Biology Reference
In-Depth Information
maps stored in these pathway databases because of the lack of information for constructing simulatable
computational models.
We have conducted some simulations of biological phenomena including apoptosis signaling pathway
[Matsuno
et al.
, 2003b], cell cycles [Fujita
et al.
, 2004; Matsui
et al.
, 2004], and circadian rhythms
[Matsuno
et al.
, 2003b], etc. [Matsuno
et al.
, 2000; Doi
et al.
, 2003; Matsuno
et al.
, 2003a; Doi
et
al.
, 2004]. Hybrid functional Petri net (HFPN) [Matsuno
et al.
, 2003b] is adopted to construct these
computational models for the simulations. These HFPN models are constructed, being based on pictures
in the biological literature. Thereafter, parameters of reactions such as the transcription speeds of
genes and degradation rates of proteins shall be tuned so that input/output concentration behaviors of
substances such as mRNAs and proteins are matched with biological facts which have been obtained from
experiments and/or written information in the literature. With this method, we can include information
for simulating molecular reactions in the HFPN model while keeping graphical images of the original
biological picture.
Proteins p53, MDM2, and p19ARF are proteins closely related to cancer. The protein p53 is a protein
which suppresses the formation of tumors, and the protein MDM2 promotes the formation of tumors
by decreasing the activity of the protein p53. Understanding of control mechanism of these proteins
connects to development of an effective medicine for suppressing the tumor.
In this paper, we present a new HFPN model of a cancer pathway including a tumor suppressor gene
p53
. As the genes related to
p53
, genes
MDM2
and
p19ARF
have been identified [Zhang and Xiong,
2001; Iwakuma and Lozano, 2003].
MDM2
works as an inhibitor for
p53
, and
MDM2
is further inhibited
by
p19ARF
. These interactions of these three genes have been described in the existing biological
pathway databases including KEGG [Kanehisa and Goto, 2000] and TRANSPATH [Krull
et al.
, 2003]
(
http://www.biobase.de/
)
. This paper presents an HFPN model of the interaction of p53, MDM2, and
p19ARF, and gives simulation results on the HFPN model using Cell Illustrator [Nagasaki et al., 2003],
also indicate that the facts and data in the biological literature can be interpreted into the HFPN model
to construct this dynamic pathway model, while the conventional pathway databases screen out some
helpful information for system dynamics.
It is known that protein p53 works as a transcription factor for many genes [el-Deiry, 1998] and its
transcriptional activity is controlled by a complex formed with proteins MDM2 and p19ARF [Zhang and
Xiong, 2001; Iwakuma and Lozano, 2003]. However, it is still unclear whether protein p53 keeps its
transcriptional activity in the form of the trimer with proteins p53, MDM2 and p19ARF. With our HFPN
model, we have simulated mutual behaviors between genes
p53
,
MDM2
,
p19ARF
, and their products.
The simulation results suggested that protein p53 should have transcriptional activity in the forms of the
trimer of proteins p53, MDM2, and p19ARF.
HFPN MODEL OF PROTEIN INTERACTIONS OF p53, MDM2, AND p19ARF
Hybrid functional Petri net
A Petri net is a network consisting of places, transitions, arcs, and tokens. A place (depicted as a
circle) can hold tokens as its content. At a transition (depicted as a filled rectangle), arcs coming from
places and those going out from the transition to some places can be connected. A transition with these
arcs defines a firing rule with regard to the contents of the places to which the arcs are attached.
