# Computational models for the signaling of tumor necrosis factor receptor on cell surfaces

> **NIH NIH R01** · ALBERT EINSTEIN COLLEGE OF MEDICINE · 2020 · $327,738

## Abstract

Project Summary
The innate immune system constitutes the first line of host defense. The invasion of external
pathogens leads into inflammatory responses, including the clinical signs such as swelling.
During inflammation, cytokines are released from injured cells.  They recruit leukocytes to
reach the site of injury and remove the foreign pathogens. Proteins in the superfamily of
tumor necrosis factor (TNF) are one major class of these cytokines. They bind to the cell
surface proteins called TNF-receptors. The binding between TNF and receptors triggers the
intracellular signaling pathways, such as NF-κB pathway that is an essential regulator of cell
survival. Due to this critical role in immune responses, binding of TNF receptors with their
ligands is under intense study. However, most of these studies isolate the TNF receptors
from their usual biological surrounding. In living cells, TNF receptors are anchored on
surfaces of plasma membrane. The membrane confinement of TNF receptors causes
significant impacts on their functions. For instance, the TNF ligand oligomerization provides
high local binding avidity to receptors. Moreover, TNF receptors can aggregate into high-
order clusters upon ligand binding. Mechanisms underlying these phenomena are not fully
understood due to current experimental limitations. Computational modeling can reach
dimensions that are currently unapproachable in the laboratory. Thus, the objective of this
proposal is to decompose the complexity of binding kinetics between TNF soluble ligands
and cell-surface-bound receptors. We have developed different methods for calculating
binding affinities between protein and simulating protein binding kinetics on the
molecular and lower-resolution levels. Through the application of these methods to the
specific problem of TNF receptor binding on cell surfaces, and the establishment of ongoing
experimental collaborations, we are specifically interested in answering the following two
questions: how does oligomerization of TNF ligands modulate receptor binding, and
what are the functional roles of TNF receptor clustering in regulating ligand binding. In
order to study these two problems, we construct a new domain-based rigid-body model
and further develop a multiscale modeling framework to quantitatively calculate the
kinetics of binding between multivalent ligands and multiple receptors on cell surfaces.
Our long-term goal is to further elucidate the functional roles of TNF-mediated signaling in
regulating the inflammatory responses. In summary, this study will shed light on the basic
mechanisms of TNF receptor binding on cell surface.

## Key facts

- **NIH application ID:** 9983105
- **Project number:** 5R01GM122804-05
- **Recipient organization:** ALBERT EINSTEIN COLLEGE OF MEDICINE
- **Principal Investigator:** Yinghao Wu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $327,738
- **Award type:** 5
- **Project period:** 2017-09-20 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9983105

## Citation

> US National Institutes of Health, RePORTER application 9983105, Computational models for the signaling of tumor necrosis factor receptor on cell surfaces (5R01GM122804-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9983105. Licensed CC0.

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