Computational Biology and Chemistry最新文献_第7页

Phytochemicals from Achillea millefolium target NAFLD and NASH: A network pharmacology integrated bioinformatics and molecular docking investigation 千叶阿喀琉叶植物化学物质靶向NAFLD和NASH：生物信息学与分子对接研究的网络药理学

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-11 DOI: 10.1016/j.compbiolchem.2025.108839

Megh Pravin Vithalkar, B. Anvitha, Vishwani Naik, Sandra K.S., Beere Vishnusai, Yogendra Nayak

Background

Non-alcoholic fatty liver disease (NAFLD) and its progressive stage, non-alcoholic steatohepatitis (NASH), are among the leading causes of chronic liver disease with limited treatment options. Dysregulation of PI3K/AKT, EGFR, and TNF-α signaling pathways plays a central role in their progression. Traditional medicinal plants, such as Achillea millefolium, are abundant in phytochemicals with potential therapeutic effects.

Objectives

This study aimed to identify and evaluate bioactive compounds from A. millefolium with potential activity against NAFLD/NASH using network pharmacology, bioinformatics, molecular docking, and ADME profiling, while exploring their multi-target synergy through network pharmacology.

Methods

Phytochemicals were collected from literature and curated databases. Potential targets were predicted via SwissTarget, PharmMapper, and SuperPred, while NAFLD/NASH-related genes were obtained from GeneCards. Common targets were identified through Venn analysis and integrated into protein-protein interaction and pathway networks in Cytoscape. Functional enrichment was conducted using DAVID. Key hub-targets (AKT1, PIK3CA, EGFR, TNF-α) were validated by molecular docking and MM-GBSA binding energy calculations. Pharmacokinetic profiles were assessed using ADMETLab 3.0, and recent nano-formulation studies were reviewed to support translational potential. Transcriptomic data further validated hub-target involvement.

Results

Network analysis highlighted multiple hub-targets and pathways. Luteolin glycosides, rutin, and apigenin showed strong binding with PI3K/AKT1 and EGFR, while vicenin-2 demonstrated affinity for TNF-α. However, glycosylated flavonoids displayed low predicted absorption and high polarity, suggesting poor bioavailability. Nanoformulations such as polymeric nanoparticles and lipid nanocapsules may improve delivery.

Conclusion

This integrative study underscores the therapeutic promise of A. millefolium, particularly luteolin glycosides, apigenin, rutin, and vicenin-2, in modulating PI3K/AKT-driven NAFLD/NASH pathology.

背景：非酒精性脂肪性肝病（NAFLD）及其进展阶段非酒精性脂肪性肝炎（NASH）是慢性肝病的主要原因之一，治疗方案有限。PI3K/AKT、EGFR和TNF-α信号通路的失调在其进展中起核心作用。传统药用植物，如千叶阿喀琉叶，含有丰富的植物化学物质，具有潜在的治疗作用。目的利用网络药理学、生物信息学、分子对接、ADME分析等方法，鉴定和评价千叶草中具有抗NAFLD/NASH活性的生物活性化合物，并通过网络药理学探讨其多靶点协同作用。方法从文献和整理的数据库中收集植物化学成分。通过SwissTarget、PharmMapper和SuperPred预测潜在靶点，而从GeneCards获得NAFLD/ nash相关基因。通过维恩分析确定了共同的靶点，并将其整合到Cytoscape中的蛋白质相互作用和途径网络中。用DAVID进行功能富集。通过分子对接和MM-GBSA结合能计算验证关键枢纽靶点（AKT1、PIK3CA、EGFR、TNF-α）。使用ADMETLab 3.0评估药代动力学特征，并回顾了最近的纳米制剂研究，以支持转化潜力。转录组学数据进一步证实了中心靶点参与。结果网络分析突出了多个中心靶点和通路。木犀草素苷、芦丁和芹菜素与PI3K/AKT1和EGFR结合较强，而vicenin-2与TNF-α有亲和力。然而，糖基化黄酮类化合物表现出低预测吸收和高极性，表明其生物利用度较差。纳米制剂如聚合纳米粒子和脂质纳米胶囊可以改善递送。结论：这项综合研究强调了千叶木犀草，特别是木犀草素苷、芹菜素、芦丁和vicenin-2在调节PI3K/ akt驱动的NAFLD/NASH病理方面的治疗前景。

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引用次数: 0

AI-powered literature mining reveals the therapeutic significance of GLP-1 receptor: Simulation of natural agonist candidates based on molecular dynamics 人工智能驱动的文献挖掘揭示了GLP-1受体的治疗意义：基于分子动力学的天然激动剂候选物模拟

