# Computational Methods for In-Situ Structure Determination using Cryo-ET

> **NIH GM R35** · DUKE UNIVERSITY · 2026 · $482,750

## Abstract

PROJECT SUMMARY
Understanding how proteins interact within the cell to perform specific functions is a central goal of modern
biology and crucial for understanding the diverse roles these molecules play in biomedicine. Single-particle
cryo-electron tomography (SP-cryo-ET) is currently the only technology capable of visualizing macromolecules
in their native environment at high resolution. Despite recent advances in sample preparation, data acquisition,
and image processing, structural analysis by SP-cryo-ET is still largely confined to naturally abundant
targets—such as ribosomes or ordered supramolecular assemblies—or to resolutions that are insufficient to
reveal molecular-level interactions. Furthermore, the complexity and high computational demands of
SP-cryo-ET workflows for data processing have restricted access to the technology for structural biologists.
These challenges present a significant barrier to fully unlocking the potential of SP-cryo-ET in advancing our
understanding of how proteins interact within cells to carry out specific functions and the essential roles they
play in biology and disease. Building on recent progress made by our group, the goal of this project is to
develop methods to address remaining bottlenecks in the SP-cryo-ET workflow that will result in broader
applicability and improved access. Our long-term goal is to enable the routine visualization of a wide range of
biomedically important targets in the cellular context at near-atomic resolution. By working closely with a
network of experimental collaborators, we will ensure that our method development efforts are driven by
diverse and impactful biological projects. Ultimately, our tools will help expand the applicability of SP-cryo-ET
and accelerate its adoption, empowering structural biologists to tackle new questions regarding molecular
interactions and cellular mechanisms.

## Key facts

- **NIH application ID:** 11330742
- **Project number:** 1R35GM163737-01
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Alberto  Bartesaghi
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** GM
- **Fiscal year:** 2026
- **Award amount:** $482,750
- **Award type:** 1
- **Project period:** 2026-05-01T00:00:00 → 2031-02-28T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11330742

## Citation

> US National Institutes of Health, RePORTER application 11330742, Computational Methods for In-Situ Structure Determination using Cryo-ET (1R35GM163737-01). Retrieved via AI Analytics 2026-07-13 from https://api.ai-analytics.org/grant/nih/11330742. Licensed CC0.

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