Evolutionary Bioinformatics最新文献

{"title":"Comprehensive In Silico Analysis of the CXCL12, C55Y Mutation Reveals Structural and Functional Disruption in CXCR4/CXCR7 Signaling.","authors":"Shah Kamal, Najeeb Ullah, Yanjuan Wang, Chen Qin, Ruilin He, Habib Ullah, Mariam Ahmed Mujtaba, Amanullah Amanullah, Kashif Ali Khan, Mohammad Amjad Kamal, Wenji Li","doi":"10.1177/11769343261471072","DOIUrl":"10.1177/11769343261471072","url":null,"abstract":"<p><strong>Background: </strong>CXCL12 is a critical chemokine involved in immune cell trafficking and tumor metastasis through its interaction with CXCR4 and CXCR7. The C55Y mutation in CXCL12 is hypothesized to disrupt its structure and function. Unlike previously reported CXCL12 mutations that affect transcriptional regulation or single-receptor binding, C55Y targets a conserved cysteine residue essential for a structural disulfide bridge, potentially inducing unique global destabilization. This study investigates the molecular consequences of the C55Y mutation using computational tools.</p><p><strong>Objectives: </strong>This study aimed to evaluate the structural and functional impact of the C55Y mutation in CXCL12, particularly its interactions with CXCR4 and CXCR7, and its relevance to prostate cancer pathogenesis.</p><p><strong>Methods: </strong>Molecular dynamics simulations (MDS), evolutionary conservation analysis, and molecular docking with CXCR4 and CXCR7 receptors were performed to assess the impact of the C55Y mutation. Tools such as I-TASSER, Meta-SNP, and PolyPhen-2 were used to analyze structural stability, while HDOCK and Schrödinger simulations assessed receptor binding. RMSD and RMSF calculations were used to evaluate protein dynamics.</p><p><strong>Results: </strong>The C55Y mutation induces significant structural instability in CXCL12, with increased RMSD and altered secondary structure. Molecular dynamics simulation further demonstrated the stability of the complexes through RMSD, RMSF, hydrogen bond, and Radius of Gyration (RoG) analyses, where the normal complexes exhibited comparatively stable structural compactness during the simulation period. Docking studies showed reduced binding affinity to CXCR4 and CXCR7, indicating disrupted receptor interactions. Notably, this dual-receptor binding loss distinguishes C55Y from other mutations that typically impair only CXCR4 signaling. These findings suggest that the mutation impairs CXCL12's function in prostate cancer, metastasis of prostate cancer, and immune response.</p><p><strong>Conclusion: </strong>The C55Y mutation in CXCL12 disrupts its structural integrity and receptor binding, uniquely compromising both the CXCR4 and CXCR7 pathways. This highlights its potential role in prostate cancer progression through mechanisms distinct from previously characterized CXCL12 variants. This study provides insights into the molecular mechanisms of CXCL12-mediated signaling and its implications for future therapeutic strategies targeting chemokine signaling to inhibit prostate cancer.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343261471072"},"PeriodicalIF":1.6,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13443258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteins Rich in Prime Mass Residues and Their Role in Cell Biology.","authors":"Matthew Wright, Kevin M Downard","doi":"10.1177/11769343261453240","DOIUrl":"10.1177/11769343261453240","url":null,"abstract":"<p><strong>Background: </strong>Prime mass amino acids residues, assigned based upon the nominal mass of their repeating structure in peptides and proteins, have been found to occur more often than by chance. These 9 such residues are predominantly hydrophobic in character and thus play an important role in protein stability and folding. This study investigates their prevalence in human proteins and the function of such proteins.</p><p><strong>Objectives: </strong>To identify human proteins rich in the prime mass residues and assess their functions.</p><p><strong>Results: </strong>Prime-rich proteins are found to proliferate among those important to transcriptional events, cell adhesion, and the formation of cell surface membranes. Eighteen prime-rich proteins are identified that are abundant in 3 or 4 prime residues, the latter notably contain alanine, cysteine, histidine or threonine, and proline. The percentage of prime residues in these prime-rich proteins exceeds one-half (>50%) of all residues in many cases, and these residues are found to be concentrated in particular regions of the protein.