Frontiers in bioinformatics最新文献

{"title":"Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma.","authors":"Shangyi Luo, Li Liu, Yang Sun, Jian Shi, Yajing Zhang","doi":"10.3389/fbinf.2025.1669236","DOIUrl":"10.3389/fbinf.2025.1669236","url":null,"abstract":"<p><strong>Introduction: </strong>Intra-tumoral heterogeneity is a prominent characteristic of hepatocellular carcinoma (HCC). However, it remains unexplored whether intra-tumoral transcriptomic differences can capture crucial information regarding HCC evolution and be utilized to derive a predictive signature for patient's clinical trajectories.</p><p><strong>Methods: </strong>We quantified transcriptomic heterogeneity using four multiregional HCC cohorts comprising 172 samples from 37 patients, and validated transcriptomic heterogeneity and spatial dynamics using multiregional single-cell transcriptomic profiling of 110,817 cells from 34 liver specimens. The HCC evolutionary signature (HCCEvoSig) was developed and assessed across six cross-platform HCC cohorts.</p><p><strong>Results: </strong>Genes exhibiting high intra- and inter-tumor expression variation were significantly enriched in a gene set associated with HCC prognosis, from which we developed and validated a reproducible and robust transcriptomic signature, HCCEvoSig. Multiregional single-cell data confirmed the high intra- and inter-tumoral heterogeneity of HCCEvoSig genes across different cell types, and importantly, demonstrated that the dysregulation of HCCEvoSig genes exhibited a geospatially gradual transition from the non-tumor region to the tumor border and tumor core, as well as from non-malignant to malignant epithelial cells. HCCEvoSig showed significant positive associations with adverse features of HCC, and a high HCCEvoSig risk score predicted increased risks of disease progression and mortality, independent of established clinicopathological indices. Furthermore, HCCEvoSig outperformed 15 published signatures in discriminative ability and prognostic accuracy, particularly regarding 1-year survival rates. Notably, HCCEvoSig demonstrated predictive utility for responses to immunotherapy and trans-arterial chemoembolization. Additionally, we established a well-calibrated predictive nomogram that integrates HCCEvoSig and TNM stage to generate an individualized numerical probability of mortality.</p><p><strong>Conclusion: </strong>Our study reveals that regional transcriptional heterogeneity within tumors is substantial enough to capture survival signals, and the constructed and validated HCCEvoSig provides reliable prognostic information for HCC patients.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1669236"},"PeriodicalIF":3.9,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12399655/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144994608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DIAMOND2GO: rapid Gene Ontology assignment and enrichment detection for functional genomics.","authors":"Christopher Golden, David J Studholme, Rhys A Farrer","doi":"10.3389/fbinf.2025.1634042","DOIUrl":"10.3389/fbinf.2025.1634042","url":null,"abstract":"<p><p>DIAMOND2GO (D2GO) is a high-speed toolset for assigning Gene Ontology (GO) terms to genes or proteins based on sequence similarity. Leveraging the ultra-fast alignment capabilities of DIAMOND, which is 100 to 20,000 times faster than BLAST, D2GO enables rapid functional annotation of large-scale datasets. D2GO maps GO terms from pre-annotated sequences in the NCBI non-redundant database to query sequences. During benchmarking, D2GO assigned over 2 million GO terms to 98% of 130,184 predicted human protein isoforms in under 13 min on a standard laptop. In addition to annotation, D2GO includes an enrichment analysis tool that allows users to identify significantly overrepresented GO terms between subsets of sequences. We compared D2GO against two widely used tools, Blast2GO and eggNOG-mapper, and observed substantial differences in the number and type of annotations produced. These discrepancies reflect varying sensitivities and specificities across tools and suggest that using multiple methods in tandem may improve overall annotation coverage. D2GO is open-source and freely available under the MIT license at https://github.com/rhysf/DIAMOND2GO.