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-11 DOI: 10.1016/j.compbiolchem.2025.108828

Rabia Kalkan Cakmak , Nail Besli , Nilufer Ercin , Ulkan Celik

Glucagon-like peptide-1 (GLP-1), a pivotal incretin hormone modulating glycemic homeostasis, has emerged as a clinically validated target for the treatment of type 2 diabetes and obesity. In this study, we present a comprehensive AI-integrated drug discovery pipeline that leverages BioBERT-based biomedical text mining to delineate the therapeutic landscape of GLP-1 receptor agonism systematically. Subsequent high-throughput virtual screening (HTVS) of a curated natural product library identified structurally diverse candidate ligands. A machine-learning-guided ADMET profiling algorithm was employed to prioritize compounds with optimal pharmacokinetic and safety characteristics. Top-ranked molecules were subjected to extensive molecular dynamics (MD) simulations using the GROMACS platform, enabling quantitative evaluation of structural stability, dynamic behavior, and receptor-ligand interaction persistence. Molecular docking analyses demonstrated robust binding affinities (ΔG: −11.3 to −8.7 kcal/mol), while MM-PBSA free energy estimations (ΔG<−30 kcal/mol) corroborated the thermodynamic favorability of binding. Among the screened entities, five lead candidates—CNP0244222.1, CNP0186692.11, CNP0361941.2, CNP0547477.1, and CNP0258197.2—consistently exhibited superior ADMET scores (>0.67), stable interaction trajectories, and enthalpically favorable profiles. This integrative, AI-augmented computational framework demonstrates substantial potential to accelerate the rational design and preclinical advancement of GLP-1-targeted therapeutics.

胰高血糖素样肽-1 （GLP-1）是调节血糖稳态的关键肠促胰岛素激素，已成为治疗2型糖尿病和肥胖的临床验证靶点。在这项研究中，我们提出了一个全面的人工智能集成药物发现管道，利用基于biobert的生物医学文本挖掘来系统地描绘GLP-1受体激动作用的治疗前景。随后的高通量虚拟筛选（HTVS）的策划天然产物库确定了结构多样化的候选配体。采用机器学习引导的ADMET分析算法对具有最佳药代动力学和安全性特性的化合物进行优先排序。使用GROMACS平台对排名前几位的分子进行了广泛的分子动力学（MD）模拟，从而能够定量评估结构稳定性、动态行为和受体-配体相互作用的持久性。分子对接分析显示了强大的结合亲和力（ΔG:−11.3至−8.7 kcal/mol），而MM-PBSA自由能估计（ΔG<−30 kcal/mol）证实了结合的热力学优势。在筛选的实体中，五个主要候选实体- cnp0244222.1, CNP0186692.11, CNP0361941.2, CNP0547477.1和cnp0258197.2 -始终表现出优越的ADMET分数（>0.67），稳定的相互作用轨迹和有利的热谱。这种整合的、人工智能增强的计算框架显示出巨大的潜力，可以加速glp -1靶向治疗的合理设计和临床前进展。

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引用次数: 0

Bioinformatic assessment of allergenicity, virulence, and secondary metabolites in Aspergillus species for industrial applications 工业应用中曲霉的致敏性、毒力和次生代谢物的生物信息学评估。

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-11 DOI: 10.1016/j.compbiolchem.2025.108841

Berenice Talamantes-Becerra , Mya Myintzu Hlaing , Natalie A. Twine , Laurence Wilson , Denis C. Bauer , Netsanet Shiferaw Terefe

Aspergillus species are widely used in industrial applications, including food and feed production, due to their ability to enhance nutritional content through fermentation. However, certain strains may pose safety concerns because of their potential to produce allergenic or toxic secondary metabolites. In this study, we developed a bioinformatics pipeline to assess the safety of Aspergillus strains by evaluating allergenicity, virulence factors and metabolite biosynthesis. As part of this pipeline, we implemented HitRefiner, a custom tool designed to improve protein detection by identifying multiple non-overlapping hits within long genomic contigs, enhancing the resolution and reliability of in-silico predictions. A total of 10 Aspergillus isolates of various species including A. niger, A. oryzae and A. sojae were analysed to identify proteins associated with virulence, allergenicity and production of secondary metabolites. Results showed two A. sojae strains that may be potential candidates for further characterisation and potential use for food and feed applications. This workflow provides a structured framework for cleaning assemblies, removing contaminant sequences, and identifying proteins associated with allergenic or virulence potential. The pipeline offers a practical in-silico pre-screening method to prioritise fungal isolates for safe use in industrial fermentation.

