Preclinical Pharmacology Core Laboratory, Molecular Pharmacology & Chemistry Program, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
Integr Biol (Camb). 2011 May;3(5):548-59. doi: 10.1039/c0ib00130a. Epub 2011 Mar 14.
The relationship between dose and effect is not random, but rather governed by the unified theory based on the median-effect equation (MEE) of the mass-action law. Rearrangement of MEE yields the mathematical form of the Michaelis-Menten, Hill, Henderson-Hasselbalch and Scatchard equations of biochemistry and biophysics, and the median-effect plot allows linearization of all dose-effect curves regardless of potency and shape. The "median" is the universal common-link and reference-point for the 1st-order to higher-order dynamics, and from single-entities to multiple-entities and thus, it allows the all for one and one for all unity theory to "integrate" simple and complex systems. Its applications include the construction of a dose-effect curve with a theoretical minimum of only two data points if they are accurately determined; quantification of synergism or antagonism at all dose and effect levels; the low-dose risk assessment for carcinogens, toxic substances or radiation; and the determination of competitiveness and exclusivity for receptor binding. Since the MEE algorithm allows the reduced requirement of the number of data points for small size experimentation, and yields quantitative bioinformatics, it points to the deterministic, efficient, low-cost biomedical research and drug discovery, and ethical planning for clinical trials. It is concluded that the contemporary biomedical sciences would greatly benefit from the mass-action law based "Green Revolution".
剂量与效应之间的关系不是随机的,而是受基于质量作用定律中值效应方程(MEE)的统一理论所支配。MEE 的重新排列产生了生物化学和生物物理学的米氏方程、Hill 方程、Henderson-Hasselbalch 方程和 Scatchard 方程的数学形式,中值效应图允许对所有剂量-效应曲线进行线性化,而不管效价和形状如何。“中值”是从一阶到高阶动力学的通用共同链接和参考点,以及从单一实体到多个实体,因此,它允许“一合为万,万合为一”的统一理论“整合”简单和复杂的系统。其应用包括:如果准确确定,则只需用两个理论上最小的数据点构建剂量-效应曲线;在所有剂量和效应水平上量化协同作用或拮抗作用;对致癌物、有毒物质或辐射进行低剂量风险评估;以及确定受体结合的竞争力和排他性。由于 MEE 算法允许减少对小尺寸实验数据点数量的要求,并产生定量生物信息学,因此它指向确定性、高效、低成本的生物医学研究和药物发现,以及临床试验的伦理规划。结论是,当代生物医学科学将从基于质量作用定律的“绿色革命”中受益匪浅。