Dataset Information

The Human TSHβ Subunit Proteins and Their Binding Sites on the TSH Receptor Using Molecular Dynamics Simulation.

ABSTRACT: To gain further insight into the binding of the normal and variant human TSHβ subunits (TSHβ and TSHβv), we modeled the 2 monomeric proteins and studied their interaction with the TSH receptor ectodomain (TSHR-ECD) using molecular dynamics simulation Furthermore, analyzed their bioactivity in vitro using recombinant proteins to confirm that such binding was physiologically relevant. Examining the interaction of TSHβ and TSHβv with the TSHR-ECD model using molecular dynamic simulation revealed strong binding of these proteins to the receptor ECD. The specificity of TSHβ and TSHβv binding to the TSHR-ECD was examined by analyzing the hydrogen-bonding residues of these subunits to the FSH receptor ECD, indicating the inability of these molecules to bind to the FSH receptors. Furthermore, the modelling suggests that TSHβ and TSHβv proteins clasped the concave surface of the leucine rich region of the TSHR ECD in a similar way to the native TSH using dynamic hydrogen bonding. These mutually exclusive stable interactions between the subunits and ECD residues included some high-affinity contact sites corresponding to binding models of native TSH. Furthermore, we cloned TSHβ and TSHβv proteins using the entire coding ORF and purified the flag-tagged proteins. The expressed TSHβ subunit proteins retained bioactivity both in a coculture system as well as with immune-purified proteins. In summary, we showed that such interactions can result in a functional outcome and may exert physiological or pathophysiological effects in immune cells.

SUBMITTER: Mezei M

PROVIDER: S-EPMC7447003 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Protein dynamics play an important role in small molecule binding and can pose a significant challenge in the identification of potential binding sites. Cryptic binding sites have been defined as sites which require significant rearrangement of the protein structure to become physically accessible to a ligand. Mixed-solvent MD (MixMD) is a computational protocol which maps the surface of the protein using molecular dynamics (MD) of the unbound protein solvated in a 5% box of probe molecules with explicit water. This method has successfully identified known active and allosteric sites which did not require reorganization. In this study, we apply the MixMD protocol to identify known cryptic sites of 12 proteins characterized by a wide range of conformational changes. Of these 12 proteins, three require reorganization of side chains, five require loop movements, and four require movement of more significant structures such as whole helices. In five cases, we find that standard MixMD simulations are able to map the cryptic binding sites with at least one probe type. In two cases (guanylate kinase and TIE-2), accelerated MD, which increases sampling of torsional angles, was necessary to achieve mapping of portions of the cryptic binding site missed by standard MixMD. For more complex systems where movement of a helix or domain is necessary, MixMD was unable to map the binding site even with accelerated dynamics, possibly due to the limited timescale (100 ns for individual simulations). In general, similar conformational dynamics are observed in water-only simulations and those with probe molecules. This could imply that the probes are not driving opening events but rather take advantage of mapping sites that spontaneously open as part of their inherent conformational behavior. Finally, we show that docking to an ensemble of conformations from the standard MixMD simulations performs better than docking the apo crystal structure in nine cases and even better than half of the bound crystal structures. Poorer performance was seen in docking to ensembles of conformations from the accelerated MixMD simulations.

Dataset Information

The Human TSHβ Subunit Proteins and Their Binding Sites on the TSH Receptor Using Molecular Dynamics Simulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets