Computational Biology and Chemistry最新文献

{"title":"Harnessing transcriptome data of Viola inconspicua for discovery of novel cyclotides and AEP ligases","authors":"S. Hamsa,&nbsp;Suhani Pathak,&nbsp;Reema Mishra,&nbsp;Aparajita Mohanty","doi":"10.1016/j.compbiolchem.2025.108614","DOIUrl":"10.1016/j.compbiolchem.2025.108614","url":null,"abstract":"<div><div>Cyclotides are plant-derived cyclic peptides with three conserved disulfide linkages, forming a cyclic cystine knot (CCK) motif. This CCK topology makes them ultra stable structures and resistant to thermal and chemical degradation. Cyclotides are known to exhibit, anti-HIV, antimicrobial, cytotoxic, hemolytic and pesticidal bioactivities. They have been reported in six angiosperm families (Cucurbitaceae, Fabaceae, Poaceae, Rubiaceae, Solanaceae, Violaceae). The identification of novel cyclotides is the first important step for investigating their potential applications in agriculture and therapeutics. To address this need, the present study employed a de novo transcriptome assembly of <em>Viola inconspicua</em> root and shoot tissues. HMM-based searches were used to identify novel cyclotides and the enzymes involved in their biosynthesis, specifically asparaginyl endopeptidases (AEPs). The analysis revealed six types of cyclotide precursor (CP) gene architectures and 68 novel cyclotides of which 31 and 19 were exclusive to roots and shoots respectively, and 18 were common in both tissues. Assessment of potential bioactivity of 68 novel cyclotides was investigated by analysing their physicochemical characteristics, loop sequence variations and phylogenetic studies. Furthermore, the analysis revealed 40 AEP isoforms. Two of these were identified as potential peptide asparaginyl ligases (PALs), important for the cyclization of cyclotides. Moreover, comparison of homology models of potential PALs with experimentally validated structure of PAL from <em>Viola yedoensis</em> (VyPAL2) revealed high structural homology. In summary, this study reveals tissue specific diversity of cyclotides in <em>V. inconspicua</em>; identifies novel cyclotides, provides insights on CP gene architectures and structure of potential PALs.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108614"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773002","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}

{"title":"Identification of hub genes as potential diagnostic biomarkers for cervical cancer: A bioinformatic approach","authors":"Tara Chand ,&nbsp;Pankaj Vaishanavaa ,&nbsp;Ashwini Kumar Dubey ,&nbsp;Gauri Misra","doi":"10.1016/j.compbiolchem.2025.108605","DOIUrl":"10.1016/j.compbiolchem.2025.108605","url":null,"abstract":"<div><h3>Background</h3><div>Cervical cancer remains a prevalent malignancy with rising incidence, primarily due to sexual transmission, persistent HPV infection, and delayed screening. Identifying new biomarkers is critical for improved diagnosis, prognosis, and treatment of cervical cancer. This study utilized integrated bioinformatics to identify potential biomarkers by analysing gene expression data from the GEO database.</div></div><div><h3>Methods</h3><div>Four GEO microarray datasets (GSE7410, GSE7803, GSE52903, GSE67522) were analysed using GEO2R to identify DEGs with an adjusted p-value &lt;0.05. Common DEGs were visualized using Venn diagrams. Protein-protein interaction network was constructed using STRING to identify hub genes. Gene Ontology (GO) and KEGG pathway analyses were performed to investigate biological functions and pathways. The Human Protein Atlas (HPA) was used for <em>in silico</em> validation of protein expression via immunohistochemistry. Kaplan-Meier survival analysis was performed to determine the prognostic value of hub genes.</div></div><div><h3>Results</h3><div>Analysis revealed 684 common DEGs across the datasets (446 upregulated, 238 downregulated). The top 20 upregulated DEGs from GSE67522 were used for heatmap construction and PPI analysis, leading to the identification of nine key hub genes. GO and KEGG analyses showed that six of these were significantly involved in cell cycle regulation and tumorigenic pathways. These hub genes were validated for their protein expression through HPA data.</div></div><div><h3>Conclusion</h3><div>Six hub genes (CCNB2, AURKA, CDC20, CDT1, CENPF, and KIF2C) were identified as potential biomarkers for cervical cancer management.</div></div><div><h3>Impact</h3><div>These findings provide valuable insight into the molecular profiles of genes that play significant roles in cervical cancer for translational outcomes in diagnosis.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108605"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773003","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}

