标题： 细胞水平的量子信息处理。 欧几里得方法 显示英文标题

标题： Quantum information processing at the cellular level. Euclidean approach

摘要： 量子原理在活细胞中的应用需要对细胞内动力学的完整量子力学描述进行新的近似。 我们讨论任何这样的良好近似应包含的主要元素。 作为其中一个元素，引入了“催化力”Cf的概念。 Cf是催化分子靶对催化微环境的影响，这种影响使微环境调整到一个有利于催化作用的状态。 这一现象可以实验检验，并对生物组织和进化具有引人入胜的含义，因为它相当于“无需复制子自然选择的优化”。 与自组织的统计力学方法不同，Cf原理在个体细胞层面不会遇到“稳定性与复杂性之间的权衡”问题。 从物理上讲，Cf被视为一种类似谐波的反应力，它使细胞状态保持在基态附近，此处定义为酶促作用最有效的状态。 基态服从幺正演化，并作为这里称为“欧几里得方法”的细胞内过程量子描述的一般策略的起点。 该策略的下一步是从基态描述过渡到生长态描述，我们建议如何利用涨落-耗散定理的论点来实现这一点。 最后，鉴于单个细胞最可靠和信息量最大的可观测量是其基因组序列，我们提出，可以在单细胞水平上使用高通量DNA测序最容易地检测个体分子事件之间的非经典关联。 显示英文摘要

摘要： Application of quantum principles to living cells requires a new approximation of the full quantum mechanical description of intracellular dynamics. We discuss what principal elements any such good approximation should contain. As one such element, the notion of "Catalytic force" Cf is introduced. Cf is the effect of the molecular target of catalysis on the catalytic microenvironment that adjusts the microenvironment towards a state that facilitates the catalytic act. This phenomenon is experimentally testable and has an intriguing implication for biological organization and evolution, as it amounts to "optimization without natural selection of replicators". Unlike the statistical-mechanical approaches to self-organization, the Cf principle does not encounter the problem of "tradeoff between stability and complexity" at the level of individual cell. Physically, the Cf is considered as a harmonic-like force of reaction, which keeps the state of the cell close to the ground state, defined here as a state where enzymatic acts work most efficiently. Ground state is subject to unitary evolution, and serves as a starting point in a general strategy of quantum description of intracellular processes, termed here "Euclidean approach". The next step of this strategy is transition from the description of ground state to that one of growing state, and we suggest how it can be accomplished using arguments from the fluctuation-dissipation theorem. Finally, given that the most reliable and informative observable of an individual cell is the sequence of its genome, we propose that the non-classical correlations between individual molecular events at the single cell level could be easiest to detect using high throughput DNA sequencing.