英国MRC分子生物学实验室Sjors H. W. Scheres、Dari Kimanius研究组近日取得一项新成果。经过不懈努力，他们发现数据导向的正则化能降低冷冻电镜结构测定的尺寸障碍。该研究于2024年6月11日发表于国际学术期刊《自然-方法学》杂志。

研究人员探索了如何通过深度学习，利用有关生物大分子结构的先验知识来改善图像配准，因为这些知识难以用数学方法表达。研究人员利用电子显微镜数据库（EMDB）的半集重建对校准去噪卷积神经网络，并用这种去噪方法替代常用的平滑度先验。

研究证明，这种被称为 "Blush正则化 "的方法会比现有算法产生更好的重建结果，尤其是在信噪比较低的数据中。对分子量为40 kDa的蛋白质-核酸复合物重建（这在以前难以实现）表明，去噪神经网络将扩大冷冻电镜在多种生物大分子结构测定中的应用。

研究人员表示，利用冷冻电子显微镜（冷冻电镜）确定大分子结构受到单个颗粒噪声图像配准的限制。由于较小颗粒的信号较弱，配准误差对其适用性产生了尺寸限制。

附：英文原文

Title: Data-driven regularization lowers the size barrier of cryo-EM structure determination

Author: Kimanius, Dari, Jamali, Kiarash, Wilkinson, Max E., Lvestam, Sofia, Velazhahan, Vaithish, Nakane, Takanori, Scheres, Sjors H. W.

Issue&Volume: 2024-06-11

Abstract: Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles. Because smaller particles have weaker signals, alignment errors impose size limitations on its applicability. Here, we explore how image alignment is improved by the application of deep learning to exploit prior knowledge about biological macromolecular structures that would otherwise be difficult to express mathematically. We train a denoising convolutional neural network on pairs of half-set reconstructions from the electron microscopy data bank (EMDB) and use this denoiser as an alternative to a commonly used smoothness prior. We demonstrate that this approach, which we call Blush regularization, yields better reconstructions than do existing algorithms, in particular for data with low signal-to-noise ratios. The reconstruction of a protein–nucleic acid complex with a molecular weight of 40 kDa, which was previously intractable, illustrates that denoising neural networks will expand the applicability of cryo-EM structure determination for a wide range of biological macromolecules. Blush regularization makes use of a neural network pre-trained on a diverse set of high-resolution cryo-EM half-maps to improve image alignment, effectively lowering the size barrier, during cryo-EM structure determination.

DOI: 10.1038/s41592-024-02304-8

Source: https://www.nature.com/articles/s41592-024-02304-8