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1634042"},"PeriodicalIF":3.9,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12394471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precision medicine on a budget in Africa: using existing genetic data to mitigate adverse drug reactions to conventional cancer drugs.","authors":"Alexandra Lindsey Djomkam Zune, Charles Ochieng' Olwal, Emmanuel Agbeli, Abdoulaye Baniré Diallo, Emmanuella Amoako, Yaw Bediako, Lily Paemka","doi":"10.3389/fbinf.2025.1555637","DOIUrl":"10.3389/fbinf.2025.1555637","url":null,"abstract":"<p><p>Variations in drug-metabolizing enzymes and transporters are associated with adverse drug reactions (ADRs). ADRs to cancer drugs can differ among populations owing to environmental and genetic differences. Due to limited resources and prohibitive costs associated with drug development, African countries rely on cancer drugs developed from non-African genetic backgrounds. Black Africans carry a high burden of ADRs partly because of the use of poorly optimized drugs. Black Africans are the least studied population despite being the most genetically diverse. There is a profound lack of pharmacogenetic studies in Black African populations, necessitating an urgent need for pharmacogenomic studies in Black African populations to optimize dosing and minimize ADRs. Using two common generic cancer drugs, capecitabine and cyclophosphamide, we leveraged the PharmGKB platform and several genomic databases to highlight the need for pharmacogenomic studies in Africa. Our computational approach identifies previously reported and unreported toxicity- and efficacy-associated variants that are overrepresented or underrepresented in Black Africans relative to other ethnicities. These findings suggest that capecitabine and cyclophosphamide may not work optimally and/or may predispose Black Africans to ADRs. This underscores the need for population-based drug screening and development to minimize ADRs and guarantee better treatment outcomes. Since Black Africans are currently underrepresented in genomic studies, African scientists could adopt our low-cost approach to evaluate the suitability of existing drugs for treating diseases. However, in the long term, African scientists must initiate large-scale genomic studies that will drive the discovery of African-tailored drugs and promote the implementation of precision medicine on the continent.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1555637"},"PeriodicalIF":3.9,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12390963/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144981007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stain-free artificial intelligence-assisted light microscopy for the identification of blood cells in microfluidic flow.","authors":"Alexander Hunt, Holger Schulze, Kay Samuel, Robert B Fisher, Till T Bachmann","doi":"10.3389/fbinf.2025.1628724","DOIUrl":"10.3389/fbinf.2025.1628724","url":null,"abstract":"<p><p>The identification and classification of blood cells are essential for diagnosing and managing various haematological conditions. Haematology analysers typically perform full blood counts but often require follow-up tests such as blood smears. Traditional methods like stained blood smears are laborious and subjective. This study explores the application of artificial neural networks for rapid, automated, and objective classification of major blood cell types from unstained brightfield images. The YOLO v4 object detection architecture was trained on datasets comprising erythrocytes, echinocytes, lymphocytes, monocytes, neutrophils, and platelets imaged using a microfluidic flow system. Binary classification between erythrocytes and echinocytes achieved a network F1 score of 86%. Expanding to four classes (erythrocytes, echinocytes, leukocytes, platelets) yielded a network F1 score of 85%, with some misclassified leukocytes. Further separating leukocytes into lymphocytes, monocytes, and neutrophils, while also increasing the dataset and tweaking model parameters resulted in a network F1 score of 84.1%. Most importantly, the neural network's performance was comparable to that of flow cytometry and haematology analysers when tested on donor samples. These findings demonstrate the potential of artificial intelligence for high-throughput morphological analysis of unstained blood cells, enabling rapid screening and diagnosis. Integrating this approach with microfluidics could streamline conventional techniques and provide a fast automated full blood count with morphological assessment without the requirement for sample handling. Further refinements by training on abnormal cells could facilitate early disease detection and treatment monitoring.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1628724"},"PeriodicalIF":3.9,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12391159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequence-based prioritization of i-Motif candidates in the human genome.","authors":"Veronica Remori, Michela Prest, Mauro Fasano","doi":"10.3389/fbinf.2025.1657841","DOIUrl":"10.3389/fbinf.2025.1657841","url":null,"abstract":"<p><strong>Introduction: </strong>i-Motifs (iMs) are cytosine-rich, four-stranded DNA structures with emerging roles in gene regulation and genome stability. Despite their biological relevance, genome-wide prediction of iM-forming sequences remains limited by low specificity and high false-positive rates, leading to considerable experimental burden.