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

> **NIH NIH R01** · PURDUE UNIVERSITY · 2020 · $305,459

## 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 organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Daisuke Kihara
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $305,459
- **Award type:** 1
- **Project period:** 2020-09-20 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971996

## Citation

> US National Institutes of Health, RePORTER application 9971996, Building protein structure models for intermediate resolution cryo-electron microscopy maps (1R01GM133840-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9971996. Licensed CC0.

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