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Analyzing machupo virus-receptor binding by molecular dynamics simulations.

Austin G Meyer1, Sara L Sawyer2, Andrew D Ellington2

  • 1Department of Integrative Biology, Institute for Cellular and Molecular Biology, and Center for Computational Biology and Bioinformatics, The University of Texas at Austin , Austin, TX , USA ; Department of Molecular Biosciences, Institute for Cellular and Molecular Biology, The University of Texas at Austin , Austin, TX , USA ; School of Medicine, Texas Tech University Health Sciences Center , Lubbock, TX , USA.

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Summary

Predicting how mutations affect protein-protein interactions is challenging. This study uses steered molecular dynamics (SMD) to analyze host-virus binding affinity, offering new insights into viral infection mechanisms.

Keywords:
ArenavirusComputational mutagenesisFree energy perturbationMachupoMolecular dynamicsProtein–protein interaction

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Accurately predicting mutational effects on protein-protein interaction (PPI) affinity is crucial for biological applications.
  • Existing computational methods often struggle with complex mutations, non-alanine substitutions, and flexible protein regions.
  • Understanding host-virus PPIs is vital for developing antiviral strategies.

Purpose of the Study:

  • To apply steered molecular dynamics (SMD) to investigate affinity differences in a host-virus PPI interface.
  • To evaluate the utility of SMD in predicting the biophysical impact of mutations on binding affinity.
  • To gain novel insights into the machupo virus (MACV) spike glycoprotein (GP1) and human transferrin receptor (hTfR1) interaction.

Main Methods:

  • Utilized steered molecular dynamics (SMD) to computationally separate the MACV GP1 from hTfR1.
  • Approximated binding affinity using maximum force and the area under the force-distance curve from SMD simulations.
  • Correlated SMD-derived affinity measures with relative free energy differences from free energy perturbation (FEP) calculations.

Main Results:

  • SMD successfully differentiated between wild-type and mutant protein complexes without prior system knowledge.
  • The simple SMD approach showed good correlation with more rigorous FEP calculations for relative binding affinities.
  • Simulations suggested that one of the two major hydrogen-bonding networks in the GP1/hTfR1 interface might not be critical for tight binding.
  • Identified a potential evolutionary suppressor site on hTfR1 linked to a critical viral infection site.

Conclusions:

  • Steered molecular dynamics (SMD) provides a computationally efficient framework for gaining biophysical insights into PPIs and mutational effects.
  • This method can differentiate wild-type and mutant complexes and correlates well with established free energy methods.
  • The findings offer new perspectives on the GP1/hTfR1 interaction, including the role of specific binding networks and evolutionary adaptations.
  • The presented approach allows for the analysis of individual and combined effects of multiple mutations on PPIs.