# Mesoscale spatial kinetic modeling of cell systems

> **NIH NIH R01** · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · 2021 · $344,400

## Abstract

This project proposes to develop new network-free spatial modeling software at the mesoscale -
occupying the niche between detailed molecular dynamics and cellular reaction-diffusion
systems. Specifically, we plan to address spatial scales in the range of 50nm – 2µm and
temporal scales within the range of 100µs to 10s. Examples of systems that would benefit from
modeling tools at this “mesoscale” are receptor signaling platforms and clusters (e.g. the
immune synapse or the post-synaptic density), cell adhesion complexes, lipid rafts, chromatin
organization, cytoskeletal dynamics, and nucleoprotein phases. Our approach builds on the
foundation of the SpringSaLaD software, which uses a Langevin dynamics formalism to model
multi-molecular interactions with explicit excluded volumes. It permits spatial simulations of
combinatorially complex processes such as clustering and polymerization. The approach is an
amalgam of kinetic and molecular modeling, in that it derives probabilities of reactions from both
coarse structural features of the molecules and macroscopic biochemical parameters such as
on and off rate constants, diffusion coefficients and allosteric state transition rates. Currently
SpringSaLaD represents molecules as spherical “sites” connected by linear linkers, modeled as
stiff springs. Molecules can diffuse and react either in a rectangular volume or be anchored to a
planar patch of membrane. Our Specific Aims propose to dramatically expand the scope of
SpringSaLaD by allowing more realistic representation of structural details and expanding the
range of biophysical mechanisms that can be modelled. To better account for the influence of
membrane curvature on clustering and the possibility of assemblies that span across thin
processes such as filopodia or endocytic invaginations, we will implement methods for Brownian
dynamics along curved membranes. We will develop methods to derive the arrangement of
spherical sites and linkers from more realistic 3D molecular data, including atomic coordinates.
We will develop new optional schemes to better account for the rigidity of molecular structures
at this coarse-grained level and, separately, the flexibility of linker domains; the latter will help us
represent the influence of intrinsically disordered domains. We will develop statistical and
analytical methods to analyze simulation results and build lumped models so as to bridge from
this mesoscale to the full cell scale. Finally, we propose to support mechanochemistry by
accounting for local force experienced by a site and appropriately altering probabilities for
unbinding (i.e. off rates), binding (on-rates) and the tension at membrane surfaces. Ultimately,
the SpringSaLaD functionality will be incorporated within the Virtual Cell software system.

## Key facts

- **NIH application ID:** 10189659
- **Project number:** 5R01GM132859-03
- **Recipient organization:** UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
- **Principal Investigator:** LESLIE M LOEW
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $344,400
- **Award type:** 5
- **Project period:** 2019-09-20 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10189659

## Citation

> US National Institutes of Health, RePORTER application 10189659, Mesoscale spatial kinetic modeling of cell systems (5R01GM132859-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10189659. Licensed CC0.

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