Bioinformatics and Biology Insights最新文献

{"title":"Unravelling Ferroptosis in Sepsis: A Comprehensive Integrative Transcriptomic Analysis Across Age and Disease Severity.","authors":"Miguel Victor Bringel Sales, Helder Imoto Nakaya, Fernando de Queiroz Cunha, Antonio Edson Rocha Oliveira","doi":"10.1177/11779322261447645","DOIUrl":"10.1177/11779322261447645","url":null,"abstract":"<p><p>Ferroptosis, an iron-dependent, regulated form of cell death, has been increasingly recognised as a pivotal driver of organ dysfunction and mortality in sepsis. Despite its importance, the transcriptomic regulation of ferroptosis in human sepsis has not been systematically characterised. Here, we present a comprehensive integrative analysis, combining 17 transcriptomic data sets from previously published studies involving blood samples from septic patients and healthy controls, encompassing microarray, bulk RNA sequencing, and single-cell RNA sequencing platforms. Our findings reveal that ferroptosis-related gene regulation intensifies with disease progression and is markedly more pronounced in adults. Single-cell analysis identified monocytes as the primary regulators of ferroptosis in peripheral blood during sepsis. Eleven core ferroptosis-related genes (<i>ACSL1</i>, <i>ALOX5</i>, <i>CAPG</i>, <i>CREB5</i>, <i>MAPK14</i>, <i>MGST1</i>, <i>MICU1</i>, <i>QSOX1</i>, <i>SAT1</i>, <i>SIAH2</i>, and <i>SLC2A3</i>) were consistently upregulated, serving as robust candidates for sepsis biomarkers, while additional genes correlated with disease severity, suggesting prognostic value. This large-scale integrative approach provides novel molecular insights into sepsis pathophysiology and identifies promising targets for improved diagnosis and therapy.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261447645"},"PeriodicalIF":2.0,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13583280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148987666","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":"Novel Pyrazoline Derivatives as Therapeutic Candidate for Alzheimer's Disease: An Integrated Network Pharmacology and 3D-QSAR Modelling.","authors":"Md Mainuddin Hossain, Towfika Rahman Singdha, Saiful Islam Sakib, Juthi Adhikari, Prottay Choudhury, Md Sumon Miya, Ashis K Sarker, Mukta Das, Abu Zaffar Shibly","doi":"10.1177/11779322261489770","DOIUrl":"10.1177/11779322261489770","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a complex neurodegenerative condition marked by amyloid-β accumulation, tau pathology, and neuroinflammation, while current single-target therapies largely provide symptomatic relief without effectively halting disease progression. Therefore, the rational design and synthesis of novel small molecules capable of simultaneously modulating multiple AD-related targets represent a promising therapeutic strategy. Based on this rationale, novel pyrazoline derivatives were synthesized and their therapeutic potential was evaluated using an integrative computational framework. AD-related genes were retrieved from GeneCards, CTD, and DisGeNET databases, and hub genes were identified through topological and centrality analyses, followed by functional enrichment analyses to explore their biological relevance. Molecular docking was used to evaluate the binding affinities of the synthesized compounds toward the identified hub targets, while 3D-QSAR modeling was used to predict their inhibitory potential. A total of 63 common genes were identified across the three databases, with APOE, BACE1, and CSF1R emerging as key hub genes. Enrichment analysis revealed their involvement in PI3K-Akt, mTOR, NF-κB, TNF, AMPK, and FoxO signaling pathways associated with amyloid processing, tau pathology, and neuroinflammation. Among the evaluated compounds, compound 2a exhibited the strongest binding affinities toward the hub targets along with favorable drug-likeness, pharmacokinetics, toxicity, and promising IC₅₀ values (226-336 nM). The 3D-QSAR models showed high predictive reliability (R² = 0.93-0.96; Q² = 0.94-0.95). These findings highlight APOE, BACE1, and CSF1R as key therapeutic targets and identify compound 2a as a promising multi-target lead candidate for additional experimental validation in AD.