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NIH ProtIG Seminar:Data-Driven Modeling of the Mouse Macrophage Toll-like Receptor Signaling Pathway by Nathan Manes

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Air date: Thursday, April 11, 2024, 1:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 63 (12 Live, 51 On-demand)
Category: Special
Runtime: 00:49:07
Description: The Toll-like receptor (TLR) signaling pathway is important for the initiation of innate immune responses. To develop a strongly data-driven model of the mouse macrophage TLR4 pathway and to avoid oversimplification and overfitting, we used targeted mass spectrometry (LC-MS) to measure protein copies/cell, and we constrained interaction parameters using experimental data and molecular simulations. Most of the TLR4 pathway proteins were quantitated successfully, and they moderately correlated with RNA-seq transcript abundance values (r = 0.699), and this regression was used to estimate proteome-wide abundance values. Hundreds of PPI constants (k_on, k_off, k_trans, K_D, K_M, and k_cat) and other experimental data (e.g., quantitative phosphoproteomics datasets) were retrieved from the literature. AlphaFold-Multimer was used to predict protein complex structures, and subsequently TransComp was used to estimate 151 association rate constants. Simmune is being used to perform rule-based modeling by locally exploring pathway parameters. This work was supported by the Intramural Research Program of NIAID, NIH.

For more information go to https://nih.zoomgov.com/j/1615827662?pwd=OHBlbWErVzZqSTZVNTBGYkFWSGxLdz09
Author: Nathan P. Manes
 
CIT Live ID: 54650
Permanent link: https://videocast.nih.gov/watch=54650