# Analysis of protein interactions in neurodegenerative disease

> **NIH NIH R01** · SCRIPPS RESEARCH INSTITUTE, THE · 2022 · $693,264

## Abstract

Summary/Abstract
Late Onset Alzheimer's disease (LOAD) is the most common form of age-related dementia.
Currently, 5 million people in the US are afflicted with LOAD and with the aging population this
number is expected to double in the next decades. There are no drugs to cure or halt the
progression of LOAD. The two pathological hallmarks of LOAD are extracellular amyloid plaques
formed by the insoluble A peptide and neurofibrillary tangles consisting of hyperphosphorylated
Tau protein. To date, most clinical drug candidates have targeted A, but none have proven
effective at ameliorating the symptoms of AD. New drug targets are needed to combat this
increasingly common and devastating disease. The recent identification of LOAD risk factors has
revealed an enrichment of proteins in the endosomal-lysosomal network (ELN). This
corroborates decades of evidence that the disruption of the ELN is an early event in LOAD
pathogenesis and indicates that the ELN contains potential drug targets. However, a lack of
molecular characterization of ELN has prevented the discovery of suitable candidates. Once
considered “undruggable”, protein-protein interactions (PPI) are emerging as attractive targets for
drug development. Global analysis of PPI in the ELN has not been studied. We propose to use
mass spectrometry to quantitate different biochemical characteristics ELN protein complexes and
determine how LOAD induces alterations in PPI within the ELN. These experiments will be
performed in human brain tissues (AD vs. age-matched controls) and in human AD and control
IPSC derived neurons and organoids. Endogenous ELN targets will be immunoprecipitated with
validated antibodies and quantitated between conditions to identify novel ELN interactors and
disease-relevant drug targets. Quantitation will be performed using multiplexing isobaric labeling
technology. The structure of the ELN complexes will also be resolved, and differences will be
quantitated with using our Covalent Protein Painting method. Additionally, we will employ a novel
application of the non-canonical amino acid, azidohomoalanine, to quantitate the stability of ELN
protein complexes. Our proposal will produce three different quantitative measurements of the
influence of LOAD pathogenesis on ELN protein complexes and will provide alternative drug
development targets for the most common form of age-related dementia.

## Key facts

- **NIH application ID:** 10423610
- **Project number:** 1R01AG077046-01
- **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE
- **Principal Investigator:** John R Yates III
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $693,264
- **Award type:** 1
- **Project period:** 2022-05-01 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10423610

## Citation

> US National Institutes of Health, RePORTER application 10423610, Analysis of protein interactions in neurodegenerative disease (1R01AG077046-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10423610. Licensed CC0.

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