</p><p><strong>Method: </strong>To address this, we developed a refined computational approach that prioritizes high-confidence iM candidates using a Position-Specific Similarity Matrix (PSSM) derived from multiple sequence alignments. The human reference genome (hg38) was scanned using a custom regular expression targeting cytosine-rich motifs, followed by scoring each sequence with the PSSM. Statistical significance was assessed via permutation testing, one-sided t-tests, Benjamini-Hochberg correction, and Z-scores.</p><p><strong>Results: </strong>This pipeline identified 37,075 candidate sequences (15-46 nucleotides) with strong iM-forming potential. Validation against experimentally confirmed iMs and known G-quadruplexes (G4s) demonstrated significant differences in alignment scores and sequence similarity, confirming structural specificity. A random forest classifier trained on nucleotide features further supported the distinctiveness of the candidates, achieving a high classification performance.</p><p><strong>Conclusion: </strong>This work presents a scalable and statistically robust method to enrich for biologically relevant iM sequences, providing a valuable resource for future experimental validation and the rational design of ligands targeting iMs to modulate gene expression in contexts such as cancer.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1657841"},"PeriodicalIF":3.9,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12378704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internal fossil constraints have more effect on the age estimates of crown Palaeognathae than different phylogenomic data type.","authors":"Alexandre Pedro Selvatti, Naoko Takezaki","doi":"10.3389/fbinf.2025.1563786","DOIUrl":"10.3389/fbinf.2025.1563786","url":null,"abstract":"<p><p>Palaeognathae is an ancient bird lineage that includes the volant tinamous and six flightless lineages: ostrich, rhea, cassowary, emu, kiwi (extant) and moa, elephant bird (extinct). Over the past decade, a consensus has emerged on the relationships within the group. In this consensus, the ostrich branch splits first, followed by rheas, a clade containing tinamou and moa and a clade with the emu and cassowary sister to the kiwi and elephant bird. However, the timing of the origin of these major clades remains uncertain. In phylogenomic studies, the origin of the crown Palaeognathae is typically dated to the K-Pg boundary (∼66 Ma), though one study suggested a younger Early Eocene age (∼51 Ma). This discrepancy might result from the number and position of fossil priors (calibration strategies) or by differences in genomic regions sampled (data types). We investigated the impact of calibration strategies and data types on the timing of the Palaeognathae root using genomic sequences from nuclear (noncoding [CNEE and UCE] and coding [first and second codon positions]) and mitogenomic datasets. The nuclear dataset included 14 Palaeognathae species (13 extant and the extinct moa), while the mitogenomic included 31 species, covering all extant and extinct lineages. The datasets were analyzed with and without internal calibrations. The age estimates were more influenced by calibration strategy than data type, although some nuclear data (CNEE) produced substantially younger ages except for the Casuariiformes node, whilst another dataset (PRM) from a previous study estimated younger ages for Casuariiformes compared to the other datasets. Nevertheless, our results consistently placed the origin of crown Palaeognathae around the K-Pg boundary (62-68 Ma), even when using the original dataset that produced the Eocene age. These findings demonstrate that multiple internal calibrations yield consistent results across different sequence types and taxon schemes, providing robust estimates of the crown Palaeognathae age. This improved timing enhances our understanding of the early evolutionary history of this clade, particularly regarding the placement of enigmatic Paleocene fossils, such as Lithornithidae and <i>Diogenornis</i>, which in this timeframe can be assigned to internal branches within the crown Palaeognathae.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1563786"},"PeriodicalIF":3.9,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12368558/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144981017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico analysis of CSF2RB from cancer genomic databases reveals a heterogeneous role in different breast cancer subtypes.","authors":"Raghad Alshelaiel, Abdulmohsen Alkushi, Lolwah Abdullah Alriyees, Abir Abdullah Alamro, Humidah Alanazi, Areej Alhareeri, Bader AlMuzzaini, Mamoon Rashid","doi":"10.3389/fbinf.2025.1606828","DOIUrl":"10.3389/fbinf.2025.1606828","url":null,"abstract":"<p><strong>Objective: </strong><i>CSF2RB</i> is the common beta chain of the heterodimeric receptors for the cytokines, granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin 3 (IL-3), and interleukin 5 (IL-5). The activation of these cell surface receptors results in functional responses including cellular proliferation, differentiation, survival, and maturation via multiple signaling pathways such as JAK2/STAT5, MAPK, and PI3-kinase/AKT. Moreover, <i>CSF2RB</i> is abnormally expressed in a variety of tumors, especially in leukemia. The implications of <i>CSF2RB</i> in breast cancer remain unclear and have not been widely studied.