Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network

Emilia M. Wysocka, Matthew Page, James Snowden, T. Ian Simpson

Research output: Working paperPreprint

Abstract

Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular complexes, can be prohibitive. Contemporary modelling methods, such as rule-based (RB) modelling, have addressed these issues. Although the advantages of RB modelling over ODEs have been presented and discussed in numerous reviews, no direct comparison of the time courses of a molecular system encoded in the two frameworks has been made before. To make such a comparison, a set of reactions that underlie an ODE model by Fernandez et al. [1] was manually encoded in the Kappa language, one of the RB frameworks. A comparison of the models was performed at the level of model specification and results were acquired through model simulations. We found that the Kappa model recapitulated the general dynamics of its ODE counterpart with minor differences. These differences occur whenever molecules have multiple sites binding the same interactor. The notation of such rules requires a complete listing of all possible binding configurations. Furthermore, activation of these molecules in the RB model is slower than in the ODE one but can be corrected by revision of the rate constants used in the relevant rules. We conclude that the RB representation offers a more expressive and flexible syntax that eases access to fine-grain details of the model, facilitating model reuse. In parallel with these analyses, this manuscript reports a refactored model of a DARPP-32 interaction network that can serve as a canvas for the development of a more complex interaction network to study this particular molecular system.Competing Interest StatementThe authors have declared no competing interest.Ca2+calcium ionscAMPcyclic adenosine monophosphateDAdopamineDARPP-32dopamine- and cAMP-regulated neuronal phosphoprotein with molecular weight 32 kDaGluglutamateMSPNmedium spiny projection neuronsODEordinary differential equationPTMpost-translational modificationRBrule-basedSBMLSystems Biology Markup LanguageSer102Serine 1O2Ser137Serine 137SSAStochastic Simulation AlgorithmThr34Threonine 34Thr75Threonine 75
Original languageEnglish
PublisherbioRxiv
Number of pages24
DOIs
Publication statusPublished - 27 Mar 2022

Keywords

  • modeling molecular dynamics
  • rule-based modelling
  • ordinary differential equations
  • DARPP-32
  • dopamine-dependent synaptic plasticity
  • Kappa

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