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<p>Enhancing protein stability while maintaining activity is a long-standing challenge in protein engineering, as modifications that benefit one property often compromise another. In this study, we leveraged a computational design strategy, CamSol Combination, to make a first step to improve the stability of purple acid phosphatase (PAP), a metalloprotein known for its distinctive pink color. PAP serves as a challenging model for engineering due to its complex redox-active site and the incorporation of iron ions critical to its function. Five mutations were introduced—H22R, A24P, F54P, H197P, and T208R—targeted to enhance thermal stability, as suggested by the computational design pipeline, while avoiding key functional regions. Experimental validation confirmed the choice of mutations with a 5&#xa0;°C increase in thermal stability and retained enzymatic activity across a slightly expanded pH range. The mutations introduced subtle shifts in the enzyme’s spectral and redox behavior, consistent with a lower energy of the oxidized state, and with dynamic light scattering data suggesting low aggregation. These results highlight the potential of computational approaches like the CamSol Combination to streamline protein engineering by enabling multi-trait optimization.</p>

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Modifying recombinant purple acid phosphatase using computational design

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月12日

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  • Aishwarya Venkatramani,
  • Montader Ali,
  • Olga Predeina,
  • Jennifer C. Molloy,
  • Pietro Sormanni,
  • Elizabeth A. H. Hall

摘要

Enhancing protein stability while maintaining activity is a long-standing challenge in protein engineering, as modifications that benefit one property often compromise another. In this study, we leveraged a computational design strategy, CamSol Combination, to make a first step to improve the stability of purple acid phosphatase (PAP), a metalloprotein known for its distinctive pink color. PAP serves as a challenging model for engineering due to its complex redox-active site and the incorporation of iron ions critical to its function. Five mutations were introduced—H22R, A24P, F54P, H197P, and T208R—targeted to enhance thermal stability, as suggested by the computational design pipeline, while avoiding key functional regions. Experimental validation confirmed the choice of mutations with a 5 °C increase in thermal stability and retained enzymatic activity across a slightly expanded pH range. The mutations introduced subtle shifts in the enzyme’s spectral and redox behavior, consistent with a lower energy of the oxidized state, and with dynamic light scattering data suggesting low aggregation. These results highlight the potential of computational approaches like the CamSol Combination to streamline protein engineering by enabling multi-trait optimization.