曲霉种类被广泛应用于工业应用，包括食品和饲料生产，因为它们能够通过发酵提高营养成分。然而，某些菌株可能会引起安全问题，因为它们可能产生致敏或有毒的次级代谢物。在这项研究中，我们建立了一个生物信息学管道，通过评估曲霉菌株的致敏性、毒力因子和代谢物的生物合成来评估其安全性。作为该流程的一部分，我们实施了HitRefiner，这是一种定制工具，旨在通过识别长基因组组群中的多个非重叠命中来改进蛋白质检测，提高了计算机预测的分辨率和可靠性。对包括黑曲霉、米曲霉和大豆曲霉在内的10个不同种类的曲霉分离株进行了分析，以确定与毒力、致敏性和次生代谢物产生相关的蛋白质。结果显示，这两株大豆豆豉菌株可能有进一步鉴定和潜在的食品和饲料应用潜力。该工作流程为清洁组件、去除污染物序列和识别与致敏性或毒性潜在相关的蛋白质提供了结构化框架。该管道提供了一种实用的计算机预筛选方法，以优先选择真菌分离物，安全用于工业发酵。

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引用次数: 0

MethylMSI: Prediction of microsatellite instability based on DNA methylation profile and SVM model 甲基msi：基于DNA甲基化谱和SVM模型的微卫星不稳定性预测。

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-10 DOI: 10.1016/j.compbiolchem.2025.108832

Chenzhi Yan , Qijie He , Runtian Yao , Jiawen Wu , Xing-Ding Zhang , Lin Qi , Mi Ni Huang

Microsatellite instability (MSI) has gained increasing attention as a promising biomarker for cancer immunotherapy in diverse cancer types. As a result of DNA mismatch repair (MMR) deficiency, MSI tumors show a hypermutator phenotype. Based on this feature, many computational methods have been developed to predict MSI with DNA sequencing data or mRNA expression data. Using the methylation data from The Cancer Genome Atlas (TCGA) program, we developed MethylMSI, a support vector machine (SVM) model based tool for MSI classification in three cancer cohorts (colorectal, stomach and endometrial cancers). We demonstrated that MethylMSI has high MSI prediction accuracy in all three cohorts. Analysis of underlying features of the SVM model showed that hypermethylation of MLH1 is an important indicator for MSI in colorectal and endometrial cancers; while in stomach cancer, other MMR deficiency might be more important for MSI formation. We concluded that SVM had the potential to be the best model for predicting MSI status from DNA methylation data. In addition, an easy handling software is now freely available at https://github.com/Huanglab-ai/MethylMSI.

微卫星不稳定性（Microsatellite instability， MSI）作为一种有前景的肿瘤免疫治疗生物标志物，越来越受到人们的关注。由于DNA错配修复（MMR）缺陷，MSI肿瘤表现出超突变表型。基于这一特征，人们开发了许多计算方法，利用DNA测序数据或mRNA表达数据来预测MSI。利用来自癌症基因组图谱（TCGA）项目的甲基化数据，我们开发了MethylMSI，一个基于支持向量机（SVM）模型的工具，用于三个癌症队列（结直肠癌、胃癌和子宫内膜癌）的MSI分类。我们证明甲基MSI在所有三个队列中都具有很高的MSI预测准确性。对SVM模型的基础特征分析表明，MLH1的高甲基化是结直肠癌和子宫内膜癌MSI的重要指标；而在胃癌中，其他MMR缺乏可能对MSI的形成更为重要。我们得出结论，支持向量机有潜力成为从DNA甲基化数据预测MSI状态的最佳模型。此外，一个易于处理的软件现在可以在https://github.com/Huanglab-ai/MethylMSI上免费获得。

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引用次数: 0

Integrated transcriptomics and miRNA-mRNA network analysis reveals Kisspeptin-10 mediated regulation of EMT and apoptosis in glioblastoma 整合转录组学和miRNA-mRNA网络分析显示Kisspeptin-10介导胶质母细胞瘤EMT和细胞凋亡的调控

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-10 DOI: 10.1016/j.compbiolchem.2025.108826

Hetvi Shah , Adikrishna Murali Mohan , Rushabh Shah , Drashti Mehta , A.V. Ramachandran , Parth Pandya

