Abstract

Single particle reconstruction using Cryo-Electron Microscopy (cryo-EM) is an emerging technique in structural biology for estimating the 3-D structure (density) of protein macromolecules. Unlike tomography where a large number of images of a specimen can be acquired, the number of images of an individual particle is limited because of radiation damage. Instead, the specimen consists of identical copies of the same protein macro-molecule embedded in vitreous ice at random and unknown 3-D orientations. Because the images are extremely noisy, thousands to hundreds-of-thousands of projections are needed to achieve the desired resolution of 5A. Along with differences of the imaging modality compared to photographs, single particle reconstruction provides a unique set of challenges to existing computer vision algorithms. Here, we introduce the challenge and opportunity of reconstruction from transmission electron micrographs, and briefly describe our contributions in areas of particle detection, contrast transfer function (CTF) estimation, and initial 3-D model construction. Reconstructing the Structure of Protein Macromolecules One of the most exciting challenges for biology today is understanding the molecular machinery of the cell as a working, dynamic system. Critical to this understanding is determining the 3-D structure of protein macromolecules, a task that is often accomplished using x-ray crystallography. The technique of cryo electron microscopy (cryo-EM) has a unique role to play in addressing this challenge as it can provide structural information of large macromolecular complexes in a variety of conformational and compositional states while preserved under close to physiological conditions. Traditionally the methods for cryo-EM have been time consuming and labor intensive, involving data acquisition, analysis and averaging of thousands to hundreds of thousands of images (views) of the individual macro-molecular complexes. Thus, over the last few years there has been considerable interest and substantial effort devoted to developing automated methods to improve the accuracy, robustness, ease of use, and throughput of cryo-EM [1, 2, 3, 12, 15, 17], and this abstract considers three aspects originally presented in [9, 10, 11]. 1

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