# Gating Mechanisms of Retinal Cyclic Nucleotide-Regulated Ion Channels

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2021 · $377,087

## Abstract

Hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels were first
discovered in photoreceptors where they shape the light response. They exhibit several
properties that make them specialized for retinal signaling: 1) they are weakly K+
selective, 2) they are activated by membrane hyperpolarization, instead of depolarization
seen in virtually every other voltage-gated channel, and 3) they are regulated by the
direct binding of cyclic nucleotides to an intracellular domain. Our long term goal is to
understand the molecular mechanisms for these properties to better understand the
physiology and pathophysiology of the channels in the brain and heart. In previous
funding periods we have made great progress toward achieving this goal. We have
solved the molecular structures of HCN and related channels and invented ground-
breaking new fluorescence methods that allow us to record molecular rearrangements in
intact channels simultaneous with electrophysiological recording. In this funding period,
we propose to apply these methods to determine the molecular mechanisms of
hyperpolarization activation and cyclic nucleotide modulation. These experiments will
lead to the first dynamic picture for how HCN channels regulate the excitability of
neurons and cardiomyocytes.

## Key facts

- **NIH application ID:** 10162596
- **Project number:** 5R01EY010329-27
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** William N Zagotta
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $377,087
- **Award type:** 5
- **Project period:** 1994-01-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10162596

## Citation

> US National Institutes of Health, RePORTER application 10162596, Gating Mechanisms of Retinal Cyclic Nucleotide-Regulated Ion Channels (5R01EY010329-27). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10162596. Licensed CC0.

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