# Targeting receptor tyrosine kinases with novel methods in computer-aided drug discovery for the treatment of fibrotic renal disease

> **NIH NIH F30** · VANDERBILT UNIVERSITY · 2020 · $47,875

## Abstract

PROJECT SUMMARY
Chronic Kidney Disease (CKD) is a major disease multiplier in patients aged 65+. CKD is characterized by
progressive renal fibrosis mediated through supraphysiologic type IV collagen deposition by renal
myofibroblasts. As the US population continues to age, it becomes increasingly critical to identify new
therapeutic strategies for CKD. Mouse models of kidney injury suggest reducing the activity of the receptor
tyrosine kinase discoidin domain receptor 1 (DDR1) is protective against fibrotic renal disease. Inhibition of
DDR1 kinase reduces mesangial cell deposition of type IV collagen. To develop targeted therapeutics for CKD,
the laboratory of Jens Meiler (sponsor of this application) partners with the laboratories of Ambra Pozzi (co-
sponsor of this application) and Craig Lindsley to create a comprehensive DDR1 kinase inhibitor discovery
pipeline. The Meiler laboratory utilizes a combination of ligand-based quantitative structure-activity relationship
(QSAR) modeling for virtual high-throughput screening (vHTS) and subsequent protein-ligand docking to
identify lead compounds for synthesis/derivatization (Lindsley) and biochemical/functional evaluation (Pozzi).
Selective targeting of individual kinases remains a significant challenge, and current methods in vHTS fail to
account for protein binding pocket features contributing to binding selectivity. The central objectives of this
proposal are to identify novel DDR1-selective inhibitors for the treatment of CKD and to develop new
technologies to address current limitations in vHTS. In Specific Aim I, I will generate and use QSAR models to
perform vHTS for potential DDR1 inhibitors. I will subsequently define a structural model of DDR1 kinase
inhibitor selectivity using molecular dynamics (MD)-generated conformational ensembles of DDR kinases in
conjunction with ROSETTA flexible docking. I will also perform in silico and in vitro site-directed mutagenesis to
further characterize the determinants of DDR1 kinase inhibitor selectivity. In Specific Aim II, I will develop a
multitasking machine algorithm within the Meiler lab BIOLOGY AND CHEMISTRY LIBRARY (BCL) which will
leverage protein structural information in addition to conventional ligand-based descriptors to improve vHTS for
selective DDR1 kinase inhibitors. The methods developed will address long-standing shortcomings in the field
of computer-aided drug discovery (CADD) – namely, that protein structure-based methods are computationally
prohibitive for vHTS while ligand-based methods do not include direct information on binding mode. As the
methods developed in Aim II become available, they will be integrated in the discovery cycle described in Aim I
to ultimately define a structural model of DDR1 kinase selectivity and identify novel therapeutic agents for the
treatment of CKD through the use of new and established methods. Furthermore, novel computational
methods established in these studies will be broadly applicable to other...

## Key facts

- **NIH application ID:** 9952362
- **Project number:** 5F30DK118774-03
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Benjamin Patrick Brown
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $47,875
- **Award type:** 5
- **Project period:** 2018-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9952362

## Citation

> US National Institutes of Health, RePORTER application 9952362, Targeting receptor tyrosine kinases with novel methods in computer-aided drug discovery for the treatment of fibrotic renal disease (5F30DK118774-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9952362. Licensed CC0.

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