# Direct Electrical Measurement of Proteasome Activity for Single-Molecule Protein Sequencing

> **NIH NIH R21** · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · 2022 · $431,750

## Abstract

Project Summary
Direct electronic measurement of protease activity may yield signals that can be interpreted in terms of the
amino acid sequence being processed by the proteasome. This proposal seeks to explore these signals (using
a scanning tunneling microscope) and, from these experiments, layout the design parameters for solid state
devices that can be multiplexed. As simple 2 terminal devices with no optical or electrolyte reservoirs (as
required for nanopore devices) current technology should yield die with >10,000 devices, leading to possible
total read speeds of 106 amino acids per second. As a single-molecule counting device, the dynamic range
would be limited only by the recording time, so that a range of 109:1 may be possible. In this exploratory R21
phase, we will synthesize two types of proteasome with chemical tags that allow for incorporation into an
electronic circuit, and record the current variations that occur as different peptides are processed. We will
explore the processing of intact proteins when an unfoldase is also present. We will use machine learning to
explore ways in which amino acid sequence information can be extracted from the stochastic electronic signals
that we expect the proteasomes will produce.

## Key facts

- **NIH application ID:** 10496255
- **Project number:** 1R21HG012538-01
- **Recipient organization:** ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- **Principal Investigator:** STUART LINDSAY
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $431,750
- **Award type:** 1
- **Project period:** 2022-08-12 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10496255

## Citation

> US National Institutes of Health, RePORTER application 10496255, Direct Electrical Measurement of Proteasome Activity for Single-Molecule Protein Sequencing (1R21HG012538-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10496255. Licensed CC0.

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