</p><p><strong>Conclusion: </strong>Proteins rich in prime residues are found to play an important role in biological events important to cellular life. Such prime residues represent those associated with the highest hydrophobicity, and those essential to protein folding and function. Many prime residues were recruited early into the genetic code according to the composition of the last universal common ancestor (LUCA) proteins. Consideration is given to whether the formation of evolution of these proteins is predicated by the primality of the residues or their physicochemical and structural properties. This remains an open question and awaits further inquiry and debate.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343261453240"},"PeriodicalIF":1.6,"publicationDate":"2026-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13198640/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148018836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Feature Selection-Based Machine Learning and Deep Learning Framework for Biomarker Prediction From RNA-seq Data During Dengue Fever to Severe Dengue Progression.","authors":"Srilekha Anumulapuri, Jhansi Venkata Nagamani Josyula, Agiesh Kumar Balakrishna Pillai, Srinivasa Rao Mutheneni","doi":"10.1177/11769343261449312","DOIUrl":"10.1177/11769343261449312","url":null,"abstract":"<p><strong>Background: </strong>Severe dengue (SD) represents a life-threatening progression of dengue virus infection. Early identification of patients at risk of transitioning from dengue fever (DF) to SD remains a major clinical challenge. Unraveling the transcriptomic changes underlying this progression may aid in developing timely therapeutic interventions.</p><p><strong>Methods: </strong>RNA-seq datasets comprising 103 samples (62 SD and 41 DF) were retrieved from the GEO repository. Following normalization using DESeq2, differentially expressed genes (DEGs) were identified between the 2 disease stages. Functional enrichment analysis was performed to uncover dysregulated biological processes. A hybrid computational framework combining classical machine learning (Logistic Regression, Support Vector Machine, and Random Forest) and deep learning models (Artificial Neural Network, Convolutional Neural Network, and Transformer-based architectures) were applied to classify SD and DF samples. Model performance was evaluated using ROC-AUC and balanced accuracy metrics.</p><p><strong>Results: </strong>Differential expression analysis identified 55 significantly dysregulated genes distinguishing severe dengue from dengue fever. These genes were enriched in pathways related to metal ion homeostasis, platelet signaling, ferroptosis, and oxidative stress. Among multiple machine learning and deep learning models, the Transformer-CNN achieved the best performance (test AUC = 0.85; balanced accuracy = 0.89). SHAP-based interpretation highlighted <i>ILDR2, TCP1, HNRNPUL1, SEC14L5, ATP2C2, LOXL3, ACVRL1, STEAP3</i>, and <i>ST8SSIA5</i> as key discriminative features. Integrated network analyses further implicated coordinated regulation of iron metabolism, calcium signaling, and platelet dysfunction in severe dengue.</p><p><strong>Conclusion: </strong>This study integrates RNA-seq and hybrid Artificial Intelligence modeling to identify transcriptomic signatures associated with dengue severity. The study highlights candidate genes and pathways that provide a hypothesis-generating foundation; further increasing the sample size and experimental validation will support early risk stratification in severe dengue.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343261449312"},"PeriodicalIF":1.6,"publicationDate":"2026-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13167281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional Annotation and Molecular Characterization of a Hypothetical Protein From <i>Mycobacterium leprae</i> Through <i>In Silico</i> Approaches: A Potential Therapeutic Target.","authors":"Tasnim Hosen Tanha, Shoaib Saikat, Rabiul Hasan, Md Mehedi Hasan Yeamin, Rehana Parvin, Md Imtiaz, Md Hasib","doi":"10.1177/11769343261438525","DOIUrl":"10.1177/11769343261438525","url":null,"abstract":"<p><strong>Objective: </strong><i>Mycobacterium leprae</i> causes leprosy, an infectious disease that has persisted over centuries and is still an issue in public health in many nations. Diverse bioinformatics techniques have been effectively employed to annotate the functions of hypothetical proteins (HPs) originating from different pathogenic bacteria. The objective of the current research was to elucidate the functions of an HP obtained from <i>M. leprae</i>.