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<p>DNA polymerases (DNAPs) catalyze DNA replication by coordinating the polymerase and exonuclease activities to enhance the fidelity through exonuclease proofreading at the cost of additional dNTP consumption. Whether and how DNAPs achieve an optimal or even a robust optimal fidelity-cost trade-off remains elusive. By building a ladder-like model to describe the synthesis-excision kinetics and adopting an objective function <i>Q</i> to explicitly quantify the trade-off, we revealed by <i>Q</i> maximization that DNAPs, having long-range mismatch sensing and complex excision modes, could fine-tune key parameters that are intrinsic to excision to achieve an optimal fidelity-cost trade-off, which is robust to large fluctuations in synthesis-specific parameters. Part of the predictions on the key parameters were validated by high-resolution single-molecule assays on two DNAPs (KF and gp5). Our work reveals a new and potentially universal optimization strategy of DNAPs, and also offers a new perspective to understand the architecture of molecular machines with distinctly separated multiple domains, i.e., the structural modularity may enable robust functional optimization of the machine if part of its domains are subject to fluctuating parameters.</p>

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Optimal fidelity-cost trade-off in DNA polymerase proofreading

  • 期刊论文

  • 发表日期：

    2026年6月26日

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  • Qi Jia,
  • Qiushi Li,
  • Hang Fu,
  • Hao Wang,
  • Dongfei Ma,
  • Ming Li,
  • Ying Lu,
  • Ming Li

摘要

DNA polymerases (DNAPs) catalyze DNA replication by coordinating the polymerase and exonuclease activities to enhance the fidelity through exonuclease proofreading at the cost of additional dNTP consumption. Whether and how DNAPs achieve an optimal or even a robust optimal fidelity-cost trade-off remains elusive. By building a ladder-like model to describe the synthesis-excision kinetics and adopting an objective function Q to explicitly quantify the trade-off, we revealed by Q maximization that DNAPs, having long-range mismatch sensing and complex excision modes, could fine-tune key parameters that are intrinsic to excision to achieve an optimal fidelity-cost trade-off, which is robust to large fluctuations in synthesis-specific parameters. Part of the predictions on the key parameters were validated by high-resolution single-molecule assays on two DNAPs (KF and gp5). Our work reveals a new and potentially universal optimization strategy of DNAPs, and also offers a new perspective to understand the architecture of molecular machines with distinctly separated multiple domains, i.e., the structural modularity may enable robust functional optimization of the machine if part of its domains are subject to fluctuating parameters.