Building protein structure models for intermediate resolution cryo-electron microscopy maps

NIH RePORTER · NIH · R01 · $305,459 · view on reporter.nih.gov ↗

Abstract

Project Summary Cryo-electron microscopy (cryo-EM) is an emerging technique in structural biology, which is capable of determining three-dimensional (3D) structures of biological macromolecules. Compared to conventional structural biology techniques, such as X-ray crystallography and NMR, a major advantage of cryo-EM is its ability to solve large macromolecular assemblies. Moreover, recent technical breakthroughs in cryo-EM have enabled determination of 3D structures at nearly atomic-level resolutions. Cryo-EM will undoubtedly become a method of central importance in structural biology in the next decade. With the rapid accumulation of cryo-EM structure data, it has become crucial to develop computational methods that can effectively build and extract 3D structures of biological macromolecules from EM maps. The goal of this project is to develop computational methods for modeling both global and local structures and for interpreting 3D structures embedded in EM maps of around 4 Å to medium-resolution. Recently, we have developed a new de novo protein structure modeling method, MAINMAST, which can model protein structures from an EM density map without using existing template or fragment structures on the map. Based on the successful development of MAINMAST, we further extend the capability of MAINMAST toward more accurate modeling and for multiple-chain modeling. In addition, we will also develop novel modeling methods for medium-resolution EM maps, which combine a coarse-grained protein structure modeling technique, methods in protein structure prediction, and a low- resolution image processing approach with deep learning, a state-of-the-art powerful machine learning method. The proposed project capitalizes on the tremendous efforts and progress made in structural determination with cryo-EM by developing computational tools that allow researchers to perform efficient and reliable structure analyses for 3D EM density maps. The project will greatly facilitate investigation into the molecular mechanisms of macromolecule function by providing an efficient means of 3D structure modeling.

Key facts

NIH application ID
9971996
Project number
1R01GM133840-01A1
Recipient
PURDUE UNIVERSITY
Principal Investigator
Daisuke Kihara
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$305,459
Award type
1
Project period
2020-09-20 → 2024-07-31