In Silico-Based Structural Evaluation to Categorize the Pathogenicity of Mutations Identified in the RAD Class of

Aaliya Anwaar1, Ashok K Varma1,2, Reshita Baruah1

  • 1Advanced Centre for Treatment, Research and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India.

ACS Omega
|March 27, 2023
PubMed

Insights

Pathogenic mutations in RAD genes increase breast and ovarian cancer risk by altering DNA repair. Computational analysis revealed specific RAD51C and RAD51D mutations disrupt protein structure and function, highlighting their role in cancer development.

Area of Science:

  • Genomics
  • Molecular Biology
  • Cancer Research

Background:

  • RAD genes encode double-strand break repair proteins crucial for genomic integrity.
  • Mutations in RAD proteins are linked to increased susceptibility to breast and ovarian cancers.
  • Understanding the functional impact of these mutations is vital for cancer research.

Purpose of the Study:

  • To computationally analyze pathogenic mutations in RAD genes.
  • To evaluate the effects of these mutations on protein structure and function.
  • To understand the role of RAD gene mutations in breast and ovarian cancers.

Main Methods:

  • Identified 5122 missense mutations from cBioPortal, COSMIC, ClinVar, and gnomAD databases.
  • Utilized eight computational prediction servers to predict pathogenicity.
  • Characterized high-risk mutations based on conserved domains and structural stability.

Main Results:

  • 1165 pathogenic mutations were identified using at least five prediction servers.
  • Specific mutations (G125V, L138F in RAD51C; S207L, E233G in RAD51D) altered protein folding and structural behavior.
  • These alterations suggest faulty DNA repair mechanisms.

Conclusions:

  • Pathogenic RAD gene mutations, particularly in RAD51C and RAD51D, significantly impact protein structure and function.
  • These structural changes are implicated in the development of breast and ovarian cancers.
  • Further investigation into these mutations can inform cancer diagnostics and therapeutics.

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