</p><p><strong>Methods: </strong>A variety of <i>in silico</i> tools were utilized to make predictions regarding the structure and function of this protein. To identify homologous proteins, the BLASTp program was used to search for sequence similarity across the available biological databases. Additionally, using the proper bioinformatics methods, a number of properties were determined, including physicochemical characteristics, subcellular localization, phylogenetic analysis, functional annotation, pathway analysis, protein-protein interaction, secondary and tertiary structure determination, active site detection, quality assessment analysis, molecular docking, pharmacokinetic and toxicity profiling, and further molecular dynamics simulations.</p><p><strong>Results: </strong>The HP exhibited putative biological activity associated with a conserved functional domain, the CT_C_D superfamily domain. The allophanate hydrolase activity of the chosen HP was predicted by the functional annotation. Pathway analysis demonstrated the protein's involvement in cellular and metabolic processes. Numerous functional partners that play a crucial role in bacterial survival were identified through the chosen HP's protein-protein interactions. Furthermore, active site prediction and molecular docking analysis of the HP with ligands indicated that it could be a therapeutic target for <i>M. leprae.</i> ADMET analysis indicated that the selected compound has favorable bioavailability, drug-likeness, and safety. The stability of these complexes was verified by molecular dynamics simulations, which suggests they have therapeutic potential.</p><p><strong>Conclusion: </strong>This study emphasizes the effectiveness of <i>in silico</i> methods in predicting the biological functions of HP and generating hypotheses for potential therapeutic targets.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343261438525"},"PeriodicalIF":1.6,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13065284/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147678250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolutionary Bioinformatics Expands its Breadth.","authors":"Gustavo Caetano-Anollés","doi":"10.1177/11769343261433786","DOIUrl":"10.1177/11769343261433786","url":null,"abstract":"","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343261433786"},"PeriodicalIF":1.6,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13009746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene Expression Underlying Teloblast Formation in Leech (Annelida: Hirudinae).","authors":"Samuel Hsiao, Naim Saglam, Ralph Saunders, Daniel H Shain","doi":"10.1177/11769343251412523","DOIUrl":"10.1177/11769343251412523","url":null,"abstract":"<p><strong>Objective: </strong>Species of glossiphoniid leech provide model systems for exploring fundamental questions in evolutionary and developmental biology. In this study, we took advantage of large embryonic cells and stereotypical cleavage patterns in the leech, <i>Helobdella austinensis</i>, to identify genes associated with the births of teloblasts and their lineage specifications.</p><p><strong>Methods: </strong>Using staged embryos and pools of dissected precursor cells and teloblasts, a systematic computational comparison of staged and cell type-specific transcriptomic data was employed to identify unique gene sets associated with mesodermal (M), neuroectodermal (N) and teloblast (M + N) cell formation.</p><p><strong>Results and conclusions: </strong>Our predicted candidate genes comprised sets of nucleic acid binding factors as anticipated but displayed little similarity with differentiation factors in other metazoans (eg, mammals, cnidarians), suggesting that stem cell/lineage induction processes have diverged across the Animalia and may reflect fundamentally different modes of embryonic development.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343251412523"},"PeriodicalIF":1.6,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12949301/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147328009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Optimization of CRISPR-Cas13a sgRNAs Targeting the SARS-CoV-2 Spike Gene for SHERLOCK-Based Diagnostics.","authors":"Maryam Ahmadzadeh, Fatemeh Akbarian, Mohammad Hossein Sanati, Hanieh Motaharirad, Fatemeh Farrokhi","doi":"10.1177/11769343251414318","DOIUrl":"10.1177/11769343251414318","url":null,"abstract":"<p><strong>Background: </strong>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered a global health crisis, emphasizing the urgent need for accurate and rapid diagnostic tools. Modern molecular biology technologies, including CRISPR-Cas systems, provide highly efficient strategies for viral detection. Bioinformatic pipelines are essential for identifying conserved genomic regions and enabling rational single-guide RNA (sgRNA) design.