{"title":"Theoretical design of metal–porphin systems for selective interaction with trace geosmin","authors":"Ali Kadhim Wadday ,&nbsp;Sukaina Tuama Ghafel ,&nbsp;Suraa Reaad ,&nbsp;Mustafa M. Kadhim","doi":"10.1016/j.compbiolchem.2025.108604","DOIUrl":"10.1016/j.compbiolchem.2025.108604","url":null,"abstract":"<div><div>Geosmin, even at minuscule concentrations, can significantly compromise the taste and odor of drinking water, making its removal a critical challenge. In this study, an integrated computational strategy encompassing DFT, QTAIM, NCI analysis, RDG, DOS, and Molecular Dynamics simulations was used to probe how geosmin interacts with both pristine Porphin and its copper-coordinated variant. The findings clearly show that copper coordination markedly enhances geosmin adsorption. Specifically, the average isosteric heat increases from 18.66 to 20.67 kcal/mol, while the energy distribution narrows, suggesting more consistent interaction strength. Mulliken charge and electrostatic potential analyses indicate a partial charge transfer involving the hydroxyl group of geosmin, supporting the conclusion that van der Waals and hydrogen-bonding interactions play a significant role. Additionally, copper coordination dramatically reduces the HOMO–LUMO gap from 0.0756 eV to 0.00083 eV signaling increased electronic reactivity and a shift towards semi-metallic character. Molecular Dynamics simulations confirm that these frameworks are both structurally and thermally stable, with total energy fluctuations remaining within ±0.17 kcal/mol. Altogether, these results highlight copper-modified Porphin as a highly promising platform for geosmin adsorption, offering robust thermal stability, enhanced selectivity, and notable electronic property modulation. Such frameworks are potential candidates for next-generation VOC sensors and advanced water purification technologies.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108604"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144772988","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}

{"title":"Machine learning driven identification of therapeutic phytochemicals targeting Hepatocellular carcinoma","authors":"V Vanitha Jain,&nbsp;Madhu Anabala,&nbsp;Deepak Sharma,&nbsp;Rajiniraja Muniyan","doi":"10.1016/j.compbiolchem.2025.108608","DOIUrl":"10.1016/j.compbiolchem.2025.108608","url":null,"abstract":"<div><div>Hepatocellular carcinoma (HCC), being the most common liver cancer, remains a global health concern due to the high mortality rate. HCC is also attributed to severe alcohol abuse, further leading to liver cirrhosis and cytochrome expression. The known treatments for HCC are becoming less effective with high side effects, which highlights the need for promising phytochemicals, as antioxidants, anti-inflammatories, antitumor, and other pharmacological properties. This study comprises a majorly utilized <em>in vitro</em> model for HCC, i.e., Huh 7 cell line, which was considered for retrieving the IC50 values of experimentally known inhibitors using the ChemBL database. Followed by many subsequent steps, Extra Trees Classifier and Light Gradient Boosting Machine (LGBM) showed the best performance of Receiver Operative Characteristic (ROC) of 0.91 and 0.90, respectively, as robust ML-based QSAR models. Furthermore, screening of the unknown phytochemicals and ADMET analysis showed optimum results for the phytochemicals: Bilobol, Corlumine, and Oliveotilic acid. Additionally, HSP90AA1 and CTNNB1, being the major targets with corlumine, had the best docking score of −8.66 kcal/mol and −5.21 kcal/mol, respectively, than the reference compound −8.31 kcal/mol for HSP90AA1 and −4.83 for CTNNB1 kcal/mol respectively. Further studies of molecular dynamic simulation, such as RMSD, RMSF, RG, SASA, and H-bond formation for CTNNB1- corlumine complex showed comparatively better results than HSP90AA1- corlumine complex. In a nutshell, corlumine phytochemicals, as an outcome from this study, may be used for <em>in vitro</em> and <em>in vivo</em> model testing as a novel compound as a pharmaceutical drug molecule for HCC inhibition.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108608"},"PeriodicalIF":3.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773001","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}

