Network pharmacology and AI in cancer research uncovering biomarkers and therapeutic targets for RALGDS mutations.

ABSTRACT: The lack of target therapies is accountable for the higher mortality of various types of cancer. To address this issue, we selected a target mutated Kirsten rat sarcoma virus oncogene homologue, which plays a significant role in various cancers. Our study aims to identify selective biomarkers and develop diagnostic and therapeutic strategies for KRAS-associated genes using artificial intelligence. Initially, Genomic data, cancer epidemiology, proteomics network interactions, and omics enrichment were analyzed. Structured E-pharmacophore model aided in capturing the binding cavity using eraser algorithms and fabricating a new selective lead compound for the KRSA. The selective molecule was abridged inside the binding cavity and stability was validated through 100 ns molecular dynamics simul

SUBMITTER: Zaidh SM 

PROVIDER: S-EPMC11954960 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature