Pathogenic KRAS variants disrupt structure and dynamics: Insights from integrated computational analyses

Saqib Ishaq1,2,3, Aizaz Ali4, Obaid Habib1

  • 1Guangdong Provincial Key Laboratory of System Biology and Synthetics Biology for Urogenital Tumors, School of Basic Medicine, Shenzhen University Medical School, Shenzhen University (SZU), Shenzhen, Guangdong, China.

Plos One
|February 11, 2026
PubMed
Abstract

Insights

Computational analysis identified four detrimental KRAS gene variants (L79P, A130P, G138E, F141L) that destabilize protein structure, potentially driving oncogenic activation in cancers like colorectal and lung cancer.

Area of Science:

  • Oncogenomics
  • Computational Biology
  • Structural Biology

Background:

  • KRAS is a frequently mutated oncogene in pancreatic, colorectal, and lung cancers.
  • Mechanisms by which KRAS variants alter function are poorly understood.
  • This study focuses on identifying detrimental non-synonymous single nucleotide polymorphisms (nsSNPs) in KRAS.

Purpose of the Study:

  • Identify and characterize pathogenic KRAS nsSNPs.
  • Elucidate atomistic effects of these variants on KRAS structure, stability, and oncogenic potential.

Main Methods:

  • Screened 173 nsSNPs using an integrated computational workflow.
  • Employed pathogenicity prediction, evolutionary conservation, structural modeling, molecular docking, and molecular dynamics simulations.
  • Assessed post-translational modifications and protein-protein interactions.

Main Results:

  • Identified four high-impact deleterious variants: L79P, A130P, G138E, and F141L.
  • Simulations showed these variants perturb conformational stability, residue flexibility, and binding energetics.
  • Variants are linked to colorectal, pancreatic, and lung cancers, indicating clinical relevance.

Conclusions:

  • Provides mechanistic insights into KRAS variations driving oncogenic activation.
  • Identified variants are high-priority targets for experimental validation.
  • Highlights the utility of computational methods in cancer biology research.

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