Molecular dynamics simulations reveal R399Q mutation disrupts XRCC1-polβ interaction, potentially impairing DNA base

Nabajyoti Goswami1, Rupam Dutta2, Rene Barbie Browne3

  • 1Department of Bioengineering and Technology, Gauhati University, Jalukbari, Guwahati, Assam, India.

Insights

The R399Q mutation in XRCC1 impairs DNA repair by destabilizing its interaction with DNA polymerase β. This molecular dynamics study reveals altered protein binding, impacting genomic stability and cancer risk.

Area of Science:

  • Molecular Biology
  • Genetics
  • Biochemistry

Background:

  • Mutations in XRCC1 disrupt DNA base excision repair (BER), a critical pathway for maintaining genomic stability.
  • Defects in BER are linked to increased cancer risk and genomic instability.
  • The R399Q mutation is of particular interest due to its potential impact on XRCC1 function.

Purpose of the Study:

  • To investigate the structural and functional effects of the R399Q mutation on XRCC1 interactions with DNA ligase IIIα and DNA polymerase β.
  • To provide atomic-level insights into mutation-induced alterations in DNA repair protein dynamics.
  • To reconcile conflicting experimental data on XRCC1 mutation effects.

Main Methods:

  • Large-scale molecular dynamics (MD) simulations were employed to model XRCC1 interactions.
  • Analysis of protein-protein interactions and hydrogen bond rearrangements.
  • Free energy calculations to quantify binding affinity changes.

Main Results:

  • The R399Q mutation caused subtle rearrangements in XRCC1's interaction with DNA ligase IIIα.
  • Binding of XRCC1 to DNA polymerase β was significantly destabilized by the R399Q mutation.
  • Free energy calculations indicated a substantial reduction in binding affinity to DNA polymerase β.

Conclusions:

  • The R399Q mutation impairs XRCC1's role in DNA repair by disrupting its interaction with DNA polymerase β.
  • MD simulations offer dynamic, atomic-level insights into mutation effects, complementing biochemical studies.
  • These findings provide a computational framework for understanding mutation-driven DNA repair defects and their link to cancer risk.

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