# Advancing drug-lead and chemical-probe discovery using weighted-ensemble simulations and biophysical validation

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2021 · $293,701

## Abstract

Project Summary
 This project will study La-related protein 1 (LARP1), a molecular switch that allows cells to rapidly increase
protein synthesis. LARP1 stores and protects the mRNA molecules required to make ribosomal proteins. In
response to pro-growth signals or cancer, the mammalian target of rapamycin complex 1 (mTORC1) causes
LARP1 to release its bound mRNAs. Ribosome production surges, leading to rapid increases in protein
synthesis generally.
 Our strong preliminary data has led us to two central hypotheses. First, we hypothesize that LARP1-
binding molecules (ligands) will interfere with the LARP1 mRNA-storage mechanism, thereby reducing protein
synthesis. Second, we hypothesize that better understanding the flexibility of molecule-binding protein
pockets—including LARP1 pockets—will improve rational ligand design. We will test these hypotheses in two
aims. Aim 1 will create a new pocket-centric method for simulating proteins, called SubPEx. We will show that
SubPEx can effectively reveal the flexibility of two well-characterized dynamic pockets (from TEM-1 b-
lactamase and influenza neuraminidase). Aim 2 will use SubPEx, virtual screening, and biophysical
experiments to identify new ligands that bind flexible LARP1 pockets.
 This work is significant in several ways. LARP1 ligands will serve as basic-science tools (chemical probes)
to advance our understanding of LARP1 biology. Additionally, cancer requires extensive protein synthesis, so
molecules that disrupt mTORC1-LARP1 signaling will serve as leads that will further the development of new
therapies. Most mTORC1-pathway inhibitors bind mTOR itself. They are subject to resistance mutations
and/or incomplete inhibition. LARP1 inhibition will provide a unique and innovative pharmacological approach.
 SubPEx itself will also be impactful. Many protein drug targets have highly flexible binding pockets, and
successful structure-based drug design must account for that flexibility. Unlike other methods for exploring
protein flexibility, SubPEx will focus computational effort on the binding pocket itself. Its permissive, open-
source license will encourage adoption. We expect that many in the broader community will also use SubPEx
to design ligands that bind their own disease-relevant proteins of interest.

## Key facts

- **NIH application ID:** 10189658
- **Project number:** 5R01GM132353-03
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Jacob D Durrant
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $293,701
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10189658

## Citation

> US National Institutes of Health, RePORTER application 10189658, Advancing drug-lead and chemical-probe discovery using weighted-ensemble simulations and biophysical validation (5R01GM132353-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10189658. Licensed CC0.

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