</p><p><strong>Methods: </strong>This study aimed to design specific sgRNAs targeting the spike gene of SARS-CoV-2 isolates from Iranian patients using the SHERLOCK diagnostic platform. Complete genomes of the RefSeq virus and 470 SARS-CoV-2 isolates, representing all variants of concern (VOCs) detected in Iran, were retrieved from the NCBI and GISAID databases. Multiple sequence alignment with ClustalW identified conserved sequences within the receptor-binding domain (RBD) that differ from the RBD of SARS-CoV and MERS-CoV RefSeq genomes. Based on these regions, sgRNAs and isothermal amplification primers were designed using ADAPT, OLIGO7, and the UCSC Genome Browser to maximize diagnostic sensitivity and specificity. Secondary and tertiary structures of sgRNA-target complexes were analyzed via RNAfold and RNAup to select the most efficient sgRNA-amplicon combination.</p><p><strong>Results: </strong>Twenty-two-nucleotide sgRNA candidates were initially selected based on sequence alignment, showing high similarity to the SARS-CoV-2 RefSeq and low homology to SARS-CoV and MERS-CoV genomes. Analyses of secondary structures, RNA-RNA interactions, and free energy identified 6 sgRNAs with favorable 2-dimensional conformations and strong interaction profiles. Among these, the sgRNA1-Amplicon2 sequence exhibited the most stable 3-dimensional structure and a molecular docking score of -309.67, indicating high sensitivity and specificity for viral detection.</p><p><strong>Conclusion: </strong>This study successfully designed an sgRNA with high sensitivity and specificity for rapid SARS-CoV-2 detection using the CRISPR-Cas13a system, informed by genomic analysis of Iranian isolates. The proposed approach provides an efficient framework for the rapid design and deployment of CRISPR-based diagnostic tools applicable to diverse viral pathogens.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343251414318"},"PeriodicalIF":1.5,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12905083/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146203711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Evolution-Inspired Algorithm for Intrusion Detection in Bioinformatics Systems.","authors":"Mehtab Alam, Chandra Kanta Samal, Ashraf Ali, Abdullah Alourani","doi":"10.1177/11769343251412695","DOIUrl":"10.1177/11769343251412695","url":null,"abstract":"<p><p>The increasing integration of bioinformatics with cloud infrastructure, artificial intelligence, and real-time data analytics has introduced unprecedented cybersecurity challenges. Sensitive genomic and clinical data, when exposed to evolving cyber threats such as data exfiltration, injection attacks, and model poisoning, require more adaptive and resilient defense mechanisms. This research presents an <b>Evolution-Inspired Cyber Defense Architecture (EICDA)</b> that mimics biological immune and evolutionary processes to detect, respond to, and adapt against cyber intrusions targeting bioinformatics-informed systems. The proposed architecture employs a genetic algorithm-based detection core combined with reinforcement-driven adaptation, enabling real-time learning and decision reconfiguration. EICDA is validated on multiple datasets including NSL-KDD, CICIDS2017, and a simulated genomic API log environment, achieving a detection accuracy of 96.2%, a false positive rate of 2.8%, and sub-150 ms response latency. Comparative analyses with SVM, Random Forest, CNN, and traditional AIS highlight EICDA's superior adaptability and robustness. The framework also demonstrates resilience under threat drift conditions, positioning it as a viable defense model for next-generation bioinformatics platforms. This research provides a novel contribution by fusing evolutionary intelligence with cybersecurity to protect critical biomedical infrastructures.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"22 ","pages":"11769343251412695"},"PeriodicalIF":1.5,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12861380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Genome Analysis of 25 Sri Lankan <i>Leptospir</i>a Isolates Outer Membrane Receptors That Interact With Human TLR2.","authors":"Chamila Kappagoda, Indika Senavirathna, Dinesha Jayasundara, Janith Warnasekara, Thilini Agampodi, Suneth Agampodi","doi":"10.1177/11769343251389782","DOIUrl":"10.1177/11769343251389782","url":null,"abstract":"<p><strong>Background: </strong>During leptospiral infection, the host innate immune response is initiated through recognition of pathogen-associated molecular patterns (PAMPs) by Toll-like receptor 2 (TLR2). Among these PAMPs, LipL32, Loa22, Lsa21, and lipopolysaccharide biosynthesis genes, are of particular interest.</p><p><strong>Objective: </strong>This study aimed to investigate these molecules' genetic variability and evolutionary conservation in recently isolated clinical <i>Leptospira</i> strains from Sri Lanka.