John Ross of Stanford University is supported by an award from the Theoretical and Computational Chemistry program within the Division of Chemistry for the development of methods and tools to determine dominant reaction pathways in complex biochemical networks. The approach is based on the use of a generalized Fisher law, combined with a renormalization group approach, and applied to response experiments. Statistical approaches for identifying dominant reaction pathways from incomplete data collected from response experiments have been introduced. These methods permit the analysis of incomplete experimental data in biochemical reactions.
The broader impacts of this work involve an international collaboration to apply these methods to study several biological systems: to the study of yeast metabolism and blood coagulation. It is expected that the blood coagulation model will be implemented in clinical software programs for improved prediction of the dosage of oral coagulants.
Chemical Kinetics, both theory and experiment, are vital components of studies in Chemistry, Chemical Engineering, Biochemistry, Genetic Engineering, Biology, Earth Science (Geochemistry), and therefore much research is needed and applied in Chemical Kinetics in these fields. Our interest and contributions to the study of Chemical Kinetics have been in several areas, and three of these studied in the last three years will be briefly described. 1) Multi-Criteria Optimization of Regulation in Metabolic Networks. It has been hypothesized that biochemical pathways (the ordered appearance of reactants and products in metabolic networks) may have undergone an evolutionary process of optimization with respect to several variables over time. To investigate such a possibility we used a multi- criteria approach to optimize parameters for the (allosteric) regulation of enzymes in a model of a metabolic substrate cycle. The mathematical analysis is tedious but shows the existence of a universal regulation system. 2) MIDER: network inference with mutual information distance and entropy reduction. In prior work done almost 20 years ago, we introduced the concept of information theory to construct frame of a reaction network in which distances between molecules are related to their interactions. There are two steps: first the visual representation of the network in which the distances among the modes indicate their statistical closeness; second the method can be developed to distinguish between direct and indirect interactions and assign directionality. This method is very general and was tested on seven different benchmark problems which cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. 3) Proposed principles of maximum local entropy production. When an irreversible process occurs, such as a spontaneous chemical reaction, then there also occurs entropy production. Dozens of articles have been written that under stated conditions the entropy production is a maximum. We have made a thorough study of these predictions and find them wrong. No such principle is valid.
