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<p>Fibrinolytic drugs, particularly streptokinase (SK), are crucial for the management of blood clotting disorders. However, SK’s bacterial origin triggers immune responses that generate neutralizing antibodies, diminishing its effectiveness. This study aimed to identify and eliminate B-cell epitopes in SK to reduce its immunogenicity through targeted point mutations. By utilizing advanced in silico tools, we predicted the SK structure and identified both linear and conformational B-cell epitopes. Hot spot residues within these epitopes were identified using a combination of epitope prediction algorithms, molecular dynamics and docking simulations, conservancy analysis, and propensity scales. Our innovative approach suggested key antigenic residues E53, D174, and S258 that were strategically mutated to minimize immunogenicity. Immuno-informatics tools indicated that the modified SK could exhibit a significantly reduced immunogenic profile. Molecular dynamics simulations supported the structural integrity of the modified SK, and docking studies suggested its preserved interaction potential with plasminogen. Our results propose that the mutein E53M-D174M-S258W could reduce the immunogenic response, thus improving its therapeutic potential.</p>

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Epitope mapping strategies for immunogenicity mitigation in streptokinase therapeutics: an in-silico study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月29日

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  • Mohammad Soroosh Hajizade,
  • Mohammad Reza Rahbar,
  • Maryam Kabiri,
  • Mahdie Hajimonfarednejad,
  • Mohammad Javad Raee

摘要

Fibrinolytic drugs, particularly streptokinase (SK), are crucial for the management of blood clotting disorders. However, SK’s bacterial origin triggers immune responses that generate neutralizing antibodies, diminishing its effectiveness. This study aimed to identify and eliminate B-cell epitopes in SK to reduce its immunogenicity through targeted point mutations. By utilizing advanced in silico tools, we predicted the SK structure and identified both linear and conformational B-cell epitopes. Hot spot residues within these epitopes were identified using a combination of epitope prediction algorithms, molecular dynamics and docking simulations, conservancy analysis, and propensity scales. Our innovative approach suggested key antigenic residues E53, D174, and S258 that were strategically mutated to minimize immunogenicity. Immuno-informatics tools indicated that the modified SK could exhibit a significantly reduced immunogenic profile. Molecular dynamics simulations supported the structural integrity of the modified SK, and docking studies suggested its preserved interaction potential with plasminogen. Our results propose that the mutein E53M-D174M-S258W could reduce the immunogenic response, thus improving its therapeutic potential.