Dept. of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA 92037, USA.
Curr Opin Struct Biol. 2024 Dec;89:102918. doi: 10.1016/j.sbi.2024.102918. Epub 2024 Sep 17.
The application of single particle cryogenic electron microscopy (cryo-EM) to structure determination continues to have a transformative impact on our understanding on biological systems. While there has been a great deal of algorithmic development focused on improving attainable resolutions and streamlining atomic model building, there has not been commensurate development of validation metrics to ensure the accuracy of our cryo-EM maps and models. This review emphasizes the persistent issues that currently complicate single particle cryo-EM structure validation, and highlights the metrics that are gaining broad acceptance by the community. This article aims to underscore the need for further development of validation criteria and the potential role of machine learning methodologies in confidently assessing the quality of cryo-EM structures.
单颗粒低温电子显微镜(cryo-EM)在结构测定中的应用继续对我们对生物系统的理解产生变革性的影响。虽然已经有大量的算法开发专注于提高可达到的分辨率和简化原子模型构建,但没有相应的验证指标的发展来确保我们的 cryo-EM 图谱和模型的准确性。这篇综述强调了目前使单颗粒 cryo-EM 结构验证复杂化的持续问题,并突出了正在被社区广泛接受的指标。本文旨在强调进一步开发验证标准的必要性以及机器学习方法在自信地评估 cryo-EM 结构质量方面的潜在作用。