Integrated Transcriptomics and Machine Learning Identify NALCN and KCNQ1 as Key Ion Channel Genes in Kidney Stone Pathogenesis and Potential Therapeutic Targets

Background Disrupted ion balance contributes to kidney stone (KS) formation via metabolic, inflammatory, and cellular injury pathways. This study aimed to identify critical ion channel-related genes (ICRGs) and their mechanisms in KS. Methods Using KS transcriptome datasets and ICRG information, key genes were identified through differential expression analysis and machine learning. Subsequent analyses included pathway enrichment, immune infiltration, regulatory network construction, and drug screening with molecular docking. Molecular dynamics (MD) simulations and in vitro experiments validated the findings. Results NALCN and KCNQ1 were identified as pivotal genes. They were enriched in KS-related pathways like oxidative phosphorylation. Immune infiltration linked them to specific immune cells. A regulatory network of TFs, miRNAs, and lncRNAs was constructed. Drug screening indicated strong binding of KCNQ1 with 3-acetyl-7-hydroxy-2H-chromen-2-one and of NALCN with hydralazine, which MD simulations confirmed as stable. Conclusion This study highlights NALCN and KCNQ1 as key ICRGs in KS, elucidating their potential mechanisms and therapeutic relevance, providing a basis for novel diagnostics and targeted treatments.