Scholarlink

<p>Krüppel-like factor 14 (KLF14) is a key transcriptional regulator implicated in the pathogenesis of metabolic disorders, including diabetes and cardiovascular diseases. Despite its importance, the structural and post-transcriptional mechanisms governing <i>KLF14</i> dysfunction remain poorly understood. In this study, we present a systematic in-silico framework integrating evolutionary phylogenomic, structural modeling, and miRNA regulatory network analysis. We systematically analyzed the human <i>KLF14</i> gene family using data from NCBI and dbSNP, focusing on 377 non-synonymous single nucleotide polymorphisms (nsSNPs). By employing a consensus approach with algorithms such as SIFT, PolyPhen-2, and MutPred2, we identified 28 high-impact nsSNPS. Structural modeling via Phyre2 and I-TASSER revealed that variants like R217L (ΔΔG = + 3.2&#xa0;kcal/mol) and H277Q (RMSD = 2.8Å) significantly destabilize the conserved zinc-finger (ZF-C2H2) DNA-binding domain. Evolutionary analysis confirmed that KLF14 diverged through segmental duplications (Ka/Ks &lt; 1), maintaining high conservation in ZF domains. Furthermore, we screened the 5′-UTR using miRbase and psRNA-target, identifying 12 hsa-miRNAs (e.g., miR-27a-3p) linked to insulin signaling and atherosclerosis pathways via KEGG enrichment. The functional enrichment of the detected 12 hsa-miRNAs demonstrated their functional role in transcription regulation. Therefore, altered expression of the <i>KLF14</i> gene due to miRNA interactions in 5′-UTRs might influence the simultaneous expression patterns of interlinked genes related to metabolic conditions. This work provides the first comprehensive map linking, structural destabilization mutations and miRNA-mediated regulation of <i>KLF14</i>. These findings prioritize specific genetic targets for future experimental validation, offering a mechanistic basis for <i>KLF14</i>-associated metabolic dysregulation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrative in silico analysis of KLF14: prioritizing high-impact nsSNPs and miRNA-mediated regulation in metabolic disorders

  • 期刊论文

  • 发表日期：

    2026年2月17日

查看全文
  • Zainab Riaz,
  • Laiba Shafique,
  • Warda Safdar,
  • Shakeela Parveen,
  • Muhammad Hussain,
  • Muhammad Farhan Khan,
  • Muhammad Tayyab,
  • Mah-Noor Ayub

摘要

Krüppel-like factor 14 (KLF14) is a key transcriptional regulator implicated in the pathogenesis of metabolic disorders, including diabetes and cardiovascular diseases. Despite its importance, the structural and post-transcriptional mechanisms governing KLF14 dysfunction remain poorly understood. In this study, we present a systematic in-silico framework integrating evolutionary phylogenomic, structural modeling, and miRNA regulatory network analysis. We systematically analyzed the human KLF14 gene family using data from NCBI and dbSNP, focusing on 377 non-synonymous single nucleotide polymorphisms (nsSNPs). By employing a consensus approach with algorithms such as SIFT, PolyPhen-2, and MutPred2, we identified 28 high-impact nsSNPS. Structural modeling via Phyre2 and I-TASSER revealed that variants like R217L (ΔΔG = + 3.2 kcal/mol) and H277Q (RMSD = 2.8Å) significantly destabilize the conserved zinc-finger (ZF-C2H2) DNA-binding domain. Evolutionary analysis confirmed that KLF14 diverged through segmental duplications (Ka/Ks < 1), maintaining high conservation in ZF domains. Furthermore, we screened the 5′-UTR using miRbase and psRNA-target, identifying 12 hsa-miRNAs (e.g., miR-27a-3p) linked to insulin signaling and atherosclerosis pathways via KEGG enrichment. The functional enrichment of the detected 12 hsa-miRNAs demonstrated their functional role in transcription regulation. Therefore, altered expression of the KLF14 gene due to miRNA interactions in 5′-UTRs might influence the simultaneous expression patterns of interlinked genes related to metabolic conditions. This work provides the first comprehensive map linking, structural destabilization mutations and miRNA-mediated regulation of KLF14. These findings prioritize specific genetic targets for future experimental validation, offering a mechanistic basis for KLF14-associated metabolic dysregulation.