Glioblastoma multiforme (GB) is the most aggressive and lethal primary brain tumor, with limited biomarkers for diagnosis and therapeutic targeting. This study aimed to investigate the regulatory effects of Kisspeptin-10 on epithelial–mesenchymal transition (EMT) and apoptosis in GB by integrating transcriptomic profiling, network analysis, and in-vitro validation. Kisspeptin-10, a metastasis-suppressor peptide known to modulate EMT and apoptotic pathways in several cancers, has not been previously explored in GB. Differentially expressed genes (DEGs) were identified from publicly available GEO datasets using limma, followed by STRING-based protein–protein interaction (PPI) analysis, cytoHubba-based hub gene ranking, and construction of miRNA–mRNA regulatory networks. A total of 1401 DEGs were identified, including 859 upregulated and 542 downregulated genes, enriched in pathways associated with EMT regulation, cell-cycle progression, extracellular matrix remodeling, and apoptosis. Hub genes such as CDK1, CDC20, JUN, and FABP5 were identified, while miR-200, miR-345, and miR-577 emerged as key regulatory miRNAs linked to EMT and apoptotic signaling. In-vitro validation further supported the modulatory effects of Kisspeptin-10 on EMT and apoptosis markers in GB cells. These findings highlight the diagnostic and therapeutic relevance of Kisspeptin-10–associated molecular regulation in GB. This is the first study to integrate transcriptomics, miRNA–mRNA network analysis, and experimental validation to elucidate Kisspeptin-10–mediated modulation of GB progression.

多形性胶质母细胞瘤（GB）是最具侵袭性和致死性的原发性脑肿瘤，诊断和治疗的生物标志物有限。本研究旨在通过转录组学分析、网络分析和体外验证，探讨Kisspeptin-10对GB上皮-间质转化（epithelial-mesenchymal transition， EMT）和凋亡的调控作用。Kisspeptin-10是一种转移抑制肽，已知可调节几种癌症的EMT和凋亡途径，但此前尚未在GB中进行研究。使用limma从公开的GEO数据集中鉴定差异表达基因（DEGs），随后进行基于字符串的蛋白质-蛋白质相互作用（PPI）分析，基于cytohubba的枢纽基因排序，并构建miRNA-mRNA调控网络。共鉴定出1401个deg，包括859个上调基因和542个下调基因，富集于与EMT调控、细胞周期进程、细胞外基质重塑和凋亡相关的途径。中心基因如CDK1、CDC20、JUN和FABP5被鉴定出来，而miR-200、miR-345和miR-577成为与EMT和凋亡信号相关的关键调控mirna。体外验证进一步支持Kisspeptin-10对GB细胞EMT和凋亡标志物的调节作用。这些发现强调了kisspeptin -10相关分子调控在GB中的诊断和治疗意义。这是第一个整合转录组学、miRNA-mRNA网络分析和实验验证来阐明kisspeptin -10介导的GB进展调节的研究。

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引用次数: 0

Computational evaluation of indole alkaloids as inhibitors of 3-hydroxykynurenine transaminase in malaria vector control 吲哚类生物碱作为3-羟基犬尿氨酸转氨酶抑制剂在疟疾病媒控制中的计算评价。

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-09 DOI: 10.1016/j.compbiolchem.2025.108830

Angelina.I. Makaye , Lucas P. Kwiyukwa , Lucas Paul , Andrew Banyikwa , Said A.H. Vuai

The enzyme 3-hydroxykynurenine transaminase (3-HKT) is critical for the production of xanthurenic acid, a key metabolite required for Plasmodium falciparum gametogenesis in Anopheles mosquitoes. Recognizing the importance of disrupting this pathway, the study explores the potential of indole alkaloids as inhibitors of 3-HKT, leveraging their natural insecticidal properties. Computational methods, including virtual screening, molecular dynamics, and MMPBSA analyses, were applied to evaluate the binding affinity and stability of indole alkaloids. Virtual screening results revealed spiroindolone (EP4), asperpenazine (SP4), and strychnine (ST6) as the most promising inhibitors with the strongest binding free energy of −7.38, −7.21 and −7.12 kcal/mol for 3-HKT (PDB ID:2CH1) and −7.47 −7.13, and −7.08 kcal/mol for 2CH2, respectively. ST6 forms a structurally stable complex, but its interactions are energetically weaker, resulting in a lower binding affinity than EP4. The Molecular dynamics simulation study evaluated the stability and binding properties of EP4, SP4, and ST6 against 3-HKT using RMSD, RMSF, and ROG analyses, along with MM/PBSA calculations. The results showed that the EP4, ST6, and SP4 systems exhibited good stability and binding properties, with average RMSF values of 0.3 Å in all systems. The MMPBSA results supported MD results; EP4 demonstrated high binding energy of −69.658 and −77.025, followed by SP4 (−68.658 and −75.947), while ST6 exhibited binding energy values of −49.294 and −39.859 kJ/mol. The results revealed that EP4 and SP4 exhibited stable binding with the 3-HKT and could be suggestive candidates for anti-mosquito insecticide design. ST6 forms a stable complex, but the nature of the interactions (primarily van der Waals, less favorable electrostatics/solvation) makes it inferior to EP4, and thus optimization is vital. Further in vitro and in vivo studies should be conducted to validate the compounds' efficacy.