</p><p><strong>Results: </strong>We analyzed the whole-genome sequences of 25 clinical <i>Leptospira</i> isolates obtained from patients across Sri Lanka, sequenced using long-read technology and annotated using a standardized pipeline. Genes encoding LipL32, Loa22, Lsa21, and enzymes within the lipopolysaccharide biosynthesis locus were extracted and analyzed for phylogenetic relationships and sequence variation. LipL32 and Loa22 were highly conserved across all isolates, with only a single amino acid substitution observed in each. In contrast, genes associated with lipopolysaccharide biosynthesis, specifically those encoding glycosyl transferase and a sodium-dependent anion transporter, exhibited notable genetic variation, including multiple single nucleotide polymorphisms leading to amino acid changes. The Lsa21 gene was present only in <i>Leptospira interrogans</i> strains and showed no protein-level variation. <i>Leptospira borgpetersenii</i> isolates demonstrated strong conservation across all gene targets at both nucleotide and protein levels.</p><p><strong>Conclusion: </strong>Our findings highlight the high conservation of LipL32 and Loa22, reinforcing their potential as stable targets for molecular diagnostics and serological assays. In contrast, the variability observed in lipopolysaccharide biosynthesis genes suggests a possible role in immune evasion or adaptation, warranting further functional investigation. The restricted presence of Lsa21 in specific species also raises questions about its contribution to pathogenicity.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"21 ","pages":"11769343251389782"},"PeriodicalIF":1.5,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12612534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145543801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural and Functional Characterization of a Putative Type VI Secretion System Protein in <i>Cronobacter sakazakii</i> as a Potential Therapeutic Target: A Computational Study.","authors":"Nurun Nahar Akter, Md Moin Uddin, Nesar Uddin, Israt Jahan Asha, Md Soyeb Uddin, Md Arju Hossain, Fahadul Alam, Siratul Kubra Shifat, Md Abu Zihad, Md Habibur Rahman","doi":"10.1177/11769343251327660","DOIUrl":"10.1177/11769343251327660","url":null,"abstract":"<p><strong>Background: </strong><i>Cronobacter sakazakii</i>, a foodborne pathogen with a fatality rate of 33%, is a rod-shaped, Gram-negative, non-spore-forming bacterium responsible for causing meningitis, bacteremia, and necrotizing enterocolitis. Despite many unknown functions of hypothetical proteins in bacterial genomes, bioinformatic techniques have successfully annotated their roles in various pathogens.</p><p><strong>Objectives: </strong>The aim of this investigation is to identify and annotate the structural and functional properties of a hypothetical protein (HP) from <i>Cronobacter sakazakii</i> 7G strain (accession no. WP_004386962.1, 277 residues) using computational tools.</p><p><strong>Methods: </strong>Multiple bioinformatic tools were used to identify the homologous protein and to construct and validate its 3D structure. A 3D model was generated using SWISS-MODEL and validated using tools, developing a reliable 3D structure. The STRING and CASTp servers provided information on protein-protein interactions and active sites, identifying functional partners.</p><p><strong>Results: </strong>The putative protein was soluble, stable, and localized in the cytoplasmic membranes, indicating its biological activity. Functional annotation identified TagJ (HsiE1) within the protein, a member of the ImpE superfamily involved in the transport of toxins and a part of the bacterial type VI secretion system (T6SS). The 3-dimensional structure of this protein was validated through molecular docking involving 6 different compounds. Among these, ceforanide demonstrated the strongest binding scores, -7.5 kcal/mol for the hypothetical protein and -7.2 kcal/mol for its main template protein (PDB ID: 4UQX.1).</p><p><strong>Conclusion: </strong>Comparative genomics study suggests that the protein found in <i>C. sakazakii</i> may be a viable therapeutic target because it seems distinctive and different from human proteins. The results of multiple sequence alignment (MSA) and molecular docking supported HP's potential involvement as a T6SS. These in silico results represent that the examined HP could be valuable for studying <i>C. sakazakii</i> infections and creating medicines to treat <i>C. sakazakii</i>-mediated disorders.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"21 ","pages":"11769343251327660"},"PeriodicalIF":1.7,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143765656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}