Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors

TL;DR

This paper compares five computational modeling methods for the G-protein activation cycle in GPCR signaling, illustrating their implementation and translating high-level models into various formal languages.

Contribution

It introduces a high-level notation for biological modeling and demonstrates translation into multiple formal languages, enhancing accessibility and comparability.

Findings

Different modeling approaches yield consistent cycle representations

High-level notation simplifies model translation

Implementation in various languages facilitates cross-platform analysis

Abstract

In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we implement the G-protein cycle in the stochastic Pi-calculus using SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also provide a high-level notation to abstract away from communication primitives that may be unfamiliar to the average biologist, and we show how to translate high-level programs into stochastic Pi-calculus processes and chemical reactions.