3-羟基尿氨酸转氨酶（3-HKT）对黄嘌呤酸的产生至关重要，黄嘌呤酸是恶性疟原虫配子发生所需的关键代谢物。认识到破坏这一途径的重要性，该研究探索了吲哚生物碱作为3-HKT抑制剂的潜力，利用其天然的杀虫特性。采用虚拟筛选、分子动力学和MMPBSA分析等计算方法评价吲哚类生物碱的结合亲和力和稳定性。虚拟筛选结果显示，3-HKT （PDB ID:2CH1）的结合自由能为-7.38、-7.21和-7.12 kcal/mol，而2CH2的结合自由能分别为-7.47 -7.13和-7.08 kcal/mol，螺隆多酮（EP4）、阿斯哌嗪（SP4）和士的宁（ST6）是最有希望的抑制剂。ST6形成结构稳定的复合物，但其相互作用能量较弱，导致其结合亲和力低于EP4。分子动力学模拟研究利用RMSD、RMSF和ROG分析，以及MM/PBSA计算，评估了EP4、SP4和ST6对3-HKT的稳定性和结合性能。结果表明，EP4、ST6和SP4体系均具有良好的稳定性和结合性能，RMSF平均值均为0.3 Å。MMPBSA结果支持MD结果；EP4的结合能分别为-69.658和-77.025，其次是SP4(-68.658和-75.947)，ST6的结合能分别为-49.294和-39.859 kJ/mol。结果表明，EP4和SP4与3-HKT结合稳定，可作为抗蚊杀虫剂的候选物。ST6形成稳定的配合物，但相互作用的性质（主要是范德华，不太有利的静电/溶剂化）使其不如EP4，因此优化是至关重要的。进一步的体外和体内研究应进行验证化合物的功效。

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引用次数: 0

Diosgenin targets ITGA11-driven angiogenesis in hepatocellular carcinoma: Prognostic and mechanistic insights 薯蓣皂苷元靶向itga11驱动的肝细胞癌血管生成：预后和机制的见解

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-09 DOI: 10.1016/j.compbiolchem.2025.108822

Hao Zheng , Shengwei Tang , Zichuan Yu , Ruida Shi , Ruiyu Zhang , Xiaoyu Qu , Hao Wan , Chenshuo Fang , Xin Wang , Ye Zhu , Liangyun Guo

Background

LIHC is a solid tumor with poor prognosis. Angiogenesis-related gene models have been developed for diseases such as cutaneous melanoma and cervical cancer to accurately predict prognosis, but angiogenesis models for LIHC have not been reported. The goal of our work is to develop a new angiogenic prognostic model for LIHC.

Method

Based on TCGA data, we constructed a 10 gene-model of angiogenesis-related genes using WGCNA and LASSO regression algorithm. We also evaluated its prognostic significance using the ROC curve and the K-M survival analysis. We focused on the model gene ITGA11, examining its expression, correlation with clinicopathological features and survival, and its functional role. In vivo tumorigenesis studies, tube formation tests, and CCK8 were used to assess the pharmacological effects.

Result

We constructed a 10-gene model based on angiogenesis-related genes in LIHC and identified ITGA11 as a key gene. ROC curve analysis showed that the model had a moderate predictive performance, with AUC values of 0.527, 0.486, and 0.571 for 1-, 3-, and 5-year overall survival. Survival analysis confirmed that high ITGA11 expression was significantly associated with poor prognosis (HR = 1.48, 95 % CI: 1.04–2.12, p = 0.03). Functionally, ITGA11 was highly overexpressed in LIHC and promoted angiogenesis-related invasion and migration. Overexpression of ITGA11 increased the expression of VEGFA, thereby stimulating angiogenesis. Conversely, diosgenin treatment markedly downregulated ITGA11, VEGFA, and CCL11 expression in LIHC cells, leading to the suppression of angiogenesis both in vitro and in vivo.

Conclusion

We developed a predictive model for vascular issues in LIHC, identified important gene ITGA11 that can promote angiogenesis in LIHC and influence tumor progression in LIHC patients through the regulation of angiogenesis. We also found a small molecule medication called diosgenin that can target ITGA11's angiogenic effects.

