The rapidly increasing number of
revealed biological pathways calls for the development and use of simulation
methods and tools. Using computer simulations researchers would facilitate
their biological analysis and understanding of biological pathways. In this
work we deeply explore, examine and compare two biosimulation methods, the
Stochastic (Chemical)-p-Calculus and
the Hybrid Functional Petri Nets, as they apply to metabolic pathways. By
employing appropriate ways of modeling metabolic reactions, we introduce a
real-world simulation model of the Reduced Folates Metabolism, the pathway of
nucleic acids precursors synthesis, which is essential for DNA synthesis and cellular
proliferation and therefore, it plays an important role in cancer and cancer
chemotherapy. Using our real world reliable simulation model we perform several
virtual experiments that involve three different novel anticancer and chemotherapy
drugs. Using these experiments we determine for each drug its signature, i.e.
for each drug we determine its ways of inhibiting the cancer and more
important, in which quantities. Moreover, we theoretically investigate the
steady state phenomena of special structured metabolic pathways under some
relaxed conditions on the reactions’ rates using the Stochastic (Chemical)-p-Calculus and the Hybrid Functional Petri
Nets simulation methods. Such a theoretical approach gives us a better insight
into the convergence capabilities of the two simulation methods and the used
simulation algorithms and their asymptotic behavior. Mathematical proofs of the
simulations’ algorithms convergence and their steady state solutions which are also
illustrated by computer simulations are presented.
