CNB-CSIC, C/Darwin 3, 28049 Madrid, Spain.
Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic.
J Chem Inf Model. 2020 May 26;60(5):2533-2540. doi: 10.1021/acs.jcim.9b01032. Epub 2020 Feb 11.
Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.
冷冻电子显微镜（cryo-EM）技术的进步使得在近原子分辨率下获得大型生物大分子结构成为可能。这场“分辨率革命”鼓励了建模工具的使用和发展，这些工具能够从 cryo-EM 密度图中生成高质量的原子模型。不幸的是，在同一个处理工作流程中结合不同的软件包会出现许多实际问题，这使得非专业人士难以使用这些工具，从而降低了它们的实用性。我们在这里介绍了图像处理框架的一个重大扩展，该框架提供了模型构建领域的软件包集成，并全面跟踪从图像处理到结构验证的整个工作流程。
