Netz Roland R, Eaton William A
Fachbereich Physik, Freie Universität Berlin, 14195 Berlin, Germany;
Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD 20892
Proc Natl Acad Sci U S A. 2021 Feb 9;118(6). doi: 10.1073/pnas.2022753118.
There has been much success recently in theoretically simulating parts of complex biological systems on the molecular level, with the goal of first-principles modeling of whole cells. However, there is the question of whether such simulations can be performed because of the enormous complexity of cells. We establish approximate equations to estimate computation times required to simulate highly simplified models of cells by either molecular dynamics calculations or by solving molecular kinetic equations. Our equations place limits on the complexity of cells that can be theoretically understood with these two methods and provide a first step in developing what can be considered biological uncertainty relations for molecular models of cells. While a molecular kinetics description of the genetically simplest bacterial cell may indeed soon be possible, neither theoretical description for a multicellular system, such as the human brain, will be possible for many decades and may never be possible even with quantum computing.
最近在分子水平上对复杂生物系统的部分进行理论模拟方面取得了很大成功，目标是对整个细胞进行第一性原理建模。然而，由于细胞的巨大复杂性，存在这样的模拟是否能够进行的问题。我们建立了近似方程，以估计通过分子动力学计算或求解分子动力学方程来模拟高度简化的细胞模型所需的计算时间。我们的方程对能用这两种方法从理论上理解的细胞复杂性进行了限制，并为开发可被视为细胞分子模型的生物不确定性关系迈出了第一步。虽然对遗传上最简单的细菌细胞进行分子动力学描述可能确实很快就能实现，但对于多细胞系统，如人类大脑，在几十年内都不可能有理论描述，甚至借助量子计算也可能永远无法实现。