背景：lihc是一种预后较差的实体瘤。血管生成相关基因模型已被用于皮肤黑色素瘤和宫颈癌等疾病，以准确预测预后，但LIHC的血管生成模型尚未报道。我们的工作目标是为LIHC开发一种新的血管生成预后模型。方法基于TCGA数据，采用WGCNA和LASSO回归算法构建血管生成相关基因的10个基因模型。我们还使用ROC曲线和K-M生存分析来评估其预后意义。我们重点关注模型基因ITGA11，研究其表达、与临床病理特征和生存的相关性及其功能作用。体内肿瘤发生研究、试管形成试验和CCK8用于评估药理作用。结果构建了LIHC血管生成相关基因的10基因模型，并确定ITGA11为关键基因。ROC曲线分析显示，该模型具有中等的预测性能，1年、3年和5年总生存期的AUC值分别为0.527、0.486和0.571。生存分析证实，ITGA11高表达与预后不良有显著相关性（HR = 1.48, 95 % CI: 1.04-2.12, p = 0.03）。功能上，ITGA11在LIHC中高度过表达，促进血管生成相关的侵袭和迁移。过表达ITGA11增加VEGFA的表达，从而刺激血管生成。相反，黄芪皂苷元处理显著下调LIHC细胞中ITGA11、VEGFA和CCL11的表达，导致体外和体内血管生成受到抑制。结论我们建立了LIHC血管问题的预测模型，确定了促进LIHC血管生成的重要基因ITGA11，并通过调节血管生成影响LIHC患者的肿瘤进展。我们还发现了一种叫做薯蓣皂苷元的小分子药物，它可以靶向ITGA11的血管生成作用。

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引用次数: 0

Multi-component synergy of safflower (Carthamus tinctorius L.) against hypertension-dyslipidemia: Network pharmacology and molecular docking study 红花抗高血压-血脂异常多组分协同作用：网络药理学与分子对接研究。

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-09 DOI: 10.1016/j.compbiolchem.2025.108831

Xiao Hu , Yue Yu , Chao Wei , Jiazheng Sun , Xiangting Lin , Ruixue Chen

Background

Hypertension and dyslipidemia are prevalent comorbidities that synergistically increase cardiovascular risk. This study aims to systematically investigate the multi-component therapeutic mechanisms of safflower (Carthamus tinctorius L.) against this comorbidity.

Methods

Disease-related targets for hypertension and dyslipidemia were retrieved from GeneCards, OMIM, and TTD databases. Active components of safflower were screened from TCMSP based on oral bioavailability (OB ≥ 30 %) and drug-likeness (DL ≥ 0.18). Intersection targets were analyzed via functional enrichment and protein-protein interaction (PPI) network. Molecular docking simulations validated binding affinities between key components and core targets using AutoDock Vina.

Results

Fifty-nine shared therapeutic targets were identified. Enrichment analysis highlighted critical pathways including the AGE-RAGE signaling pathway in diabetic complications, lipid and atherosclerosis, and TNF signaling pathway. PPI network analysis identified eight hub targets (ICAM1, ESR1, VCAM1, EGFR, TNF, IL2, PPARG, MMP9). Molecular docking predicted strong binding energies (< −7 kcal/mol) between 11 active components (e.g., baicalein, baicalin, kaempferol) and six core targets, suggesting synergistic therapeutic effects through multi-target modulation.

Conclusion

This integrative study is the first to systematically reveal safflower's multi-component, multi-target, multi-pathway" mechanism against hypertension-dyslipidemia comorbidity, providing a theoretical basis for its clinical application. However, these computational findings are predictive and require further experimental validation.

背景：高血压和血脂异常是常见的合并症，可协同增加心血管风险。本研究旨在系统探讨红花（Carthamus tinctorius L.）多组分对这种合并症的治疗机制。方法：从GeneCards、OMIM和TTD数据库中检索高血压和血脂异常的疾病相关靶点。根据口服生物利用度（OB≥30 %）和药物相似度（DL≥0.18）筛选红花有效成分。交叉靶点通过功能富集和蛋白相互作用（PPI）网络进行分析。使用AutoDock Vina进行分子对接模拟，验证了关键组件与核心靶点之间的结合亲和力。结果：共鉴定出59个共同的治疗靶点。富集分析强调了糖尿病并发症、脂质和动脉粥样硬化中的AGE-RAGE信号通路和TNF信号通路等关键通路。PPI网络分析确定了8个枢纽靶点（ICAM1、ESR1、VCAM1、EGFR、TNF、IL2、PPARG、MMP9）。分子对接预测黄芩素、黄芩苷、山奈酚等11种活性成分与6个核心靶点的结合能（< -7 kcal/mol）较强，提示通过多靶点调控实现协同治疗。结论：本综合研究首次系统揭示了红花抗高血压-血脂异常多组分、多靶点、多途径的作用机制，为其临床应用提供了理论依据。然而，这些计算结果是预测性的，需要进一步的实验验证。

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引用次数: 0

Harnessing retinoic acid metabolism-related genes to identify lung adenocarcinoma subtype and establish a risk model for predicting prognosis and drug therapy response 利用维甲酸代谢相关基因鉴定肺腺癌亚型，建立预测预后和药物治疗反应的风险模型

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-08 DOI: 10.1016/j.compbiolchem.2025.108823

Danting Zheng , Weichu Zhang , Li Xu

Background

The metabolism of retinoic acid (RA) is associated with the progression of lung adenocarcinoma (LUAD), but the relationship between RA metabolism-related genes (RAMRGs) and LUAD prognosis remains unclear.

