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<p><i>Haemophilus influenza</i>, a major contributor to respiratory infections such as pneumonia, meningitis, sinusitis, chronic bronchitis, and acute otitis, poses a significant public health challenge, driven by rising antibiotic resistance particularly among the non-typeable <i>H. influenza</i> (NTHi) strains given their ability to evade immune surveillance. To address this, we employed a comprehensive immunoinformatics pipeline integrated with extensive pan-genome analysis of 59 strains of <i>H. influenzae</i> to design a novel multiepitope vaccine (MEV) candidate targeting most virulent and clinically significant proteins. Key surface exposed and virulence associated proteins, including Protein E, PilA, Protein D, P4, TolC, YadA, and HifC were prioritized based on their roles in bacterial adhesion, immune evasion, biofilm formation, and nutrient acquisition. Advanced&#xa0;in silico epitope prediction and verification strategies were utilized to map highly immunogenic regions across these proteins, followed by codon optimization to enhance expression efficiency in human systems. To further stabilize the vaccine construct, we performed disulfide engineering to enhance structural integrity and resilience. Comprehensive validation through in&#xa0;silico immune simulations, molecular dynamics (MD) simulations and binding free energy calculations confirmed the structural stability, immunogenic potential, and strong receptor affinity of the MEV candidate. Phylogenetic and virulence factor analysis further corroborated the broad coverage of the pathogenic relevance of the selected proteins. Together, our integrative approach presents a robust pipeline for rational vaccine design, offering a promising avenue toward combating multidrug resistant and immune evasive <i>H. influenza</i> strains.</p>

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Molecular insights into pangenome localization and constructs design for Hemophilus influenza vaccine

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

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  • Naila Zaman,
  • Kainat Gul,
  • Kinza Khurram,
  • Syed Sikander Azam

摘要

Haemophilus influenza, a major contributor to respiratory infections such as pneumonia, meningitis, sinusitis, chronic bronchitis, and acute otitis, poses a significant public health challenge, driven by rising antibiotic resistance particularly among the non-typeable H. influenza (NTHi) strains given their ability to evade immune surveillance. To address this, we employed a comprehensive immunoinformatics pipeline integrated with extensive pan-genome analysis of 59 strains of H. influenzae to design a novel multiepitope vaccine (MEV) candidate targeting most virulent and clinically significant proteins. Key surface exposed and virulence associated proteins, including Protein E, PilA, Protein D, P4, TolC, YadA, and HifC were prioritized based on their roles in bacterial adhesion, immune evasion, biofilm formation, and nutrient acquisition. Advanced in silico epitope prediction and verification strategies were utilized to map highly immunogenic regions across these proteins, followed by codon optimization to enhance expression efficiency in human systems. To further stabilize the vaccine construct, we performed disulfide engineering to enhance structural integrity and resilience. Comprehensive validation through in silico immune simulations, molecular dynamics (MD) simulations and binding free energy calculations confirmed the structural stability, immunogenic potential, and strong receptor affinity of the MEV candidate. Phylogenetic and virulence factor analysis further corroborated the broad coverage of the pathogenic relevance of the selected proteins. Together, our integrative approach presents a robust pipeline for rational vaccine design, offering a promising avenue toward combating multidrug resistant and immune evasive H. influenza strains.