AUTHOR=Kundu Siddhartha TITLE=ReDirection: an R-package to compute the probable dissociation constant for every reaction of a user-defined biochemical network JOURNAL=Frontiers in Molecular Biosciences VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1206502 DOI=10.3389/fmolb.2023.1206502 ISSN=2296-889X ABSTRACT=
Biochemical networks integrate enzyme-mediated substrate conversions with non-enzymatic complex formation and disassembly to accomplish complex biochemical and physiological functions. 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 depart significantly from the intracellular milieu and are less likely to retain relevance in a clinical setting. There is a need for a computational tool which is biochemically relevant, mathematically rigorous, and 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 computes 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 modeled 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