Objectives

The goal of this study was to develop and validate a prognostic model based on RAMRGs for LUAD patients.

Methods

LASSO-Cox and multivariate Cox regression analyses were undertaken, with data from TCGA-LUAD used to identify RAMRGs to create a prognostic model and data from the GEO-LUAD cohort utilized to validate the model. The predictive ability of the model was further evaluated using the nomogram. In addition, functional enrichment analysis, immunological characteristics analysis, and sensitivity analysis of chemotherapy drugs were performed.

Results

A novel prognostic model containing 10 RAMRGs (CCDC17, CLCA1, CYP17A1, FETUB, IGF2BP1, IGFBP1, KCNB2, NTSR1, RPE65, and VGF) was established. The reliable prediction performance of this model in LUAD patients was verified. The DEGs in high-risk and low-risk groups were involved in neural activity of ligand-receptor interaction, Neutrophil extracellular trap formation, and metabolism of xenobiotics by cytochrome P450. The low-risk group had a higher abundance of aDCs, iDCs, Mast_cells, and Neutrophils, and had a higher chance of benefiting from immunotherapy. In both groups, TP53 showed the highest mutation rates, with the high-risk group exhibiting a higher rate than the low-risk group (60 % vs. 39 %). In addition, Dabrafenib, ARQ-680, Vemurafenib, BGB-283, and MLN-2480 were potential therapeutic drugs for LUAD.

Conclusion

RAMRGs serve as useful biomarkers to predict prognosis in LUAD patients, and may guide the immunotherapy regimen.

维甲酸（RA）的代谢与肺腺癌（LUAD）的进展有关，但RA代谢相关基因（RAMRGs）与LUAD预后的关系尚不清楚。本研究的目的是建立并验证基于RAMRGs的LUAD患者预后模型。方法采用slaso -Cox和多变量Cox回归分析，利用TCGA-LUAD的数据识别RAMRGs建立预后模型，并利用GEO-LUAD队列的数据验证模型。模型的预测能力进一步用模态图进行评价。此外，还进行了功能富集分析、免疫学特性分析和化疗药物敏感性分析。结果建立了包含CCDC17、CLCA1、CYP17A1、FETUB、IGF2BP1、IGFBP1、KCNB2、NTSR1、RPE65、VGF等10个RAMRGs的新型预后模型。验证了该模型对LUAD患者的可靠预测性能。高危组和低危组的deg参与配体-受体相互作用的神经活动、中性粒细胞胞外陷阱的形成以及细胞色素P450对外源药物的代谢。低危组adc、idc、Mast_cells和中性粒细胞的丰度更高，免疫治疗获益的机会也更高。在两组中，TP53的突变率最高，高危组的突变率高于低危组（60 %对39 %）。此外，Dabrafenib、ARQ-680、Vemurafenib、BGB-283和MLN-2480是潜在的LUAD治疗药物。结论ramrgs是预测LUAD患者预后的有效生物标志物，可指导LUAD患者的免疫治疗方案。

