肝细胞癌生物标志物基因的鉴定和治疗研究:利用分子对接和动力学模拟的计算机研究。

IF 3.9 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in bioinformatics Pub Date : 2025-09-19 eCollection Date: 2025-01-01 DOI:10.3389/fbinf.2025.1567748
Jishnu Ghosh, Abdullah M Alshahrani, Aritra Palodhi, Debarghya Bhattacharyya, Subhadip Das, Sunil Kanti Mondal, Abul Kalam, S Rehan Ahmad, Chittabrata Mal
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引用次数: 0

摘要

背景:肝细胞癌(HCC)是全球癌症相关死亡的第三大原因,发病率排名第五。它主要影响男性,在亚洲发病率很高。危险因素包括乙型和丙型肝炎、肝硬化、非酒精性脂肪性肝病(NAFLD)和饮酒。晚期诊断导致大约20%的低生存率,强调需要早期发现方法来提高生存率。本研究旨在通过对微阵列数据集的生物信息学分析,确定HCC的预后生物标志物,为潜在的治疗靶点提供见解。方法:我们分析了5个微阵列数据集,包括402例HCC样本和121例对照样本。为了确定相关的生物学途径,我们进行了差异基因表达、基因本体(gene Ontology, GO)和KEGG途径富集分析。我们确定了枢纽基因,并定量评估了靶向这些基因的转录因子和microrna。此外,利用分子对接和动态模拟(100 ns)来鉴定能够抑制差异表达枢纽基因活性的潜在候选药物。结果:我们的生物信息学方法确定了几个有希望的HCC生物标志物。其中,CDK1/CKS2被确定为一个关键的治疗靶点,在HCC发病机制中具有调节作用,表明其有进一步研究的潜力。通过虚拟筛选、ADMET分析、分子对接研究和动态模拟证实,地高辛(DB00390)具有良好的药物相似性和稳定性,已成为潜在的再用途候选药物。结论:本研究增强了我们对HCC生物学的理解,并为药物相互作用提供了新的见解。它提出了一些有希望的早期诊断、预后和治疗的生物标志物。进一步研究CDK1/CKS2作为治疗靶点以及所鉴定的生物标志物的作用可能有助于改善HCC的诊断和治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification and therapeutic investigation of biomarker genes underpinning hepatocellular carcinoma: an in silico study utilising molecular docking and dynamics simulation.

Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality globally, and ranks fifth in terms of incidence. It primarily affects males and has a high prevalence in Asia. Risk factors include hepatitis B and C, liver cirrhosis, nonalcoholic fatty liver disease (NAFLD), and alcohol consumption. Late-stage diagnosis results in a poor survival rate of approximately 20%, underscoring the need for early detection methods to improve the survival rates. This study aimed to identify prognostic biomarkers for HCC through bioinformatic analysis of microarray datasets, providing insights into potential therapeutic targets.

Methods: We analyzed five microarray datasets, comprising 402 HCC samples and 121 control samples. To identify relevant biological pathways, we conducted differential gene expression, Gene Ontology (GO), and KEGG pathway enrichment analyses. We identified hub genes and quantitatively assessed transcription factors and microRNAs targeting these genes. Additionally, molecular docking and dynamic simulations (100 ns) were used to identify potential drug candidates capable of inhibiting the activity of differentially expressed hub genes.

Results: Our bioinformatic approach identified several promising HCC biomarkers. Among these, CDK1/CKS2 was identified as a key therapeutic target, with a regulatory role in HCC pathogenesis, suggesting its potential for further investigation. Digoxin (DB00390) has been highlighted as a potential repurposed drug candidate because of its favorable drug-likeness and stability, as confirmed by virtual screening, ADMET analysis, molecular docking study and dynamic simulations.

Conclusion: This study enhances our understanding of HCC biology and offers new insights into drug interactions. It presents several promising biomarkers for the early diagnosis, prognosis, and therapy. Further investigation into CDK1/CKS2 as a therapeutic target and the role of the identified biomarkers could contribute to improved diagnostic and therapeutic strategies for HCC.

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