The mass-action law based algorithms for quantitative econo-green bio-research

Abstract

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”.