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261489770"},"PeriodicalIF":2.0,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13570014/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148954993","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":"Tear MicroRNA-Based Molecular Signature for Keratoconus Stratification: A Cross-Cohort Integration Study.","authors":"Shao-Hsuan Chang, Kuo-Hsuan Hung, Hsieh-Fu Tsai, Chung-Pei Ma, Hao-Chang Chiang, Lung-Kun Yeh","doi":"10.1177/11779322261489962","DOIUrl":"10.1177/11779322261489962","url":null,"abstract":"<p><p>Keratoconus (KC) is a progressive corneal ectatic disorder characterized by structural remodeling and immune-associated molecular alterations. However, whether tear-derived microRNAs reflect corneal molecular changes remains unclear. We analyzed three publicly available corneal transcriptomic datasets (N = 112) to identify immune-associated gene expression patterns using differential expression analysis and Gene Set Enrichment Analysis. In a prospective tear cohort (N = 20), tear miRNA profiling was performed, and candidate miRNAs were selected using LASSO regression. miRNA patterns were integrated with immune-related transcriptomic alterations, and an exploratory molecular-structural index was constructed using standardized hsa-miR-326 expression and keratometry (K2). We identified immune-associated transcriptional alterations in KC corneas and derived a five-miRNA tear signature. The signature showed discriminatory performance in an independent corneal epithelial miRNA dataset (AUC = 0.89, 95% CI: 0.69-1.00; N = 16) and was further evaluated in an additional tear cohort using RT-qPCR (N = 52). Among these candidates, hsa-miR-326 showed consistent downregulation across datasets. Network analysis identified associations between candidate miRNAs and immune-related genes, including <i>IL1B</i>, <i>CD4</i>, <i>CXCL10</i>, and <i>TGFB1</i>. The exploratory molecular-structural index demonstrated an inverse association with keratometric steepening (Spearman ρ = -0.86, p < 0.001). These findings suggest that tear-derived miRNAs may provide complementary molecular information associated with immune-related corneal alterations and warrant further investigation in KC characterization.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261489962"},"PeriodicalIF":2.0,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13570024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148954991","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":"<i>In silico</i> Identification of Key Genes and Repurposable Drugs for Triple-Negative Breast Cancer.","authors":"Nazia Zarin, Tasnim Hosen Tanha, Mimuna Nishad, Rehana Parvin, Redwan Ashad, Md Sajedul Islam, Shaila Haque","doi":"10.1177/11779322261488174","DOIUrl":"10.1177/11779322261488174","url":null,"abstract":"<p><p>Triple-negative breast cancer (TNBC) is a highly aggressive and treatment-resistant subtype, lacking HER2, progesterone, and estrogen receptors. Systemic chemotherapy remains the primary treatment due to the absence of molecular targets, often leading to poor prognosis and high recurrence. This study used an integrated <i>in silico</i> transcriptomic and network-based bioinformatics approach to identify TNBC key genes (TKGs) and explore potential therapeutic candidates. Four TNBC microarray datasets (GSE36295, GSE38959, GSE45827, and GSE65194) were analyzed with the LIMMA algorithm in GEO2R, revealing 315 TNBC-shared differentially expressed genes (TSDEGs). Eight strongly connected TKGs were identified via topological analysis and protein-protein interaction (PPI) network construction across the STRING and IMEx databases from TSDEGs: CDK1, TOP2A, CCNB1, CDK2, FN1, UBC, PRKDC, and PARP1. Enrichment analysis of biological processes, molecular functions, cellular components, and KEGG pathways, combined with regulatory network analysis involving transcription factors and microRNAs, identified pathogenic roles of these genes. CDK1 and CDK2 were identified as the top pharmacological targets for molecular docking studies. Finally, TKG-guided top-ranked two drug molecules (Alsterpaullone and BLU-222) emerged as promising repurposed therapeutic candidates for TNBC. The absorption, distribution, metabolism, excretion, and toxicity (ADMET) and drug-likeness analyses showed these molecules have favorable pharmacokinetic properties. Molecular dynamics simulations over 100 nanoseconds demonstrated stable binding interactions and favorable behavior for the complexes CDK1-Alsterpaullone and CDK2-BLU-222, as indicated by root mean square deviation, fluctuation, and molecular interactions generalized Born surface area. Overall, these findings may aid in diagnosing and treating TNBC, providing valuable resources for future therapeutic strategies.