Prof. Guanyu Wang published a research article in the Journal of Biological Chemistry, establishing a holistic theory to reveal new mathematical principles of biochemical dose-response curves
The stimulus-response curve is a commonly used data representation method in the biomedical field, and its horizontal axis is generally based on the logarithm of the stimulus concentration. Why use logarithmic coordinate? From a teleological point of view, this is because the effective range of stimulus concentration is generally very wide, spanning multiple orders of magnitude, and the horizontal axis needs to be compressed through logarithmic transformation. In addition to this teleological reason, does the logarithmic transformation reflect deeper biochemical principles? This question may only be considered by few people because there is no relevant report in the literature.
On November 28, Professor Guanyu Wang of the School of MEDICINE, The Chinese University of Hong Kong, Shenzhen published a research paper entitled "A more holistic view of the logarithmic dose-response curve offers greater insights into insulin responses" in the internationally renowned Journal of Biological Chemistry.
In the paper, Prof. Guanyu WANG examined dose response from a global perspective, established a mathematical model spanning multiple biological levels from molecules, to cells, and to the whole-organism, and used principles of statistics (law of large numbers, central limit theorem) to mathematically analyze the model, and found that the deep-seated reason for the logarithmic dose response is the step-by-step multiplication and amplification of cell signal transduction. The signal amplification causes the log-normal distribution of cell response thresholds. As the integral of the probability density function of the cell response threshold, the dose response curve is a cumulative log-normal distribution function. This mathematical model establishes the connection between the single-cell threshold response and the slow-changing response at the whole-organism level, reveals the raison d’être of the logarithmic transformation, explains why log(dose)-response curve possesses many fine properties, and reveals a new mechanism of biological ultrasensitivity (homogeneity-induced sensitivity). The model provides new insights into important biological processes such as hormonal response and drug synergy.
Article link: https://www.jbc.org/article/S0021-9258(24)02539-0/fulltext
Prof. Guanyu WANG, the author of this paper, sincerely thanks the National Natural Science Foundation of China, the National Key Research and Development Program, the Shenzhen-Hong Kong Cooperation Zone for Technology and Innovation, and the Shenzhen Peacock Team for their funding.
Prof. Guanyu WANG
Presidential Fellow
Associate Professor
Prof. Guanyu Wang is an associate professor of The Chinese University of Hong Kong, Shenzhen, School of Medicine, a permanent council member of “Computational Systems Biology Branch” of Chinese Operations Research Society, a committee member of “Molecular Systems Biology Specialized Committee” of Chinese Society of Biochemistry and Molecular Biology. He was a postdoc and then a research assistant professor of University of Texas Health Science Center at Houston, a research assistant professor of George Washington University Physics Department, and an associate professor of Southern University of Science and Technology. Prof. Wang published as first or corresponding author more than 60 high quality papers in SCI journals such as Proc Nat Acad Sci USA, Phys Rev Letts, J Biol Chem, J Roy Soc Interface (2), iScience(3), IEEE Transactions (2), Trends Immunol, Sci Bull, Theranostics, in total more than 60 papers. He also published a monograph “Analysis of Complex Diseases: A Mathematical Perspective (CRC Press).”
Interdisciplinary research is the defining feature of Guanyu Wang's group, which is targeting fundamental problems in biology and medicine. Professor Wang engages in a research system that centers on biological experiments, with scientific computation, mathematical analysis, and physical thinking as characteristic ingredients.
