# Defining the multi-dimensional code of zinc finger specificity-Resubmission-1

> **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2021 · $393,339

## Abstract

Project Summary
The Cys2His2 zinc finger DNA-binding domain is the most common domain in human yet the DNA-binding
specificities for the great majority of these proteins remain undefined. Mutations in many of these domains,
both with and without known DNA-binding data, have been linked to a host of diseases from Alzheimers
(REST) to Cancer (e.g. Slug, WT1, CTCF). Therefore, the characterization of these proteins holds great value.
Unfortunately common methodologies used to determine the DNA-binding specificity of transcription factors
have failed to address the zinc finger, at least in part because of an inability to fully define the large target
specificities required of the average mammalian zinc finger protein. Even when ChIP-Seq data exists it is
limited because the size of the genome does not allow us to capture the full binding potential of a factor that
could offer a ≥21bp target sequence. As a result, without a comprehensive understanding of a protein’s binding
potential, SNPs across the genome will continue to represent potential binding sites that we are unable to
predict. In sum, decades of research have enlightened our understanding of this domain but we are still in the
dark when it comes to its function as a transcription factors. Recently we have taken an alternative approach to
define this domain, demonstrating that a synthetic, one-by-one screen of individual zinc fingers allows us to
predict the specificity of multi-fingered proteins with similar or greater accuracy than all prior prediction
algorithms. However, this approach fails to take into consideration the influences that adjacent fingers have on
one another. We have produced the equivalent of a comprehensive snapshot of what a zinc finger is capable
of in just one of many potential contextual environments. Here we propose to scale this approach and screen
the zinc finger under an inclusive set of contextual environments. We will consider the most common direct and
indirect influences on adjacent finger binding as well as factors that impact the geometry with which the zinc
fingers engage the DNA. We will use these results to provide a complete picture of how adjacent zinc fingers
determine their specificity and by scaffolding these two-fingered models, predict and design the specificity of
large, multi-fingered proteins. In this way, we will define a multi-dimensional code of zinc finger specificity
that allows us to predict all zinc finger DNA-binding specificities, how any neighbor finger context
would modify this specificity, and the factors that result in adjacent finger incompatibility and loss of
DNA-binding function. We will apply this model to predict the specificity of all human zinc finger proteins,
validate these predictions through in vivo characterization of an informed set of transcription factors, and test
predicted mechanisms of multi-fingered binding with designer, artificial factors.

## Key facts

- **NIH application ID:** 10093062
- **Project number:** 5R01GM118851-05
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Marcus Blaine Noyes
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $393,339
- **Award type:** 5
- **Project period:** 2017-02-16 → 2023-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10093062

## Citation

> US National Institutes of Health, RePORTER application 10093062, Defining the multi-dimensional code of zinc finger specificity-Resubmission-1 (5R01GM118851-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10093062. Licensed CC0.

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