Role of Structural Fluctuations in Allosteric Stimulation of Paramyxovirus Hemagglutinin-Neuraminidase

Structure. 2019 Oct 1;27(10):1601-1611.e2. doi: 10.1016/j.str.2019.07.005. Epub 2019 Aug 8.

Abstract

Complexity in understanding allosteric stimulation of the hemagglutinin-neuraminidase (HN) protein of paramyxoviruses by host sialic acids (SIAs) stems from (1) unavailability of structure in its SIA-bound state and (2) the observation that this process is temperature sensitive. To consider simultaneously SIA's effect on structure and thermal fluctuations, we use molecular dynamics and simulate the dimeric form of the Newcastle disease virus HN. We find that SIA induces only minor structural changes in individual monomers, yet it reorients dimer interface by 10°. Interface reorientation is accompanied by constriction of SIA binding groove and enhanced fluctuations of interfacial residues that disrupt hydrophobic interactions and favor creation of new salt bridges. Supervised machine learning analysis of non-equilibrium data reveals that the allosteric signal is not formed from a directed sequence of these events. Altogether, we propose a detailed model of the initial events of allosteric stimulation, consistent with experiments on engineered mutations.

Keywords: Newcastle disease virus; allosteric signaling; conformational ensembles; dynamic allostery; machine learning analysis; molecular dynamics; paramyxovirus entry; protein-ligand interactions; protein-protein interactions; thermal fluctuations.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Allosteric Regulation
  • Binding Sites
  • Crystallography, X-Ray
  • HN Protein / chemistry*
  • HN Protein / drug effects
  • HN Protein / metabolism*
  • Hydrophobic and Hydrophilic Interactions
  • Models, Molecular
  • Molecular Dynamics Simulation
  • Newcastle disease virus / chemistry
  • Newcastle disease virus / metabolism*
  • Protein Binding
  • Protein Conformation / drug effects
  • Protein Multimerization
  • Sialic Acids / pharmacology*
  • Supervised Machine Learning

Substances

  • HN Protein
  • Sialic Acids