</p><p><strong>Methods: </strong>We analyzed <i>CSF2RB</i> genetic changes, mRNA expression, DNA methylation, prognosis, and immune infiltration levels across different tumor types, with a focus on breast and hematological malignancies. The data used in this study were obtained from publicly available cancer genomics databases, such as TCGA, cBioPortal, TIMER2.0, GEPIA, and UALCAN.</p><p><strong>Results: </strong>Our <i>in silico</i> analyses showed overexpression of <i>CSF2RB</i> in acute myeloid leukemia (AML) and decreased expression in breast invasive carcinoma (BRCA) compared to matched normal samples. Promoter methylation of <i>CSF2RB</i> was elevated in BRCA samples compared to normal samples. Our analysis further demonstrates that the <i>CSF2RB</i> gene has a favorable prognostic effect in BRCA, although this was not statistically significant across all databases studied. We found that BRCA and its subtypes exhibit high CD8⁺ T-cell infiltration levels that are positively correlated with the <i>CSF2RB</i> gene expression level. Wild-type <i>CSF2RB</i> shows higher expression than the mutated <i>CSF2RB</i> in breast cancer. <i>CSF2RB</i> expression (and/or mutation) has no significant effect on the overall survival probability. <i>CSF2RB</i> expression is downregulated in luminal and HER2-positive samples but upregulated in triple-negative breast cancer (TNBC), compared to that in normal samples.</p><p><strong>Conclusion: </strong>The results suggest a diverse role for the <i>CSF2RB</i> gene across different subtypes of breast cancer. To attribute a clear role to <i>CSF2RB</i> in breast cancer, further functional studies focusing on differential gene expression, methylation, and their prognostic effect in each breast cancer subtype are required.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1606828"},"PeriodicalIF":3.9,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12361248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The bacteriostatic regulation of luteolin from honeysuckle by protein network interaction.","authors":"Jianfeng Zhang, Mujun Chen, Dianzeng Yang, Yanjie Jia","doi":"10.3389/fbinf.2025.1637479","DOIUrl":"10.3389/fbinf.2025.1637479","url":null,"abstract":"<p><p>A comprehensive analysis of the bacteriostatic mechanism of luteolin at the molecular level was performed. Luteolin-related targets were first retrieved from the STITCH database, followed by the acquisition of protein-protein interaction (PPI) information from the STRING database. The retrieved PPI data was subsequently imported into Cytoscape software to construct a PPI network. Finally, the Molecular Complexity Detection (MCODE) algorithm and BinGo plugin were utilized to conduct module analysis and functional annotation of the constructed network, respectively. The results showed that a total of ten targets were successfully screened from the database. Based on these targets, a PPI network consisting of 91 nodes and 332 edges was constructed. Cluster analysis identified seven distinct functional modules, and subsequent module analysis further demonstrated that luteolin was primarily involved in multiple biological processes, including pathogenic bacteria resistance, antibacterial defensive responses, pathogenic fungi resistance, and resistance to both gram-negative and gram-positive bacteria. These findings indicated that luteolin exhibits robust antibacterial and antifungal activities. By investigating the inhibitory mechanism of luteolin at the molecular-network level, this study paves the way for the development of novel bacteriostatic strategies, offering a valuable perspective for related research.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1637479"},"PeriodicalIF":3.