Abstract
Kinetic parameters are a crucial aspect when studying reactions involving proteins. Unfortunately, these are often unknown or hard to measure in the laboratory. Therefore, modeling phenomena involving protein reactions without using kinetic parameters can be a significant advantage. In this work, an agent-based model of the budding yeast (Saccharomyces cerevisiae) cell cycle was created based on a cell cycle regulatory network, to obtain the correct sequence of states of the regulatory proteins. Comparing the results to a Boolean network model, having similar results, following the correct sequence of phases and reaching in 71% of the cases the biological G1 stationary state of the cell. Yeast cell cycle is highly conservated among other eukaryotes, meaning that is regulators works similar than the ones in humans; knowing that, yeast cells can be mutated to have behavior related to a specific tumor and then treated with different drugs to check which is better to kill that particular tumor. This model could be a starting point for being used in the development of cancer drugs adding cell cycle mutations that match a specific type of tumor cell cycle and an agent representing the medication or treatment.
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References
Nitiss, J. L. & Heitman, J. Yeast as tool in cancer research. (2007).
Hartwell, L. H. Yeast and cancer. Biosci. Rep. 24, 525–544 (2005).
Matuo, R. et al. Saccharomyces cerevisiae as a model system to study the response to anticancer agents. Cancer Chemother. Pharmacol. 70, 491–502 (2012).
Kalia, V. C. & Saini, A. K. Metabolic Engineering for Bioactive Compounds. (2017). https://doi.org/10.1007/978-981-10-5511-9.
Hartwell, L. H. Saccharomyces cerevisiae cell cycle. Bacteriol. Rev. 38, 164–198 (1974).
Li, F., Long, T., Lu, Y., Ouyang, Q. & Tang, C. The yeast cell-cycle network is robustly designed. Proc. Natl. Acad. Sci. 101, 4781–4786 (2004).
Bonabeau, E. Agent-based modeling: methods and techniques for simulating human systems. Proc. Natl. Acad. Sci. 99, 7280–7287 (2002).
Bayrak, E. S. et al. In Silico Cell Cycle Predictor for Mammalian Cell Culture Bioreactor Using Agent-Based Modeling Approach. IFAC-PapersOnLine 49, 200–205 (2016).
Bauer, A. L., Beauchemin, C. A. A. & Perelson, A. S. Agent-based modeling of host-pathogen systems: The successes and challenges. Inf. Sci. (Ny). 179, 1379–1389 (2009).
Khataee, H. R., Aris, T. N. M. & Sulaiman, M. N. An agent-based model of muscle contraction process as a bio-robotic process. 2011 5th Malaysian Conf. Softw. Eng. MySEC 2011 55–60 (2011). https://doi.org/10.1109/mysec.2011.6140643.
Manzanarez-ozuna, E. et al. Computational modeling of the MAPK pathway using NetLogo. 1–4 (2015). doi:https://doi.org/10.13140/rg.2.1.4179.6244.
Zhang, L., Wang, Z., Sagotsky, J. A. & Deisboeck, T. S. Multiscale agent-based cancer modeling. J. Math. Biol. 58, 545–559 (2009).
Wilensky, U. & Rand, W. An Introduction to Agent-Based Modeling. (2015).
Wilensky, U. NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (1999). Available at: http://ccl.northwestern.edu/netlogo/.
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Castro, C., Flores, DL., Vargas, E., Cervantes, D., Delgado, E. (2019). Agent-Based Model of the Budding Yeast Cell Cycle Regulatory Network. In: Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G.S. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/1. Springer, Singapore. https://doi.org/10.1007/978-981-10-9035-6_98
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DOI: https://doi.org/10.1007/978-981-10-9035-6_98
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