Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan.
AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory (RWBC-OIL), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Int J Mol Sci. 2022 Feb 10;23(4):1977. doi: 10.3390/ijms23041977.
Application of cryo-electron microscopy (cryo-EM) is crucially important for ascertaining the atomic structure of large biomolecules such as ribosomes and protein complexes in membranes. Advances in cryo-EM technology and software have made it possible to obtain data with near-atomic resolution, but the method is still often capable of producing only a density map with up to medium resolution, either partially or entirely. Therefore, bridging the gap separating the density map and the atomic model is necessary. Herein, we propose a methodology for constructing atomic structure models based on cryo-EM maps with low-to-medium resolution. The method is a combination of sensitive and accurate homology modeling using our profile-profile alignment method with a flexible-fitting method using molecular dynamics simulation. As described herein, this study used benchmark applications to evaluate the model constructions of human two-pore channel 2 (one target protein in CASP13 with its structure determined using cryo-EM data) and the overall structure of V-ATPase complex.
低温电子显微镜（cryo-EM）的应用对于确定核糖体和膜蛋白复合物等大型生物分子的原子结构至关重要。低温电子显微镜技术和软件的进步使得获得接近原子分辨率的数据成为可能，但该方法通常只能产生部分或全部具有中等到高分辨率的密度图。因此，需要弥合密度图和原子模型之间的差距。在这里，我们提出了一种基于低分辨率到中等分辨率 cryo-EM 图构建原子结构模型的方法。该方法是使用我们的轮廓轮廓比对方法进行灵敏和准确的同源建模与使用分子动力学模拟的灵活拟合方法的结合。如本文所述，这项研究使用基准应用来评估人双孔通道 2（CASP13 中的一个目标蛋白，其结构使用 cryo-EM 数据确定）和 V-ATPase 复合物的整体结构的模型构建。
