# The Computational Pharmacology Core

> **NIH NIH P01** · WASHINGTON UNIVERSITY · 2020 · $153,218

## Abstract

Core B: Computational Systems Pharmacology
Project Summary
The Computational Systems Pharmacology Core (Core B) will provide computational biology and
quantitative systems pharmacology (QSP) support to Projects 1-3. The Core will contribute to the
research goals of the P01 in three major ways: identification of targets (proteins, pathways or
networks) implicated in ATZ accumulation (Specific Aim 1); quantitative modeling and analysis of the
cellular networks identified to be associated with ATZ elimination, and systematic interrogation of
these networks to generate plausible hypotheses for (poly)pharmacological strategies (Specific Aim
2); and refinement of drug candidates discovered in the first term (e.g. glibenclamide and its analog
G2, cyclodextrin family members, and selected agonists of mucolipins) and identification of new
testable candidates (both repurposable drugs and new compounds) to assist in the design and
development of mechanism-based ATD therapeutics (Specific Aim 3). In line with the progress and
contributions made in the first term, the Core will analyze high-throughput/content (RNAi, EMS
chemical mutagenesis, and small-molecule library screening) data collected by Project 2 and gene
expression profile data of ATZ-expressing iPS cells (Project 3). Quantitative model construction and
analyses will support Project 1 team to assess (i) the cell signaling and regulation mechanisms that
predominantly determine the cell fate in response to the proteotoxic effect of ATZ accumulation, with
focus on autophagic, proteostasis and calcium signaling pathways; (ii) the pathophysiological effects
of sequence variants detected in cohort exome sequencing studies (in coordination with Project 3);
(iii) optimal modifications of drug candidates to increase their potency, and particular combination
therapies (e.g. prochlorperazine and amlodipine) that may act synergistically. The Core will use a
broad range of machine learning algorithms, and bioinformatics, cheminformatics, QSP and
molecular modeling methods, tools and software developed by the Core members as well as relevant
databases and software publicly available.

## Key facts

- **NIH application ID:** 9994909
- **Project number:** 5P01DK096990-07
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Ivet Bahar
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $153,218
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9994909

## Citation

> US National Institutes of Health, RePORTER application 9994909, The Computational Pharmacology Core (5P01DK096990-07). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9994909. Licensed CC0.

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