{"title":"PreAIS: Prediction of A-to-I editing sites based on DNN-CNN deep learning models","authors":"Xingze Fang ,&nbsp;Yun Zuo ,&nbsp;Youxu Tan ,&nbsp;Xiangrong Liu ,&nbsp;Xiangxiang Zeng ,&nbsp;Zhaohong Deng","doi":"10.1016/j.compbiolchem.2025.108612","DOIUrl":"10.1016/j.compbiolchem.2025.108612","url":null,"abstract":"<div><div>Adenosine-to-inosine RNA editing is crucial in biological processes and diseases, making A-to-I site identification key for research and drug development. However, accurate identification remains challenging due to complexity, low accuracy, and poor generalization in current models. To overcome these, a deep learning model called PreAIS has been proposed for identifying A-to-I editing sites. PreAIS first employs K-mer algorithm for feature extraction, followed by DNN-CNN for model1 construction. Finally, the model1 was trained and evaluated using 10-fold cross-validation. Compared to state-of-the-art models, PreAIS(model1) demonstrated improvements of 3.01 %, 0.67 %, and 5.04 % in Accuracy (ACC), Specificity (Sp), and Sensitivity (Sn) on Dataset 1. Additionally, using a human A-to-I RNA editing site dataset validated by Sanger sequencing, PreAIS(model1) identified 55 out of 58 sites with 94.8 % accuracy, outperforming other classifiers. To further validate the model's generalization capability, Bi-profile Bayes features were extracted from Dataset 2 for model evaluation. While keeping other parameters unchanged, only the input dimensions were adjusted to construct model2. Results from the independent test set demonstrated that even on a different dataset, our model continued to exhibit superior performance, once again surpassing the current best predictive models. Additionally, CAM was employed to interpret the prediction of PreAIS. The predictive model PreAIS and the related dataset constructed in this study can be accessed on the following GitHub page: <span><span>https://github.com/xzfang00/PreAIS</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108612"},"PeriodicalIF":3.1,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739313","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}

{"title":"Computationally guided design and synthesis of pyrimidine–oxazole hybrids as novel antidiabetic agents: kinetic and molecular interaction studies","authors":"Shoaib Khan ,&nbsp;Tayyiaba Iqbal ,&nbsp;Rafaqt Hussain ,&nbsp;Faez Falah Alshehri ,&nbsp;Zafer Saad Al Shehri ,&nbsp;Sobhi M. Gomha ,&nbsp;Magdi E.A. Zaki ,&nbsp;Hamdy Kashtoh","doi":"10.1016/j.compbiolchem.2025.108602","DOIUrl":"10.1016/j.compbiolchem.2025.108602","url":null,"abstract":"<div><div>Diabetes mellitus (DM) is one of the complex and chronic endocrine diseases often characterized by high blood glucose level. Diabetes is due to either pancreases not producing insulin which convert excess of blood glucose to glycogen, or the cell of body becoming unresponsive to insulin’s effect. Primary symptom of DM includes blurry vision, excess urination and slow healing sores but if not diagnosed earlier and treated, it is associated with some severe secondary impairment like cardiovascular diseases, diabetic neuropathy, diabetic nephropathy and Alzheimer’s diseases etc. The focus of current research work is to design and synthesized a novel pyrimidine based oxazole derivatives (1−10) having promising anti-diabetic activity. These derivatives were synthesized by using reagent grade starting material i.e. 4-chloro-6-methylpyrimidin-2-amine. Structural conformation of the synthesized derivative was acquired by ¹H-NMR and ¹³C-NMR and their molecular weight were confirmed by HREI-MS. These compound exhibit moderate to excellent biological potential against α-amylase and α-glucosidase in comparison to standard acarbose IC₅₀= 10.50 ± 0.20 μM and IC₅₀= 10.80 ± 0.10 μM. Among these derivatives, analog 8 having IC₅₀= 5.20 ± 0.10 μM against α-amylase and IC₅₀= 5.70 ± 0.10 μM against α-glucosidase emerged as a most potent compound of the series with excellent inhibitory potency of target enzyme. The biological interaction of the newly synthesized derivatives was studied through molecular docking to assess their enzyme inhibition potency. Furthermore, the molecular dynamic (MD) simulation, density functional theory (DFT) studies are also performed in order to assess their structural conformational changes, stability and reactivity under dynamic environment. Absorption distribution metabolism excretion and toxicity (ADMET) analysis showed that these potent compounds have no toxicological effect.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108602"},"PeriodicalIF":3.1,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724019","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}

