# Computational rational design of carbohydrate and nucleic acid drug scaffolds with multiscale dynamics and AI

> **NIH NIH R35** · WAYNE STATE UNIVERSITY · 2024 · $365,630

## Abstract

ABSTRACT
Computer aided drug discovery (CADD) can dramatically accelerate and lower costs for the often long and
expensive process of drug development. However, most CADD techniques are created for small organic
molecules, and tend to be less accurate for drugs designed around biological scaffolds or that include
unique chemical properties. The overall goal of the Walker lab is to develop and apply multiscale models
for rational design of complex biomolecules. In this proposal, we detail our strategies to: automate the
creation of large, high quality datasets with accurate simulations, and develop and apply machine learning
(ML) models to design new nucleic acid-based imaging agents and carbohydrate-based drugs.
Carbohydrates, particularly polysaccharides, are highly flexible, and our previous work has demonstrated
the inaccuracy of even very high quality docking scores as compared to experimental affinities. Similarly,
the rational design of synthetic fluorescent nucleobases (SFNs) is challenging because understanding their
photophysics requires computing excited state properties. In both cases, we hypothesize that by creating
ML models that learn the statistical correlation between highly accurate simulations and known
experimental properties, we can both learn new rational design principles and predict novel drug targets.

## Key facts

- **NIH application ID:** 10938272
- **Project number:** 1R35GM154949-01
- **Recipient organization:** WAYNE STATE UNIVERSITY
- **Principal Investigator:** Alice Rachel Walker
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $365,630
- **Award type:** 1
- **Project period:** 2024-09-10 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10938272

## Citation

> US National Institutes of Health, RePORTER application 10938272, Computational rational design of carbohydrate and nucleic acid drug scaffolds with multiscale dynamics and AI (1R35GM154949-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10938272. Licensed CC0.

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