# Advanced Computational Modeling of Molecular Machines in Gene Regulation and DNA Repair

> **NIH NIH R35** · GEORGIA STATE UNIVERSITY · 2021 · $446,372

## Abstract

PROJECT SUMMARY/ABSTRACT
Genomic DNA is the information repository of the cell, encoding the myriad of proteins required to sustain life.
To harness this information, cells depend on RNA polymerases - dynamic biomolecular machines that first
transcribe the genetic code into RNA. Transcription is a complex and highly regulated process that governs cell
growth, differentiation, development and all responses to environmental change. Importantly, the biochemical
pathways that orchestrate the expression and repair of genes are intricately intertwined. As a consequence,
many human diseases trace their origins to deficiencies in gene regulation or DNA repair. Understanding the
molecular-level mechanisms that underlie gene expression and transcription-coupled DNA repair (TCR) is a
grand challenge in biomedical science. Progress toward this goal has been hindered by the size, complexity and
dynamic nature of the assemblies that accomplish transcription and TCR. In initial studies with our experimental
collaborators we combined computational modeling with cryo-electron microscopy data to determine structures
of transcription preinitiation complexes (PICs) from all three classes of RNA polymerases (Pol I, Pol II and Pol
III). The structures captured the PICs in multiple functional states covering the path from promoter recognition to
the formation of a proficient elongation complex. These results offer an unprecedented opportunity for integrative
modeling to connect the experimentally observed states, delineate DNA remodeling during the early stages of
transcription and uncover the critical mechanisms of transcription regulation. Specifically, we will leverage
computational and structural systems biology approaches to 1) determine how the Pol I, II and III transcription
machineries recognize and open promoter DNA; 2) examine how the transcription factor TFIID associates with
promoter DNA and serves as a platform for assembling the PIC; and 3) uncover the key functions of two
recognized TCR master coordinators, transcription factor IIH (TFIIH) and Cockayne Syndrome B protein (CSB).
Our work will benefit from synergistic collaborative interactions with world-class experimental groups to inform,
validate, and extend our models. Parallel advances in computation and cryo-EM will yield key insights into the
structure, dynamics and function of gene regulatory complexes while making direct connection to genetic disease
phenotypes. Success of the project will thus have major impacts - both in understanding the etiology of cancers
and inherited genetic disorders and in offering a structural framework to devise effective treatments.

## Key facts

- **NIH application ID:** 10074956
- **Project number:** 1R35GM139382-01
- **Recipient organization:** GEORGIA STATE UNIVERSITY
- **Principal Investigator:** Ivaylo Nikolaev Ivanov
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $446,372
- **Award type:** 1
- **Project period:** 2021-03-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10074956

## Citation

> US National Institutes of Health, RePORTER application 10074956, Advanced Computational Modeling of Molecular Machines in Gene Regulation and DNA Repair (1R35GM139382-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10074956. Licensed CC0.

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