Biology Reference
In-Depth Information
Biological Petri Nets
Simulation-Based Validation of the p53
Transcriptional Activity with Hybrid
Functional Petri Net
Atsushi Doi
a
, Masao Nagasaki
a
, Hiroshi Matsuno
b
,∗
and Satoru Miyano
a
a
Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo
108-8639, Japan
b
Faculty of Science, Yamaguchi University, 1677-1 Yoshida, Yamaguchi, 753-8512, Japan
ABSTRACT:
MDM2 and p19ARF are essential proteins in cancer pathways forming a complex with protein p53 to control the
transcriptional activity of protein p53. It is confirmed that protein p53 loses its transcriptional activity by forming the functional
dimer with protein MDM2. However, it is still unclear that protein p53 keeps its transcriptional activity when it forms the trimer
with proteins MDM2 and p19ARF. We have observed mutual behaviors among genes
p53
,
MDM2
,
p19ARF
and their products
on a computational model with hybrid functional Petri net (HFPN) which is constructed based on information described in the
literature. The simulation results suggested that protein p53 should have the transcriptional activity in the forms of the trimer
of proteins p53, MDM2, and p19ARF. This paper also discusses the advantages of HFPN based modeling method in terms of
pathway description for simulations.
KEYWORDS:
Hybrid functional Petri net, p53, biological pathway, simulation
INTRODUCTION
Molecular interactions are usually summarized in a picture composed of figures of various shapes
(e.g. circles and rectangles) and several types of arrows. Graphical images in the picture are important
since they reflect the knowledge in biology and medicine. Biological pathway databases such as
KEGG [Kanehisa and Goto, 2000] and TRANSPATH [Krull
et al.
, 2003], (
http://www.biobase.de/
)
have
compiled many biological molecular interactions, providing invaluable information to researchers in the
forms of pictures. However, with such databases, it is not easy to grasp the information about quantitative
interactions of molecules, since such databases focus on providing qualitative information of molecular
interactions.
On the other hand, the computer simulation has received attentions of researchers in biology and
medicine as a useful method to understand biological mechanisms in molecular level of their interests.
It is natural to have an idea to use computer simulations for obtaining quantitative information of
molecular interactions. However, it is impossible to conduct simulations with only molecular interaction
∗
Corresponding author. E-mail:
matsuno@sci.yamaguchi-u.ac.jp
.
