The Mass-Action-Law Based GPS Concept for Bio-Informatics
Author(s) -
TingChao Chou
Publication year - 2008
Publication title -
nature precedings
Language(s) - English
Resource type - Journals
ISSN - 1756-0357
DOI - 10.1038/npre.2008.2064.2
Subject(s) - mass action law , context (archaeology) , action (physics) , law of mass action , mathematics , law , physics , thermodynamics , quantum mechanics , paleontology , political science , biology
The unified theory of dose and effect, as indicated by the median-effect equation for single and multiple entities and for the first and higher order kinetic/dynamic, has been established by T.C. Chou and it is based on the physical/chemical principle of the mass-action law (_J. Theor. Biol._ 59: 253-276, 1976; _Pharmacological Rev._ 58: 621-681, 2006). Rearrangements of the median-effect equation lead to Michaelis-Menten, Hill, Scatchard, and Henderson-Hasselbalch equations. The “median” serves as the “universal reference point” and the “common link” for the relationship of all entities at all dynamic orders, and is also the “harmonic mean” of kinetic dissociation constants. Over 300 mechanism-specific equations have been derived and published using the mathematical induction-deduction process. These equations can be deduced into several general equations, including the median-mediated whole/part equation, combination index theorem, isobologram equation, and polygonogram. It is proven that “dose” and “effect” are interchangeable, thus, “substance” and “function” are interchangeable, which leads to “the-unity theory” in philosophical context. Based on the mass-action law, the fundamental conceptual claim is that “one can draw a specific cure for only two data points”, if they are determined accurately. Furthermore, instead of drawing an empirical curve for data-fitting, we can now use the data points to fit the median-effect principle of the mass-action law by automated computer simulation. This small kill has far reaching consequences in biomedical sciences including small size experimentation, efficient experimental design and data interpretation, efficiency in drug discoveries, quantifying/simulating synergism in drug combinations, assessing low-dose risk of carcinogens, toxic substances or radiation, and conserving laboratory animals’ lives. For the “combination index” alone, the theory has been cited in over 345 different biomedical journals, based on the Thompson-ISI Web search, indicating broad applications
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