ReDirection: an R-package to compute the probable dissociation constant for every reaction of a user-defined biochemical network - Kundu, Siddhartha (Frontiers in Molecular Biosciences, 2023)
Biochemical networks integrate enzyme-mediated substrate conversions with non-enzymatic complex formation and disassembly to accomplish complex biochemical and physiological function. The choice of parameters and constraints used in most of these studies is numerically motivated and network-specific. Although sound in theory, the outcomes that result will depart significantly from the intracellular milieu and are less likely to retain relevance in a clinical setting. There is need for a computational tool which is biochemically relevant, mathematically rigorous, unbiased and can ascribe functionality to and generate potentially testable hypotheses for a user-defined biochemical network. Here, we present “ReDirection”, an R-package which will compute the probable dissociation constant for every reaction of a biochemical network directly from a null space generated subspace of the stoichiometry number matrix of the modelled network. “ReDirection” delineates this subspace by excluding all trivial and redundant or duplicate occurrences of non-trivial vectors, combinatorially summing the vectors that remain and verifying that the upper- or lower-bounds of the sequence of terms formed by each row of this subspace belong to the open real-valued intervals (-∞,-1) or (1,∞) or whether the number of terms that are differently signed are almost equal. “ReDirection” iterates these steps until these bounds are consistent and unambiguous for all reactions of the modelled biochemical network. Thereafter, “ReDirection” filters the terms from each row of this subspace, bins them to outcome-specific subsets, sums and maps this to an outcome-specific reaction vector and computes the p1-norm which is the probable dissociation constant for a reaction. “ReDirection” works on first principles, does not discriminate between enzymatic and non-enzymatic reactions, offers a biochemically relevant and mathematically rigorous environment to explore user-defined biochemical networks under baseline and perturbed conditions and can be used to address empirically intractable biochemical problems. The utility and relevance of “ReDirection” is highlighted by numerical studies on stoichiometry number models of biochemical networks of Galactose metabolism and heme- and cholesterol-biosynthesis. “ReDirection” is freely available and accessible from the comprehensive R archive network (CRAN) with the URL (https://cran.r-project.org/package=ReDirection).