Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794;
Proc Natl Acad Sci U S A. 2019 Mar 26;116(13):5902-5907. doi: 10.1073/pnas.1812149116. Epub 2019 Mar 8.
How does a biomolecular machine achieve high speed at high efficiency? We explore optimization principles using a simple two-state dynamical model. With this model, we establish physical principles-such as the optimal way to distribute free-energy changes and barriers across the machine cycle-and connect them to biological mechanisms. We find that a machine can achieve high speed without sacrificing efficiency by varying its conformational free energy to directly link the downhill, chemical energy to the uphill, mechanical work and by splitting a large work step into more numerous, smaller substeps. Experimental evidence suggests that these mechanisms are commonly used by biomolecular machines. This model is useful for exploring questions of evolution and optimization in molecular machines.
生物分子机器如何实现高速高效?我们使用简单的两态动力学模型来探索优化原则。通过该模型,我们建立了物理原理,例如在机器循环中分配自由能变化和障碍的最佳方式,并将其与生物机制联系起来。我们发现,通过改变构象自由能,直接将下坡的化学能与上坡的机械功相连接,并将一个大的工作步骤分解为更多的较小的子步骤,机器可以在不牺牲效率的情况下实现高速。实验证据表明,这些机制在生物分子机器中被广泛使用。该模型对于探索分子机器中的进化和优化问题非常有用。