2003 Special Issue Kinetic simulation of signal transduction system in hippocampal long-term potentiation with dynamic modeling of protein phosphatase 2A Shinichi Kikuchi a, * , Kenji Fujimoto a , Noriyuki Kitagawa a , Taro Fuchikawa a , Michiko Abe a , Kotaro Oka a,b , Kohtaro Takei a,c , Masaru Tomita a a Laboratory for Bioinformatics, Institute for Advanced Biosciences, Keio University, Endo 5322, Fujisawa 252-8520, Japan b Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Yokohama, Japan c Department of Molecular Pharmacology and Neurobiology, Yokohama City University School of Medicine, Yokohama, Japan Received 28 December 2002; revised 3 September 2003; accepted 3 September 2003 Abstract We modeled and analyzed a signal transduction system of long-term potentiation (LTP) in hippocampal post-synapse. Bhalla and Iyengar [Science 283(1999) 381] have developed a hippocampal LTP model. In the conventional model, the concentration of protein phosphatase 2A (PP2A) was fixed. However, it was reported that dynamic inactivation of PP2A was essential for LTP [J. Neurochem. 74 (2000) 807]. We introduced a dynamic modeling of PP2A; inactivation (phosphorylation) of PP2A by calcium/calmodulin-dependent protein kinase II (CaMKII) in the presence of calcium/calmodulin, self-activation (autodephosphorylation) of PP2A, and inactivation (dephosphorylation) of CaMKII by PP2A. This model includes complex feedback loops; both CaMKII and PP2A are autoactivated, while they inactivate each other. Moreover, we proposed an analysis strategy for model validation by applying the results of sensitivity analysis. In our system, calcineurin (CaN) played an essential role, rather than the activation of protein kinase C (PKC) as documented in the conventional model. From results of the analysis of our model, we found the following robustness as characteristics of bistability in our model: (1) PP2A reactions against calcium ion (Ca 2þ ) perturbation; (2) PP2A inactivation against PP2A increase; (3) protein phosphatase 1 (PP1) activation against PF2A increase; and (4) PP2A reactions against PP2A initial concentration. These properties facilitated LTP induction in our system. We showed that another mechanism could introduce bistable behavior by adding dynamic reactions of PP2A. q 2003 Elsevier Ltd. All rights reserved. Keywords: Kinetic simulation; Long-term potentiation; Protein phosphatase 2A; Hippocampus; E-Neuron; E-Cell 1. Introduction Progress in neuroscience and information science has brought a novel approach called neuroinformatics (Beltrame & Koslow, 1999; Huerta & Koslow, 1996). The scope of neuroinformatics is various and wide encompassing micro- level to macrolevel phenomenon (see reviews: Ko ¨tter, 2001; Wong & Koslow, 2001). In order to cover a large area, various international consortiums have been formulated: Human Brain Project (Brinkley & Rosse, 2002), International Consortium for Brain Mapping (ICBM) (Mazziotta et al., 2001) and OECD Neuroinformatics Working Group (Eckersley et al., 2003). These projects store and share the databases and software tools similar to web-based genome projects. The macro and mid approaches directly relate to the mechanism of human brain, including neuroanatomy/atlas (Bowden & Martin, 1995; Martin & Bowden, 1996), neuroimaging/fMRI (Fox & Lancaster, 2002; Magnotta et al., 2002; Pizzi, Vivanco, & Somorjai, 2001; Worsley et al., 2002), MEG/EEG (Muller, Neuper, & Pfurtscheller, 2003; Wolpaw, Birbaumer, McFarland, Pfurtscheller, & Vaughan, 2002), connectivity (Burns & Young, 2000; Stephan et al., 2001), and machine learning (Doya, 2002). On the other hand, the micro approach enables elucidation of its mechanism and discovering novel drugs. That includes neurophysiology (Gardner, Abato, Knuthm, DeBellism, & Erdem, 2001) and neuromorphology (Ascoli, Krichmar, Nasuto, & Senft, 2001; Breslin & O’Lenskie, 2001; van Pelt, van Ooyen, & Uylings, 2001). Our E-Neuron project aims to model and analyze neuronal behaviors at the molecular level. Although 0893-6080/$ - see front matter q 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.neunet.2003.09.002 Neural Networks 16 (2003) 1389–1398 www.elsevier.com/locate/neunet * Corresponding author. Tel./fax: þ 81-466-47-5099. E-mail address: kikuchi@sfc.keio.ac.jp (S. Kikuchi).