# Project 4: Integrative structure modeling of protein complexes in aggregation

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $306,692

## Abstract

PROJECT SUMMARY
Our broad goal is to contribute to a molecular understanding of neurodegenerative processes, such as prion
propagation and clearance. We propose to achieve this goal by determining the structures of aggregation-related
complexes, including Hsp70-CHIP-tau complex, TREM2 complexes, and 0N4R tau, at near-atomic resolution.
In addition, we propose to characterize the native cellular environment of TREM2, thus bridging the gap between
atomic-resolution complex models and the cellular scale. The target complexes have been largely refractive to
traditional structural biology approaches. Therefore, we will apply integrative structure determination based on
sparse, noisy, and ambiguous data largely produced by the consortium, using a variety of different experimental
methods, including electron microscopy, solid-state nuclear magnetic resonance spectroscopy, chemical cross-
linking with mass spectrometry, soft X-ray tomography, and many others. Structural models will be produced by
satisfying all the data simultaneously, using our Integrative Modeling Platform (IMP) software. The models will
be used to rationalize the existing experimental data and propose new experiments, such as assessing the
phenotypes of relevant point mutations.

## Key facts

- **NIH application ID:** 9937166
- **Project number:** 2P01AG002132-39
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** ANDREJ SALI
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $306,692
- **Award type:** 2
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9937166

## Citation

> US National Institutes of Health, RePORTER application 9937166, Project 4: Integrative structure modeling of protein complexes in aggregation (2P01AG002132-39). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9937166. Licensed CC0.

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