De novo atomic protein structure modeling for cryoEM density maps
In recent years, cryo-electron microscopy (cryo-EM) has emerged as a key technology for experimentally determining the structures of large protein complexes and assemblies. The 3D arrangement of atoms provides a mechanistic understanding of molecular processes, offering insights into the fundamental processes of life at the molecular level. Accurately modeling protein atomic structures from cryo-EM density maps is crucial because it reveals how proteins perform their biological functions and interact with other molecules, such as substrates, inhibitors, DNA, RNA, and other proteins. This understanding also enables the design of molecules that can precisely interact with proteins, leading to the development of more effective and specific drugs. Additionally, determining the structures of proteins from pathogens, such as bacteria and viruses, can inform the development of vaccines and treatments.
Our Approach:
We developed Cryo2Struct, a fully automated, ab initio modeling method that generates 3D atomic structures solely from cryo-EM density maps, without using predicted or homologous structures as templates. This method allows for the modeling of atomic structures through direct observation of atoms in the density maps.
Results:
Cryo2Struct achieved substantially better performance than the most widely used de novo modeling method - Phenix in terms of multiple evaluation metrics including C-alpha recall, F1 score, global normalized TM-score, aligned C-alpha length, C-alpha match score, C-alpha sequence match score, and C-alpha quality score. In general, it can build much more accurate and more complete protein structures from cryo-EM density maps than Phenix, therefore advancing the state of the art of ab initio modeling of protein structures on cryo-EM density maps and providing a useful means for the community to build better protein structural models from both existing cryo-EM density maps and new ones to be generated to support biomedical research. More detailed results and analysis are available in the manuscript, which can be accessed here: https://doi.org/10.1038/s41467-024-49647-6 .
Code:
The source code for Cryo2Struct is open-source and available in the GitHub repository: https://github.com/jianlin-cheng/Cryo2Struct. This repository also includes instructions on running Cryo2Struct on cryo-EM maps to generate 3D atomic protein structures.
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