Back

Structure of the integrin receptor M2 headpiece in complex with a function-modulating nanobody

Jensen, R. K.; Pedersen, H.; Lorentzen, J.; Laursen, N. S.; Vorup-Jensen, T.; Andersen, G. R.

2021-07-08 immunology
10.1101/2021.07.07.451531 bioRxiv
Show abstract

The integrin receptor M{beta}2 mediates phagocytosis of complement-opsonized objects, adhesion to the extracellular matrix and trans-endothelial migration of leukocytes. Here we present the first atomic structure of the human M{beta}2 headpiece fragment in complex with the nanobody hCD11bNb1 determined at a resolution of 3.2 [A]. The receptor headpiece adopts the closed conformation expected to have low ligand affinity. The crystal structure advocates that in the R77H M variant associated with systemic lupus erythematosus, the modified allosteric coupling between ligand coupling and integrin outside-inside signalling is due to subtle conformational effects transmitted over 40 [A]. The nanobody binds to the I domain of the M subunit in an Mg2+ independent manner with low nanomolar affinity. Biochemical and biophysical experiments with purified proteins argue that the nanobody acts as a competitive inhibitor through steric hindrance exerted on the thioester domain of iC3b attempting to bind the M subunit. Surprisingly, the nanobody stimulates the interaction of cell-bound M{beta}2 with iC3b suggesting that it represents a novel high-affinity proteinaceous M{beta}2 specific agonist. We propose a model based on the conformational spectrum of the receptor to reconcile these conflicting observations regarding the functional consequences of hCD11bNb1 binding to M{beta}2. Furthermore, our data suggest that the iC3b-M{beta}2 complex may be more dynamic than predicted from the crystal structure of the core complex.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.