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Open Access Research article

Are different stoichiometries feasible for complexes between lymphotoxin-alpha and tumor necrosis factor receptor 1?

Nahren Manuel Mascarenhas and Johannes Kästner*

Author affiliations

Computational Biochemistry Group, Institute of Theoretical Chemistry, Pfaffenwaldring 55, University of Stuttgart, Stuttgart, 70569, Germany

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Citation and License

BMC Structural Biology 2012, 12:8  doi:10.1186/1472-6807-12-8

Published: 8 May 2012

Abstract

Background

Tumor necrosis factors, TNF and lymphotoxin-α (LT), are cytokines that bind to two receptors, TNFR1 and TNFR2 (TNF-receptor 1 and 2) to trigger their signaling cascades. The exact mechanism of ligand-induced receptor activation is still unclear. It is generally assumed that three receptors bind to the homotrimeric ligand to trigger a signaling event. Recent evidence, though, has raised doubts if the ligand:receptor stoichiometry should indeed be 3:3 for ligand-induced cellular response. We used molecular dynamics simulations, elastic network models, as well as MM/PBSA to analyze this question.

Results

Applying MM/PBSA methodology to different stoichiometric complexes of human LT-(TNFR1)n=1,2,3 the free energy of binding in these complexes has been estimated by single-trajectory and separate-trajectory methods. Simulation studies rationalized the favorable binding energy in the LT-(TNFR1)1 complex, as evaluated from single-trajectory analysis to be an outcome of the interaction of cysteine-rich domain 4 (CRD4) and the ligand. Elastic network models (ENMs) help to associate the difference in the global fluctuation of the receptors in these complexes. Functionally relevant transformation associated with these complexes reveal the difference in the dynamics of the receptor when free and in complex with LT.

Conclusions

MM/PBSA predicts complexes with a ligand-receptor molar ratio of 3:1 and 3:2 to be energetically favorable. The high affinity associated with LT-(TNFR1)1 is due to the interaction between the CRD4 domain with LT. The global dynamics ascertained from ENMs have highlighted the differential dynamics of the receptor in different states.

Keywords:
Elastic network model (ENM); Lymphotoxin; MM/PBSA; Receptor; Tumor necrosis factor (TNF)