{"title":"Harnessing retinoic acid metabolism-related genes to identify lung adenocarcinoma subtype and establish a risk model for predicting prognosis and drug therapy response","authors":"Danting Zheng , Weichu Zhang , Li Xu","doi":"10.1016/j.compbiolchem.2025.108823","DOIUrl":"10.1016/j.compbiolchem.2025.108823","url":null,"abstract":"<div><h3>Background</h3><div>The metabolism of retinoic acid (RA) is associated with the progression of lung adenocarcinoma (LUAD), but the relationship between RA metabolism-related genes (RAMRGs) and LUAD prognosis remains unclear.</div></div><div><h3>Objectives</h3><div>The goal of this study was to develop and validate a prognostic model based on RAMRGs for LUAD patients.</div></div><div><h3>Methods</h3><div>LASSO-Cox and multivariate Cox regression analyses were undertaken, with data from TCGA-LUAD used to identify RAMRGs to create a prognostic model and data from the GEO-LUAD cohort utilized to validate the model. The predictive ability of the model was further evaluated using the nomogram. In addition, functional enrichment analysis, immunological characteristics analysis, and sensitivity analysis of chemotherapy drugs were performed.</div></div><div><h3>Results</h3><div>A novel prognostic model containing 10 RAMRGs (CCDC17, CLCA1, CYP17A1, FETUB, IGF2BP1, IGFBP1, KCNB2, NTSR1, RPE65, and VGF) was established. The reliable prediction performance of this model in LUAD patients was verified. The DEGs in high-risk and low-risk groups were involved in neural activity of ligand-receptor interaction, Neutrophil extracellular trap formation, and metabolism of xenobiotics by cytochrome P450. The low-risk group had a higher abundance of aDCs, iDCs, Mast_cells, and Neutrophils, and had a higher chance of benefiting from immunotherapy. In both groups, TP53 showed the highest mutation rates, with the high-risk group exhibiting a higher rate than the low-risk group (60 % vs. 39 %). In addition, Dabrafenib, ARQ-680, Vemurafenib, BGB-283, and MLN-2480 were potential therapeutic drugs for LUAD.</div></div><div><h3>Conclusion</h3><div>RAMRGs serve as useful biomarkers to predict prognosis in LUAD patients, and may guide the immunotherapy regimen.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"121 ","pages":"Article 108823"},"PeriodicalIF":3.1,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of therapeutic targets and potential phytochemicals for UTI treatment from Myristica fragrans through CADD 利用CADD技术鉴定香肉豆丝治疗尿路感染的治疗靶点和潜在植物化学物质

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry

Pub Date : 2025-12-05 DOI: 10.1016/j.compbiolchem.2025.108820

Aswathi K. Biju , Jaganathan Ramakrishnan , Manikandan Alagumuthu

Urinary tract infections (UTIs) are common health glitches caused by microbial pathogens, which frequently result in inflammation and reduced urine function. Myristica fragrans, a medicinal herb having high therapeutic value, was investigated for its activity against UTI. Phytochemicals from M. fragrans were retrieved from IMPPAT and LOTUS databases, and their potential targets were predicted through the SwissTargetPrediction tool. The UTI-related targets were identified from OTP, GeneCards, and OMIM databases. The intersection of herb and disease targets was executed using the web tool Venny 2.1.0, and a PPI network was constructed for the common targets. Highly clustered targets were identified by employing Cytoscape 3.10.3 software. Functional enrichment analysis was carried out for the highly clustered core targets using ShinyGO 0.81. Finally, molecular docking, molecular dynamics simulations and ADMET predictions were performed. A total of 349 phytochemicals, 918 targets of M. fragrans, and 3826 UTI-related targets were identified. Shared targets between phytochemicals and disease are 467. Eighteen highly clustered genes were identified as being significantly involved in the EGFR tyrosine kinase inhibitor resistance pathway. Finally, the potential targets IGF1R, JAK2, and EGFR show strong binding affinity with respective phytochemicals, supported by well-maintained radius of gyration, consistent hydrogen bonding, moderate residue fluctuations, and stable RMSD. This research demonstrates that M. fragrans exhibits promising anti-UTI activity through the detection of potential targets such as IGF1R, JAK2, and EGFR, along with its effective phytochemicals, and multiple pathways identification provides a strong foundation for future research.

尿路感染（uti）是由微生物病原体引起的常见健康问题，通常会导致炎症和尿功能下降。对具有较高治疗价值的中药香肉豆蔻抗尿路感染的活性进行了研究。从IMPPAT和LOTUS数据库中检索香支曲的植物化学物质，并通过SwissTargetPrediction工具预测其潜在靶点。从OTP、GeneCards和OMIM数据库中确定了与util相关的目标。利用web工具Venny 2.1.0进行中草药和疾病靶点的交叉，并构建了共同靶点的PPI网络。利用Cytoscape 3.10.3软件对高度聚集的靶点进行鉴定。使用ShinyGO 0.81对高度聚集的核心靶点进行功能富集分析。最后进行分子对接、分子动力学模拟和ADMET预测。共鉴定出349种植物化学物质、918个香支原体靶点和3826个uti相关靶点。植物化学物质和疾病之间有467个共同靶点。18个高度聚集的基因被确定为显著参与EGFR酪氨酸激酶抑制剂耐药途径。最后，潜在靶点IGF1R、JAK2和EGFR在良好的旋转半径、一致的氢键、适度的残基波动和稳定的RMSD支持下，与各自的植物化学物质表现出较强的结合亲和力。本研究通过检测潜在靶点如IGF1R、JAK2和EGFR，以及其有效的植物化学物质，证明了香曲菌具有良好的抗uti活性，多途径鉴定为未来的研究提供了坚实的基础。

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引用次数: 0