{"title":"Advancing explainable AI in healthcare: Necessity, progress, and future directions","authors":"Rashmita Kumari Mohapatra ,&nbsp;Lochan Jolly ,&nbsp;Sarada Prasad Dakua","doi":"10.1016/j.compbiolchem.2025.108599","DOIUrl":"10.1016/j.compbiolchem.2025.108599","url":null,"abstract":"<div><div>Clinicians typically aim to understand the shape of the liver during treatment planning that could potentially minimize any harm to the surrounding healthy tissues and hepatic vessels, thus, constructing a precise geometric model of the liver becomes crucial. Over the years, various methods for liver image segmentation have emerged, with machine learning and computer vision techniques gaining rapid popularity due to their automation, suitability, and impressive results. Artificial Intelligence (AI) leverages systems and machines to emulate human intelligence, addressing real-world problems. Recent advancements in AI have resulted in widespread industrial adoption, showcasing machine learning systems with superhuman performance in numerous tasks. However, the inherent ambiguity in these systems has hindered their adoption in sensitive yet critical domains like healthcare, where their potential value is immense. This study focuses on the interpretability aspect of machine learning methods, presenting a literature review and taxonomy as a reference for both theorists and practitioners. The paper systematically reviews explainable AI (XAI) approaches from 2019 to 2023. The provided taxonomy aims to serve as a comprehensive overview of XAI method traits and aspects, catering to beginners, researchers, and practitioners. It is found that explainable modelling could potentially contribute to trustworthy AI subject to thorough validation, appropriate data quality, cross validation, and proper regulation.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108599"},"PeriodicalIF":3.1,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739286","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}

{"title":"MJnet: A lightweight RNN-based model for microRNA target site prediction","authors":"Junhao Yu,&nbsp;Cong Hui,&nbsp;Jianhua Jia","doi":"10.1016/j.compbiolchem.2025.108603","DOIUrl":"10.1016/j.compbiolchem.2025.108603","url":null,"abstract":"<div><div>Accurate prediction of microRNA (miRNA) target sites is critical for understanding post-transcriptional gene regulation. While recent deep learning models have achieved high predictive accuracy, many suffer from excessive computational complexity and limited interpretability. In this study, we propose MJnet, a lightweight and efficient deep learning model based on a Bidirectional Gated Recurrent Unit (BiGRU) architecture, integrated with simple C2 encoding, a multi-scale one-dimensional convolutional network (TextCNN), and a self-attention mechanism. This framework captures both local sequence features and global contextual dependencies while maintaining low computational cost. Extensive experiments on experimentally validated datasets demonstrate that our model outperforms several traditional and deep learning-based baselines, including Mimosa, in terms of accuracy, F1-score, and robustness across balanced gene-level test sets. Ablation studies confirm the effectiveness of each module, and attention heatmaps reveal interpretable patterns aligned with known seed regions. Our approach offers a practical, reproducible, and interpretable solution for miRNA target site prediction in biologically relevant contexts.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108603"},"PeriodicalIF":3.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721337","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}

{"title":"Molecular insights into ATP-mediated NBD dimerization in an ABC transporter","authors":"Vinothini Santhakumar,&nbsp;Nahren Manuel Mascarenhas","doi":"10.1016/j.compbiolchem.2025.108600","DOIUrl":"10.1016/j.compbiolchem.2025.108600","url":null,"abstract":"<div><div>CmABCB1 is a Cyanidioschyzon merolae homolog of human ABCB1, which is a member of the ATP-binding cassette (ABC) transporter superfamily responsible for the efflux of a wide range of substrates from cells. The two major conformations of CmABCB1 are the inward-facing conformation that binds the substrate to be transported, and the outward-facing conformation that represents the state post the transport of the substrate. In this study, we have performed a 1000 ns all-atom MD simulation of CmABCB1 with and without ATP to understand how ATP binding influences the dynamics and conformation of the protein. Additionally, we have also performed two distinct methods of umbrella sampling (US) simulations to determine the free energy of binding of the nucleotide-binding domains (NBDs) both in the presence and absence of ATP. Our MD simulations reveal significant structural differences of the transporter depending on whether ATP is present or absent at the NBDs. Only when ATP was present at the NBDs, we discovered a specific salt-bridge interaction between the coupling helix (CH) and the nucleotide-binding domain (NBD), which we believe could play a potential role in substrate transport and the accompanying conformational change to the outward-facing state. We also observed a significant loss in the NBD-NBD interactions in the absence of ATP. Our umbrella sampling simulations showed that ATP binding stabilizes the NBD dimer by about ∼25 kJ/mol. Overall, our findings provide valuable insights into the conformational changes of CmABCB1 and the role of ATP in the transport cycle of ABC transporters.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108600"},"PeriodicalIF":2.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711593","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}