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261488174"},"PeriodicalIF":2.0,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13554646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148918460","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":"Stromal ARHGEF15 Correlates With Inflammatory EMT and Stromal-Immune Crosstalk During Inflammatory Bowel Disease-To-Colorectal Cancer Progression.","authors":"GuoliangLi, Xiangxiang Hao, Guoshuai Chen, Gaowen Huang, Yongshuai Wu, Kewei Jiang, Hongpeng Jiang","doi":"10.1177/11779322261483612","DOIUrl":"10.1177/11779322261483612","url":null,"abstract":"<p><p>Patients with inflammatory bowel disease (IBD) have an increased risk of colorectal cancer (CRC), but how chronic intestinal inflammation drives malignant transformation remains unclear. We retrospectively reanalyzed published single-cell transcriptomic datasets from intestinal biopsies of healthy individuals and patients with IBD; differential expression was assessed using independent t tests with Benjamini-Hochberg false discovery rate correction. We then integrated those single-cell findings with the Cancer Genome Atlas bulk transcriptomes and pharmacogenomic cohorts to trace stromal programs across the IBD-to-cancer continuum. ARHGEF15 emerged as a stromal gene enriched in CD74^hi HLA-DRB1^hi arterial pericytes within inflamed tissue. Its expression rose steadily from IBD to CRC and tracked with epithelial-mesenchymal transition (EMT) activity. In CRC, higher ARHGEF15 expression was associated with shorter overall and progression-free survival. These retrospective, in silico findings identify ARHGEF15 as an exploratory stromal biomarker associated with inflammatory EMT and stromal-immune remodeling during IBD-to-CRC progression. Prospective experimental and clinical validation is required to establish its prognostic or therapeutic relevance.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261483612"},"PeriodicalIF":2.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13535022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148878815","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 Identification of Natural-Product Aromatase (CYP19A1) Inhibitors via Integrated Molecular Docking and QSAR Modelling.","authors":"Erica A Akanko, Samuel Selasi Kporvie, George Hanson, Kofi Sarpong Adu-Manu","doi":"10.1177/11779322261483610","DOIUrl":"10.1177/11779322261483610","url":null,"abstract":"<p><p>Aromatase (CYP19A1) is the rate-limiting enzyme in estrogen biosynthesis and the principal therapeutic target for estrogen receptor-positive (ER+) breast cancer. Despite the clinical success of third-generation aromatase inhibitors (AIs) such as letrozole and anastrozole, acquired resistance and systemic adverse effects, including musculoskeletal pain, bone density loss, and cardiovascular complications, which necessitate the identification of novel scaffolds. This study employs an integrated computational pipeline combining ligand-based quantitative structure-activity relationship (QSAR) modelling and structure-based molecular docking to screen the AfroDB and EANPDB natural product libraries for putative aromatase inhibitors. A curated dataset of 3,068 unique compounds derived from ChEMBL (v33) was used to train Random Forest models, with the binary classification model achieving an area under the receiver operating characteristic curve (AUC) of 0.95 on the independent holdout set, an accuracy of 0.90, and a Matthews correlation coefficient (MCC) of 0.76. The regression model for pIC₅₀ prediction attained an R² of 0.65 and an RMSE of 0.81 pIC₅₀ units on the test set. The trained classifiers were applied to screen 1,871 AfroDB compounds; 361 were predicted active, of which 71 resided within the defined Applicability Domain. Molecular docking into the human aromatase crystal structure (PDB ID: 3S79) revealed that the top candidate, a prenylated dihydroflavone (5,7-dihydroxy-4'-methoxy-3'-(3-hydroxy-3-methylbut-1-enyl)-5'-(3-methylbut-2-enyl)flavanone), achieved a binding affinity of -9.598 kcal/mol, outperforming both letrozole (-7.11 kcal/mol) and anastrozole (-7.617 kcal/mol) under identical docking conditions. The docking protocol was validated by redocking of the co-crystallised ligand (RMSD = 1.35 Å). Comprehensive interaction analysis identified contacts with key active-site residues Arg115, Phe221, Thr310, Val370, Met374, and Phe430. ADMET profiling indicated that 65% of prioritised hits satisfy Lipinski's Rule of Five, while 95% meet Veber bioavailability criteria. This study provides a reproducible computational framework for next-generation AI discovery, adhering to the TRIPOD+AI reporting guidelines for machine learning in biomedical research.