# Defining the Rules for Designing Fully Chemically Modified siRNAs to Treat Genetically Linked Central Nervous System Disorders

> **NIH NIH F31** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2021 · $31,030

## Abstract

PROJECT SUMMARY
Small interfering RNA (siRNA) therapeutics specifically and potently block the expression of disease-related
genes. siRNA clinical utility is currently limited to disease targets in the liver, but the Khvorova lab has
developed a novel, fully chemically modified siRNA platform that enables delivery to the central nervous
system (CNS) and results in potent modulation of gene expression in mouse and monkey brain for 6 months.
This technology provides an opportunity to treat genetically-defined neurological disorders, including
Huntington’s disease, amyotrophic lateral sclerosis, and Alzheimer’s disease (AD).
Extensive chemical modification protects siRNAs from degradation and is essential for in vivo delivery, but
lowers the gene silencing efficacy of many siRNA sequences. Bioinformatics algorithms have been developed
to predict the activity of non-modified siRNAs, but these algorithms cannot predict whether a chemically
modified siRNA will be functional. Identifying a hyperfunctional siRNA chemical modification pattern and
developing a predictive algorithm for modified siRNA sequences will be critical for the widespread application
of this platform in vivo to treat AD and other genetically-linked neurological disorders. The goal of this proposal
is to identify parameters that impact the silencing efficacy of chemically modified siRNAs.
Aim 1 will identify the step(s) that limit the activity of chemically modified siRNAs. Using a validated AGO2-
immunoprecipitation technique and a small RNA high-throughput sequencing protocol, loading of 32 chemically
modified siRNA sequences, each with 3 different chemical modification patterns, into RNA-induced silencing
complex (RISC) will be quantified, and these results will be compared to their in vitro silencing activity. These
efforts will provide a data set to determine the impacts of chemistry and sequence on the different steps of
RISC function. Aim 2 will design and screen 192 siRNAs in 6 different chemical modification patterns (i.e., for a
total of 1152 siRNAs) to systematically assess if and how changes to siRNA sequence and chemical
modification patterns impact siRNA efficacy. These 1152 siRNAs will target 4 different mRNAs identified as
therapeutic targets for AD. Completing this aim will identify siRNAs that effectively reduce the expression of AD
targets. Using multiple bioinformatics analysis methods, including multi-parameter linear regression, support
vector machine, and random forest, Aim 3 will model algorithms that specifically predict functional, chemically
modified siRNAs. The best performing algorithm will be determined by independent and cross-validations.
Completion of this project will decrease the extent of in vitro screening needed to identify functional chemically
modified siRNAs capable of targeting disease genes in the CNS and streamline the design of siRNA therapies
to treat genetically-defined neurological disorders.

## Key facts

- **NIH application ID:** 10158011
- **Project number:** 5F31LM013111-02
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** Sarah Marie Davis
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $31,030
- **Award type:** 5
- **Project period:** 2020-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10158011

## Citation

> US National Institutes of Health, RePORTER application 10158011, Defining the Rules for Designing Fully Chemically Modified siRNAs to Treat Genetically Linked Central Nervous System Disorders (5F31LM013111-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10158011. Licensed CC0.

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