论文标题
动力学校对的帕累托最佳前沿
Pareto optimal fronts of kinetic proofreading
论文作者
论文摘要
从化学分子池中选择合适的底物时，诸如DNA复制，RNA转录和蛋白质翻译等生物学过程表现出显着的速度和准确性。该结果是通过耗散化学能的非平衡反应获得的。人们普遍认识到，速度，错误和耗散这些系统的耗散之间必须进行权衡。在本文中，我们使用数学优化理论中的工具量化了速度，错误和耗散之间的权衡。我们表征了两个生物误差校正范式模型的帕累托最佳前端：Hopfield的动力学校对模型和核糖体模型。我们发现，具有更多校对步骤的错误校正过程的特征是更好的权衡。此外，我们确定了帕累托阵线上速度，准确性和耗散之间的比例关系。
Biological processes such as DNA replication, RNA transcription, and protein translation show remarkable speed and accuracy in selecting the right substrate from pools of chemically identical molecules. This result is obtained by nonequilibrium reactions that dissipate chemical energy. It is widely recognized that there must be a trade-off between speed, error, and dissipation characterizing these systems. In this paper, we quantify the trade-off between speed, error, and dissipation using tools from mathematical optimization theory. We characterize the Pareto optimal front for two paradigmatic models of biological error correction: Hopfield's kinetic proofreading model and a ribosome model. We find that error correction processes with more proofreading steps are characterized by better trade-offs. Furthermore, we identify scaling relations between speed, accuracy, and dissipation on the Pareto front.
