Intelligent cryo-electron microscopy of G protein-coupled receptors

在项目的第一年，我们在这方面的研究取得了良好的进展。为项目的开展搭建了主要的研究平台。这包括为与自动样本筛选和基于人工智能的数据采集有关的机器学习任务选择和采购一台功能强大的图形处理器工作站。它于2023年3月安装在鹿儿岛2号园区，2022年上半年还安装了两台新的低温电子显微镜。GPU机器现在连接到显微镜网络，可以直接与显微镜和数据存储服务器通信。安装后，我们开始了必要的软件包的初步性能和稳定性测试和安装，目前仍在进行中。从项目期开始，我们就开始了智能冷冻电子显微镜系统软件平台的开发。它是用Python语言编写的，已经具有分析样本地图的能力，包括网格正方形的识别和量化、支持膜孔的准确定位、每个孔的各种定量参数的测量以及每个网格的全局数据库中所有孔及其属性的枚举。我们还开始测试YOLO深度学习框架在GridNet神经网络中的应用，用于网格正方形、支撑膜孔洞、污染物等的分类。结果非常令人鼓舞，我们可以准确地检测和分类网格正方形。我们还开始测试线性和非线性图像分析，以量化样本条件。

In the first year of the project, we made good progress in this research. We established the main research platform for carrying out the project. This included selection and procurement of a powerful GPU workstation for the machine learning tasks related to automated sample screening and AI-based data acquisition. It was installed in March 2023 at the Kashiwa 2 campus where two new cryo-electron microscopes were also installed in the first half of 2022. The GPU machine is now connected to the microscope network and can communicate directly with the microscope and the data storage server. After installation, we began initial performance and stability testing and installation of the necessary software packages, which are still ongoing.From the beginning of the project period, we started the development of the software platform for the intelligent cryo-electron microscopy system. It is written in Python and already has capabilities for analyzing sample maps, including identification and quantification of grid squares, accurate localization of support film holes, measurement of various quantitative parameters for each hole and enumeration of all holes and their properties in a global database for each grid. We also began testing the YOLO deep learning framework for applications in the GridNet neural network for classification of grid squares, support film holes, contaminants etc. The results are very encouraging, and we can accurately detect and classify grid squares. We also began testing linear and non-linear image analysis for quantification of the sample condition.