# NOT-GM-21-028:Towards a generalizable drug discovery framework based on intrinsically disordered regions

> **NIH NIH R01** · BRIGHAM AND WOMEN'S HOSPITAL · 2021 · $14,320

## Abstract

Project Summary
Current approaches to drug discovery are yielding diminishing returns as costs, failure rate, and
drug resistance all increase. Meanwhile, novel targets and drug candidates are not keeping up
with demand across the disease spectrum. This work seeks to address several of these areas.
It seeks to lower cost, increase success rate, and address drug resistance while increasing
novel targets and potential drug candidates.
While most drugs are found by trial-and-error or designed for specific structured protein pockets,
it turns out that many diseases and drug resistance occur at interfaces involving disordered
protein regions. So, while most informatics for drug design has focused on structured protein
pockets, an area with tremendous potential lies in disordered proteins and their interfaces. To
do so effectively, and at a large-scale, an informatics framework is needed that effectively uses
information across genomic, proteomic, structural, chemical, pathway, ontological, interaction
modeling, and evolutionary space.
Here, we present such a framework that creates: 1) disordered target libraries and
corresponding small molecules to interact them and 2) small molecules that can mimic
disordered regions and thus interact with the usual partners of the disordered protein regions.
We will first create a disordered target library across several organisms. Then, through a
Bayesian framework, we will integrate expert knowledge, sequence information/statistics, and
interaction modeling to predict drugs that can: 1) target these regions and 2) mimic these
regions in interactions. Finally, we will focus on drug resistant pathogens to validate predicted
drugs experimentally.

## Key facts

- **NIH application ID:** 10393070
- **Project number:** 3R01GM118467-06S1
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** GIL ALTEROVITZ
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $14,320
- **Award type:** 3
- **Project period:** 2016-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10393070

## Citation

> US National Institutes of Health, RePORTER application 10393070, NOT-GM-21-028:Towards a generalizable drug discovery framework based on intrinsically disordered regions (3R01GM118467-06S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10393070. Licensed CC0.

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