Pearlstein Robert A, McKay Daniel J J, Hornak Viktor, Dickson Callum, Golosov Andrei, Harrison Tyler, Velez-Vega Camilo, Duca José
Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, MA, United States.
Curr Top Med Chem. 2017;17(23):2642-2662. doi: 10.2174/1568026617666170414152311.
Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT.
细胞药物靶点存在于网络化的功能生成系统中，其组成分子种类会响应特定扰动（即输入）而经历动态相互依存的非平衡状态转变。细胞表型行为通过此类网络的综合行为得以体现。然而，体外数据常常采用与孤立靶点群体相关的经验平衡或稳态模型（如希尔方程、米氏方程、布里格斯 - 霍尔丹方程）进行测量和/或解释。我们提出，细胞就像模拟计算机，通过对这些群体间动态状态概率分布的“整合”来“求解”耦合的“分子微分方程”集（即由相互作用物种群体表示）。对于远离平衡运行的含靶点系统，以及在生化结果分析中忽略耦合作用（包括靶点 - 同源伴侣结合和药物药代动力学）时，生化检测与功能/表型检测（细胞/体内）之间可能会出现脱节。将药物发现从反复试验的努力转变为基于可靠设计标准的过程，依赖于在系统层面更好地理解驱动细胞功能/功能障碍的动态机制。在此，我们阐述分子和细胞功能的一般机制及其药理学调节。我们概述了一个关于自由能如何储存并转化为生物学功能，以及生物学功能如何通过药物 - 靶点结合进行调节的第一原理理论。我们提出，细胞功能取决于非平衡条件下分子状态转变的指数行为所必需的动态平衡分子系统，包括正、负质量作用动力学以及溶质对溶剂化水氢键与kT的扰动。