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261483610"},"PeriodicalIF":2.0,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13530448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872986","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":"De Novo Molecular Design and Bioactivity Prediction of Novel Hexahydroquinolines as <i>Plasmodium falciparum</i> Calcium-Dependent Protein Kinase 4 (CDPK4) Inhibitors.","authors":"Gbolahan O Oduselu, Damilola S Bodun, Olayinka O Ajani, David J Conway, Lucas N Amenga-Etego, Wellington Oyibo, Gordon A Awandare","doi":"10.1177/11779322261483607","DOIUrl":"10.1177/11779322261483607","url":null,"abstract":"<p><p><i>Plasmodium falciparum</i> Calcium-Dependent Protein Kinase 4 (<i>Pf</i>CDPK4) is a validated target for malaria transmission-blocking interventions, as its inhibition disrupts male gametocyte exflagellation. Hexahydroquinolines (HHQs) have emerged as promising gametocytocidal agents. This study aimed to design novel HHQs as potential <i>Pf</i>CDPK4 inhibitors with good binding affinity, favourable pharmacokinetics, and structural stability. A library of 20,000 novel HHQ analogs was generated using genetic algorithm-driven <i>de novo</i> molecular design in AlvaBuilder and systematically filtered through a pipeline comprising machine-learning-based bioactivity prediction, PAINS removal, pharmacophore modeling, ADMET screening, and structure-based virtual screening. Top-ranking compounds underwent bioisosteric optimization and were evaluated using 300 ns molecular dynamics simulations and density functional theory (DFT) calculations. Comparative <i>in silico</i> validation against known inhibitor Bumped Kinase Inhibitor-1 (BKI-1) and the co-crystallized ligand DXR as controls demonstrated that four HHQ analogs exhibited comparable binding affinities and stable interactions with key residues within the ATP-binding pocket. Favourable ADMET profiles, dynamic stability, and supportive electronic properties further reinforced their inhibition potential. These findings provide biologically meaningful computational evidence supporting HHQ scaffolds as potential <i>Pf</i>CDPK4 inhibitors and demonstrate the utility of integrated bioinformatics approaches for malaria transmission-blocking drug discovery. Further experimental validation is required to confirm the inhibitory activities of the identified hexahydroquinoline compounds.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261483607"},"PeriodicalIF":2.0,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13525292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148857092","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":"Genomic Insights Into <i>Bacillus thuringiensis</i> Strain JSd1 From Bangladesh: A Whole Genome Sequencing Approach.","authors":"Md Abdul Bari, Dipta Chandra Pal, Md Al Muid Khan, Mahfuza Momen, Mahfuza Khan, Muhammad Manjurul Karim, Md Mozammel Hoq, Shakila Nargis Khan","doi":"10.1177/11779322261475762","DOIUrl":"https://doi.org/10.1177/11779322261475762","url":null,"abstract":"<p><p><i>Bacillus thuringiensis</i> (Bt) is a well-known entomopathogenic bacterium widely used in biopesticide formulations due to its diverse arsenal of insecticidal toxins and environmental adaptability. However, the genetic diversity and virulence potential of native Bt strains from South Asia remain underexplored. In this study, we performed whole-genome sequencing and comparative genomic analysis of <i>B. thuringiensis</i> strain JSd1, isolated from Bangladeshi soil. The high-quality draft genome, assembled at 75x coverage, comprises 5.39 Mb in 64 contigs with a GC content of 35.28% and 99.26% completeness. Genome annotation revealed 5,833 genes, including 5,756 protein-coding sequences and numerous non-coding RNAs. It also harbors 4 different plasmids. Importantly, we identified 25 genomic islands harboring mobile elements and hypothetical proteins, highlighting the strain's dynamic genome evolution. The genome encodes a diverse array of virulence factors linked to insecticidal activity. Notable genes include <i>cry22A</i> and <i>vip3A</i> homologs, multiple <i>bmp1</i>-like metalloproteases, <i>enhancin</i>, <i>cytK</i>, and <i>chiA</i>, as well as various chitinases and serine proteases. The co-occurrence of chromosomal and plasmid-encoded virulence factors suggests modular acquisition mechanisms. Secondary metabolite biosynthetic clusters, such as those for petrobactin, bacillibactin, thuricin CD, and other novel RiPPs and NRPs, were detected, supporting the strain's potential in biological control. Phylogenetic analysis positioned JSd1 within the <i>B. cereus</i> sensu lato group, forming a highly supported clade with <i>B. thuringiensis</i> serovar konkukian and <i>B. anthracis</i>. Comparative genomic and pan-genome analyses revealed substantial genomic diversity among <i>B. thuringiensis</i> strains. The strain's genome contains 2,237 core genes and a large accessory genome, reflecting its ecological adaptability. Our findings suggest that <i>B. thuringiensis</i> JSd1 is a promising candidate for development as a biopesticide targeting insect pests in Bangladeshi agriculture. The comprehensive genomic insights lay the groundwork for further functional validation and field applications, contributing to sustainable pest management strategies in the region.