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144877043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics analysis of lncRNA and mRNA differentially expressed in patients with cervical cancer.","authors":"Xiaohua An, Xiaoxue Huang, Qiujie Yu, Yiyue Tang, Yan Wang, Huasu Chen, Yafei Zhang, Qianhao Huang, Yudi Rao, Guomei Hu, He Zha","doi":"10.3389/fbinf.2025.1605681","DOIUrl":"10.3389/fbinf.2025.1605681","url":null,"abstract":"<p><p>To verify the expression profile of long non-coding RNAs (lncRNAs) and mRNAs in cervical cancer, identify their clinical significance in HPV16-associated cervical cancer, and annotate the biological function of mRNAs. Three pairs of cancerous and paracancer tissues were selected in cervical squamous cell carcinoma (IB2 stage), high-throughput sequencing was utilized to determine the expression levels of lncRNAs and mRNAs. The detection results were validated by GEPIA database analysis and RT-qPCR. Functional annotations of differential mRNAs were conducted through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network states. Furthermore, the association between antisense lncRNA and mRNA in cervical cancer was analyzed to predict the biological functions of lncRNA. Finally, recombinant lentivirus CV224-HPV16 E6/E7 was transfected into HcerEpic to establish a stable cell line with overexpressed HPV16 E6/E7, then differential lncRNAs were detected by RT-qPCR. Compared to paracancerous tissues, there were 3,608 lncRNAs significantly upregulated and 4,383 lncRNAs significantly downregulated in cervical cancer tissues (Fold change >2 and <i>P</i> < 0.05). Additionally, 3,666 mRNAs were significantly upregulated, while 2,220 mRNAs were significantly downregulated (Fold change >2 and <i>P</i> < 0.05). GO/KEGG enrichment analysis showed that differentially expressed mRNA played a significant role in cell cycle and cell senescence, and was related to signal pathways such as cAMP and MAPK, forming a complex network among the proteins encoded by these mRNAs. Further analysis indicated that the 20 antisense lncRNAs with the most remarkable differences might exert biological functions by influencing their corresponding mRNAs. The results of RT-qPCR revealed that CDKN2B-AS1, HAGLROS and GATA6-AS1 were potentially regulated by HPV16 E6/E7, which were in accordance with those obtained from chip detection. In this study, differentially expressed lncRNAs associated with HPV16 infection were screened and explored their transcriptional molecular functions and biological pathways, providing a molecular basis for predicting diagnostic markers of cervical cancer.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1605681"},"PeriodicalIF":3.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144877102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational investigation of potential natural compounds as inhibitors of monkeypox virus cysteine proteinase.","authors":"Riya Nalwa, Anis Ahmad Chaudhary, Mandeep Chouhan, Prashant Kumar Tiwari, Saurabh Gupta, Hassan Ahmed Rudayni, Vivek Dhar Dwivedi, Sanjay Kumar","doi":"10.3389/fbinf.2025.1637207","DOIUrl":"10.3389/fbinf.2025.1637207","url":null,"abstract":"<p><strong>Introduction: </strong>Monkeypox is a serious viral illness that is rarely seen but is spread from person to person and from animals to humans. Cysteine proteinase, an essential enzyme involved in the replication of the monkeypox virus (MPXV), is one of many possible therapeutic targets for MPXV. The primary function of this enzyme is to cleave the precursor polyprotein into the distinct proteins required for viral assembly. The aim was to develop potential drugs that can inhibit the proteinase and stop the spread of the MPXV.</p><p><strong>Methods: </strong>Virtual screening, molecular docking, molecular dynamics simulation, and free binding energy calculations were used to explore the potential of 569 phytochemicals from a variety of plants that could inhibit the proteinase of the MPXV.</p><p><strong>Results: </strong>The four compounds (Unii-CQ2F5O6yiy, lithospermic acid, kaempferol, and rhamnocitrin) with the best docking scores displayed docking score values ranging from -9.5 to -7.4 kcal/mol and were used for further analysis. Out of these, Unii-CQ2F5O6yiy exhibited a docking score of -9.5 kcal/mol, indicating the highest binding to the proteinase. Unii-CQ2F5O6yiy had the most stable and consistent root mean square deviation (RMSD) of <3 Å.</p><p><strong>Discussion: </strong>We identified the top four phytochemicals that exhibited better docking scores than the reference compound. The RMSDs of proteins in all the phytochemical complexes exhibited acceptable deviation except for lithospermic acid, whereas atoms of Unii-CQ2F5O6yiy and kaempferol in their docked complexes displayed less fluctuation than the reference compound (<5.4 Å).</p><p><strong>Conclusion: </strong>Unii-CQ2F5O6yiy could be used as a potential antiviral agent for the management of monkeypox virus. However, further experimental validation under <i>in vitro</i> and <i>in vivo</i> conditions is required to confirm its antiviral activity against MPXV.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"5 ","pages":"1637207"},"PeriodicalIF":3.9,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12336155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144823332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}