSS: a deep learning framework for secondary structure annotation in cryo-EM maps.

Authors:  Jiahua He; Sheng-You Huang
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.