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261475762"},"PeriodicalIF":2.0,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13487139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148787803","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":"ArchetypeShift: An R Package Integrating KEGG-Informed Pathway Analysis and IPA-Derived Functional Predictions for Validation of Single-Cell Archetypes.","authors":"Adam P Wilson, Hala Chaaban, Kathryn Y Burge","doi":"10.1177/11779322261477368","DOIUrl":"10.1177/11779322261477368","url":null,"abstract":"<p><p>Functional archetype analysis of single-cell RNA-sequencing (scRNA-seq) data is important because clustering of cell types is often nuanced and inexact. Intermediate phenotypes exist that are difficult to account for in these analyses, particularly in the setting of infant development. Further, different cell types work together to achieve biological functions, thereby broadly supporting tissue function at homeostasis and through environmental challenges via phenotypic plasticity. Currently, the process of assigning archetypes to cell clusters is labor-intensive because annotation requires manual upload of expression data to multiple programs. ArchetypeShift is an R-based pipeline that integrates existing archetypal analysis methods with annotation by Ingenuity Pathway Analysis (IPA) and Kyoto Encyclopedia of Genes and Genomes (KEGG), graphics visualization, and trajectory analysis for scRNA-seq data. Generating IPA- and/or KEGG-informed dot plots, UMAPs (uniform manifold approximation and projections) of archetype weights, archetype maps, heatmaps defining the top genes for each archetype program, and trajectory analysis graphics, ArchetypeShift streamlines the biological interpretation of archetype programs within a unified and efficient analytical framework. The source code for ArchetypeShift is available on GitHub (https://github.com/Neo-NEC-Lab/ArchetypeShift).</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261477368"},"PeriodicalIF":2.0,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13462623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148720489","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":"A Comprehensive In-Silico Pipeline for the Discovery of Non-toxic, Stable Antimicrobial Peptides From Databases for Targeting Multi-Drug Resistant <i>K. pneumoniae</i>.","authors":"Pranab Dev Sharma, Abdullah Al Noman, Md Al Amin Talukder, Md Jakaria Parvez, Md Al Hafiz, Bratakatha Nath, Himanshu Sharma","doi":"10.1177/11779322261475821","DOIUrl":"10.1177/11779322261475821","url":null,"abstract":"<p><p>The rapid emergence of multidrug-resistant <i>Klebsiella pneumoniae</i> has significantly reduced the effectiveness of conventional antibiotics, highlighting the need for alternative therapeutic strategies. This study employed a comprehensive in silico pipeline to identify antimicrobial peptides (AMPs) targeting the essential DNA replication initiator protein DnaA. A total of 28,361 peptide sequences were collected from publicly available AMP databases and sequentially filtered based on peptide length, net charge, GRAVY score, instability index, antimicrobial activity, toxicity, hemolytic potential, aggregation propensity, sequence similarity and favorable amphipathic properties. Four peptides satisfied all selection criteria and were subjected to structural prediction, membrane-binding analysis, protein-DNA docking, protein-peptide docking, and Normal Mode Analysis. Protein-DNA docking identified the functional DNA-binding residues of DnaA, while peptide docking demonstrated that all four peptides interacted within this region. Peptide 3 exhibited the strongest predicted interaction, with a binding energy of -61.8±5.1, a buried surface area of 1151.7±30.8 Ų, and seven hydrogen bonds with key DnaA residues. Normal Mode Analysis further supported the structural stability of the peptide-protein complexes. These findings identify four promising AMP candidates targeting DnaA and provide a computational framework for peptide prioritization against multidrug-resistant <i>K. pneumoniae</i>. However, the proposed interactions remain computational predictions and require experimental validation.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"20 ","pages":"11779322261475821"},"PeriodicalIF":2.0,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148696987","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}