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Multi-scale simulations of the T cell receptor reveal its lipid interactions, dynamics and the arrangement of its cytoplasmic region.

ABSTRACT: The T cell receptor (TCR-CD3) initiates T cell activation by binding to peptides of Major Histocompatibility Complexes (pMHC). The TCR-CD3 topology is well understood but the arrangement and dynamics of its cytoplasmic tails remains unknown, limiting our grasp of the signalling mechanism. Here, we use molecular dynamics simulations and modelling to investigate the entire TCR-CD3 embedded in a model membrane. Our study demonstrates conformational changes in the extracellular and transmembrane domains, and the arrangement of the TCR-CD3 cytoplasmic tails. The cytoplasmic tails formed highly interlaced structures while some tyrosines within the immunoreceptor tyrosine-based activation motifs (ITAMs) penetrated the hydrophobic core of the membrane. Interactions between the cytoplasmic tails and phosphatidylinositol phosphate lipids in the inner membrane leaflet led to the formation of a distinct anionic lipid fingerprint around the TCR-CD3. These results increase our understanding of the TCR-CD3 dynamics and the importance of membrane lipids in regulating T cell activation.

SUBMITTER: Prakaash D

PROVIDER: S-EPMC8321403 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Multi-scale simulations of the T cell receptor reveal its lipid interactions, dynamics and the arrangement of its cytoplasmic region.

Prakaash Dheeraj D Cook Graham P GP Acuto Oreste O Kalli Antreas C AC

PLoS computational biology 20210719 7

The T cell receptor (TCR-CD3) initiates T cell activation by binding to peptides of Major Histocompatibility Complexes (pMHC). The TCR-CD3 topology is well understood but the arrangement and dynamics of its cytoplasmic tails remains unknown, limiting our grasp of the signalling mechanism. Here, we use molecular dynamics simulations and modelling to investigate the entire TCR-CD3 embedded in a model membrane. Our study demonstrates conformational changes in the extracellular and transmembrane dom ...[more]

PMID: 34280187

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Project description:The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

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Multi-scale simulations of the T cell receptor reveal its lipid interactions, dynamics and the arrangement of its cytoplasmic region.

Publications

Multi-scale simulations of the T cell receptor reveal its lipid interactions, dynamics and the arrangement of its cytoplasmic region.

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