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The functional impacts of mutations that result in one or more amino acid insertions into a protein have been the focus of recent studies. However, generating these mutations in a wet lab setting is time and resource intensive, and even prohibitive. Computational methods seek to bridge this gap by generating mutant proteins in silico. In this work we explore the use of molecular dynamics (MD) to assess the effects of pairs of insertion mutations into the PDB structure file of HIV-1 Protease. We use our in-house compute pipeline to generate the exhaustive set of mutants with two insertion mutations, and identify 24 mutant structures which present as outliers based on four structural metrics as reported in our earlier work. We present an analysis of the MD runs to show the extent that they reveal the effects of the insertion mutations that earlier work was unable to elucidate.

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Using Molecular Dynamics to Assess How Two Insertion Mutations Affect Protein Structure

  • 会议论文

  • 发表日期：

    2025年

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  • Changrui Li,
  • Katie Christensen,
  • Sarah Coffland,
  • Filip Jagodzinski

摘要

The functional impacts of mutations that result in one or more amino acid insertions into a protein have been the focus of recent studies. However, generating these mutations in a wet lab setting is time and resource intensive, and even prohibitive. Computational methods seek to bridge this gap by generating mutant proteins in silico. In this work we explore the use of molecular dynamics (MD) to assess the effects of pairs of insertion mutations into the PDB structure file of HIV-1 Protease. We use our in-house compute pipeline to generate the exhaustive set of mutants with two insertion mutations, and identify 24 mutant structures which present as outliers based on four structural metrics as reported in our earlier work. We present an analysis of the MD runs to show the extent that they reveal the effects of the insertion mutations that earlier work was unable to elucidate.