{"title":"Bioinformatics analysis combined with experiments to unveil common hub genes, pathways, and transcription factor regulatory networks in ulcerative colitis and osteoporosis","authors":"Kun Li ,&nbsp;Tianshuang Xia ,&nbsp;Bin Peng ,&nbsp;Liyong Lai ,&nbsp;Weiqing Fan ,&nbsp;Yiping Jiang ,&nbsp;Jianyong Han ,&nbsp;Ruiqing Zhu ,&nbsp;Tao Jiang ,&nbsp;Ti Yang ,&nbsp;Xiaoqiang Yue ,&nbsp;Denghai Zhang ,&nbsp;Hailiang Xin","doi":"10.1016/j.compbiolchem.2025.108598","DOIUrl":"10.1016/j.compbiolchem.2025.108598","url":null,"abstract":"<div><h3>Background</h3><div>Osteoporosis (OP) is a common comorbidity in ulcerative colitis (UC) patients. However, the specific mechanism by which UC induces bone loss remains unclear.</div></div><div><h3>Methods</h3><div>Transcriptome data from the GSE87466 and GSE35958 datasets were analyzed to identify common differentially expressed genes (co-DEGs), construct protein-protein interaction network, and perform functional enrichment analysis. The R packages PROGENy, NetAct, and sRACIPE were used to infer the activity of the signaling pathways, construct transcription factor regulatory networks, and identify disease-promoting genes. A dextran sulfate sodium (DSS)-induced UC mouse model was established to validate the biological processes enriched among co-DEGs.</div></div><div><h3>Results</h3><div>A total of 66 upregulated co-DEGs were identified, with ICAM1, ITGA5, THY1, ITGB2, TGFB1, MMP2, COL6A2, FLNA, CD5, and IL16 identified as hub genes. These upregulated co-DEGs were significantly enriched in processes, such as response to cytokine, leukocyte transendothelial migration, regulation of myeloid leukocyte mediated immunity, and osteoclast differentiation. Seven signaling pathways, NF-κB, TNF-α, MAPK, EGFR, TGF-β, hypoxia, and TRAIL, were consistently activated in both UC and OP. A total of 12 genes were identified as disease-suppressing and 22 as disease-promoting in UC, while 7 genes were found to be disease-suppressing and 5 disease-promoting in OP. Among these, RELA, NFKB1, and FOS were found to be common disease-promoting genes in both UC and OP. DSS administration in mice not only induced colitis, but also resulted in significant bone loss, likely driven by TNF-α–mediated enhancement of bone resorptive activity.</div></div><div><h3>Conclusions</h3><div>UC-related colonic inflammation triggers cytokine release and promotes immune cell activation and trafficking into the bone marrow microenvironment. Key inflammatory mediators, particularly TNF-α, act synergistically with receptor activator of nuclear factor kappa-Β ligand (RANKL) to enhance the differentiation of osteoclast precursors into mature osteoclasts. This inflammatory milieu accelerates bone resorption and ultimately leads to bone loss and structural degradation. These findings suggest three potential dual-targeted therapeutic strategies for UC and OP: inhibiting TNF-α, targeting leukocyte migration-related hub genes (ICAM1, ITGA5, ITGB2, and TGFB1), and inhibiting common disease-promoting genes (RELA, NFKB1, and FOS).</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"119 ","pages":"Article 108598"},"PeriodicalIF":2.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678926","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}