cryoMDM; Molecular simulation Driven structural Matching Approach to Estimate Variety of Atomic Three-dimensional Model Based on Noisy cryoEM Single Particle Images.

Understanding the structure of biomolecules is essential for comprehending life phenomena. In recent years, cryo-electron microscopy (cryoEM) single-particle structure analysis has made remarkable advancements. The single-particle images obtained from cryoEM measurements have a poor signal-to-noise ratio, and existing methods rely on multi-image analysis, which averages multiple measurement data to achieve high-resolution structures. However, this multi-image approach statistically processes several measurement images, causing the unique structural features of individual data to be lost. To overcome this inherent challenge, we developed a molecular simulation-driven structural matching method, cryoMDM, which identifies the plausible structure for cryoEM two-dimensional images from a vast number of three-dimensional (3D) structural model candidates generated through molecular simulations. The innovative aspect of this method is that it enables the estimation of 3D atomic models from a single-particle image, going beyond merely generating a 3D electron density map. By linking each cryoEM particle image to a 3D structure in the simulation space, we can directly connect cryoEM measurement data to continuous structural changes in biomolecules. Applying this method to the spike protein derived from SARS-CoV-2, we successfully captured various intermediate structures of the spike protein, revealing critical information about the early stages of viral entry.