Formation of raft-like assemblies within clusters of influenza hemagglutinin observed by MD simulations

Daniel L Parton1, Alex Tek, Marc Baaden

  • 1Department of Biochemistry, University of Oxford, Oxford, United Kingdom.

Insights

Influenza hemagglutinin (HA) protein clusters drive raft-like lipid accumulation in cell membranes. This steric crowding mechanism explains how proteins associate with lipid rafts, crucial for viral assembly and cellular processes.

Area of Science:

  • Biophysics
  • Molecular Biology
  • Membrane Protein Dynamics

Background:

  • Influenza hemagglutinin (HA) associates with lipid rafts during virus assembly.
  • Lipid rafts are membrane domains enriched in saturated lipids, sphingolipids, and cholesterol.
  • Transmembrane proteins typically partition into unsaturated lipid domains in model membranes, creating a disparity.

Purpose of the Study:

  • To investigate the effect of high local protein concentration on membrane protein partitioning into lipid rafts.
  • To understand the mechanism behind hemagglutinin's association with raft-type lipids.

Main Methods:

  • Coarse-grained molecular dynamics (CG MD) simulations of hemagglutinin (HA) clusters in domain-forming bilayers.
  • Analysis of lipid and protein distribution and diffusion within simulated membrane environments.

Main Results:

  • Simulations showed an increase in raft-type lipids (saturated phospholipids, cholesterol) within HA protein clusters.
  • Lateral diffusion of unsaturated lipids was significantly reduced within protein clusters, while saturated lipids were less affected.
  • Steric crowding by slow-diffusing proteins appears to increase the chemical potential for unsaturated lipids within the cluster.

Conclusions:

  • Local aggregation of HA can drive the association of the protein with raft-type lipids.
  • This mechanism may explain how transmembrane proteins target lipid rafts in the plasma membrane.
  • Such targeting is functionally important for various cellular processes, including viral assembly.

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