ReDirection

ReDirection computes probable dissociation constants for every reaction in a user-defined biochemical network by analyzing the null space of the network's stoichiometry number matrix to characterize biochemical interactions.

Key Features:

• Comprehensive Reaction Characterization: ReDirection calculates probable dissociation constants for each reaction by leveraging a null space-generated subspace of the stoichiometry number matrix.
• Mathematical Rigor and Biochemical Relevance: It operates on first principles and treats enzymatic and non-enzymatic reactions equivalently to avoid bias in parameter estimation.
• Iterative Subspace Delineation: The method excludes trivial and redundant vectors, combinatorially sums remaining vectors, verifies that bounds fall within real-valued intervals, and iterates until bounds are consistent for all reactions.
• Outcome-Specific Analysis: After filtering terms from each row of the subspace, terms are binned into outcome-specific subsets, summed and mapped to reaction vectors, and the p1-norm is computed as the probable dissociation constant.
• Versatility in Conditions: The approach applies under baseline and perturbed conditions and has been demonstrated on networks for galactose metabolism, heme biosynthesis, and cholesterol biosynthesis.

Scientific Applications:

• Hypothesis Generation: Enables generation of potentially testable hypotheses about reaction dissociation constants within biochemical networks.
• Intracellular Physiology Insight: Provides quantitative estimates of probable dissociation constants to aid interpretation of biochemical and physiological functions in intracellular contexts.
• Unbiased Network Analysis: Supports analysis across enzymatic and non-enzymatic interactions for exploring diverse biochemical networks.

Methodology:

Compute a null space-generated subspace of the stoichiometry number matrix; exclude trivial and redundant vectors; combinatorially sum remaining vectors; verify bounds fall within specified real-valued intervals and iterate until consistency; filter terms from each subspace row, bin into outcome-specific subsets, map and sum to reaction vectors, and compute the p1-norm as the probable dissociation constant for each reaction.