# Harnessing simulations to uncover molecular mechanisms of mechanosensing

> **NIH NIH R35** · NEW YORK UNIVERSITY · 2021 · $375,981

## Abstract

Project Summary
In order to perform some of their most important functions, cells must be able to generate, sense, and
respond to mechanical forces. Many “mechanosensing” proteins have been discovered that are
believed to change their behavior in a predictable and repeatable way when under mechanical tension.
Yet, in most of these cases, we don’t know the molecular basis of how this force shifts the
conformations adopted by the protein, or how this then leads to a concomitant change function. The
molecular basis of mechanosensing can in principle be predicted using molecular simulation
techniques, however this approach has either not been employed or not been successful because of
the small magnitude of forces involved and the large size and complexity of the mechanosensors. In
this work, we will develop a set of new simulation methodologies to properly sample protein
conformations and protein-ligand biding lifetimes at a range of small forces. We will employ these
techniques to study mechanosensing in three different contexts where we believe three distinct
mechanisms for changing behavior in response to force are employed. Overall, the work in these
studies will lead to a much greater understanding of the molecular paradigms used by cells to regulate
their behavior in response to mechanical stimuli, and expand our simulation toolbox to be able to
properly sample and assess their response to physiologically small forces.

## Key facts

- **NIH application ID:** 10247789
- **Project number:** 5R35GM138312-02
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Glen Hocky
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $375,981
- **Award type:** 5
- **Project period:** 2020-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10247789

## Citation

> US National Institutes of Health, RePORTER application 10247789, Harnessing simulations to uncover molecular mechanisms of mechanosensing (5R35GM138312-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10247789. Licensed CC0.

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