# Selective targeting of human alkaline phosphatase isozymes

> **NIH NIH SC2** · UNIVERSITY OF TEXAS EL PASO · 2020 · $151,000

## Abstract

Project Summary
The goal of this project is to develop nucleic acid aptamers that can discriminate the four human
alkaline phosphatase isozymes for use in the development of enhanced blood tests. Alkaline
phosphatases catalyze the removal of a phosphate group from proteins, nucleic acids,
carbohydrates, and inorganic pyrophosphate. Humans express four distinct alkaline phosphatase
isozymes; germ cell alkaline phosphatase, intestinal alkaline phosphatase, placental alkaline
phosphatase, and tissue non-specific alkaline phosphatase. Due to the high structural similarity
of these isozymes, it has not been possible to generate monoclonal antibodies that have a
stringent isozyme specificity. Currently available alkaline phosphatase antibodies all display
varying degrees of isozyme cross reactivity, which reduces their usefulness in diagnostic
applications. To address this issue, we will generate nucleic acid aptamers that possess stringent
isozyme specificity using systematic evolution of ligands by exponential enrichment (SELEX). The
binding kinetics of the aptamers will be measured using surface plasmon resonance and purified
alkaline phosphatase isozymes. The aptamer’s detection limit will be determined using an
enzyme-linked aptamer assay.

## Key facts

- **NIH application ID:** 9930991
- **Project number:** 1SC2GM136445-01
- **Recipient organization:** UNIVERSITY OF TEXAS EL PASO
- **Principal Investigator:** Chu-Young Kim
- **Activity code:** SC2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $151,000
- **Award type:** 1
- **Project period:** 2020-03-02 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9930991

## Citation

> US National Institutes of Health, RePORTER application 9930991, Selective targeting of human alkaline phosphatase isozymes (1SC2GM136445-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9930991. Licensed CC0.

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