# Structural studies of chromatin complexes

> **NIH NIH R35** · PENNSYLVANIA STATE UNIVERSITY, THE · 2024 · $619,471

## Abstract

Project Summary/Abstract
 The nucleosome is the hub of signals that regulate gene expression in eukaryotic cells. An important
mechanism of such regulation is the post-translational modification of the histone protein components of the
nucleosome. However, we possess only a rudimentary mechanistic understanding for how these modifications
are installed on the physiological nucleosome substrates by histone modification enzymes and subsequently
read by epigenetic reader proteins. These shortcomings limit our ability to interpret the wealth of genetic,
genomic and biochemical data available, and they hamper development of new therapeutics that target
epigenetic chromatin enzymes and readers associated with human diseases including cancer. We are
focused on addressing these deficiencies through structural and biochemical studies of histone modification
enzymes and readers in complex with the nucleosome. We leverage structural models produced using
cryoelectron microscopy to develop mechanistic hypotheses and then challenge these models through
nucleosome-based binding and enzymatic assays. Our studies of epigenetic histone modification enzymes
and readers should impact both our basic science understanding of gene regulation and therapeutics for
human diseases.

## Key facts

- **NIH application ID:** 10842689
- **Project number:** 2R35GM127034-06
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** SONG TAN
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $619,471
- **Award type:** 2
- **Project period:** 2018-09-01 → 2029-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10842689

## Citation

> US National Institutes of Health, RePORTER application 10842689, Structural studies of chromatin complexes (2R35GM127034-06). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10842689. Licensed CC0.

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