A systems-biology model of the tumor necrosis factor (TNF) interactions with TNF receptor 1 and 2

Author:

Prada Juan Pablo1,Wangorsch Gaby1,Kucka Kirstin2,Lang Isabell2,Dandekar Thomas13ORCID,Wajant Harald2

Affiliation:

1. Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg 97074, Germany

2. Division of Molecular Internal Medicine, Department of Internal Medicine II, University Hospital Würzburg, Würzburg 97080, Germany

3. Department of Structural and Computational Biology, European Molecular Biology Laboratory (EMBL), 69012 Heidelberg, Germany

Abstract

Abstract Motivation Clustering enables TNF receptors to stimulate intracellular signaling. The differential soluble ligand-induced clustering behavior of TNF receptor 1 (TNFR1) and TNFR2 was modeled. A structured, rule-based model implemented ligand-independent pre-ligand binding assembly domain (PLAD)-mediated homotypic low affinity interactions of unliganded and liganded TNF receptors. Results Soluble TNF initiates TNFR1 signaling but not TNFR2 signaling despite receptor binding unless it is secondarily oligomerized. We consider high affinity binding of TNF to signaling-incompetent pre-assembled dimeric TNFR1 and TNFR2 molecules and secondary clustering of liganded dimers to signaling competent ligand–receptor clusters. Published receptor numbers, affinities and measured different activities of clustered receptors validated model simulations for a large range of receptor and ligand concentrations. Different PLAD–PLAD affinities and different activities of receptor clusters explain the observed differences in the TNF receptor stimulating activities of soluble TNF. Availability and implementation All scripts and data are in manuscript and supplement at Bioinformatics online. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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