A Computational Model for the Metabolism of Myo-Inositol Hexakisphosphate Public Deposited

Downloadable Content

Download PDF
Last Modified
  • February 26, 2019
  • Smith, James Evan
    • Affiliation: School of Medicine
  • This project formulates a computational model for the biochemical network interlacing inositol phosphates (InsPs) critical in the metabolism of myo-inositol hexakisphosphate (InsP6). The role these InsPs are believed to play in developmental and homeostatic regulation underlines the need for novel analysis in model organisms like Arabidopsis thaliana. While some effects with apparent cause may be accessible by means of conventional analytics, a computational model for InsP synthesis could facilitate the resolution of far more complex queries and provide a comprehensive assessment of potential, even unintuitable, behavior. The primary goal of this project was to formulate an in silico model and to verify if, and to what extent, borrowed reaction kinetics for the InsP synthesis network recapitulate the behavior seen in traditional, in vivo studies. Preliminary results suggest that while our model’s response to loss of function mutations emulates some aspects of the expected results, divergent phenomena indicate the need for deliberate modification. A subsidiary goal of this project was to demonstrate the utility of the model through its application in a variety of perturbation schemes. The model was able to, among other goal-oriented objectives, verify behavioral expectations in response to an indirect implementation of an energy-sensing kinase, SnRK1, and thereby corroborate contemporary understanding of certain protein-protein interactions without the need for expensive testing. Clearly, the flexibility and heuristic capacity of this model are of value and suggest that this project may very well represent the state of the art insofar as computational modeling of InsP signaling is concerned. In the future, iterative revision will only help to improve this model’s efficacy and predictive power.
Date of publication
Resource type
Rights statement
  • In Copyright
  • Funding: Tom and Elizabeth Long Excellence Fund for Honors
  • Funding: NSF Grant, MCB #1052034
  • Williams, Cranos
  • Bachelor of Science
Honors level
  • Highest Honors
Degree granting institution
  • University of North Carolina at Chapel Hill
  • 37 p.

This work has no parents.