Theoretical Approaches to Ribocell Modeling

  • Fabio MavelliEmail author


The so-called Ribocell (ribozymes-based cell) is a theoretical cellular model that has been proposed some years ago as a possible minimal cell prototype. It consists in a self-replicating minimum RNA genome coupled with a self-reproducing lipid vesicle compartment. This model assumes the existence of two hypothetical ribozymes one able to catalyze the conversion of molecular precursors into lipids and the second one able to replicate RNA strands. Therefore, in an environment rich both of lipid precursors and activated nucleotides, the ribocell can self-reproduce if the genome self-replication and the compartment self-reproduction mechanisms are somehow synchronized. The aim of this contribution is to explore the feasibility of this model with in silico simulations using kinetic parameters available in literature.


Stochastic Simulation Deterministic Analysis Deterministic Calculation Lipid Precursor Empty Vesicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Ao P (2005) Metabolic network modelling: including stochastic effects. Comput Chem Engin 29:2297–2303CrossRefGoogle Scholar
  2. Chen IA, Roberts RW, Szostak JW (2004) The emergence of competition between model protocells. Science 305:1474–1476CrossRefPubMedGoogle Scholar
  3. Christensen U (2007) Thermodynamic and kinetic characterization of duplex formation between 2’-O, 4’-C-Methylene-modified Oligoribonucleotides. DNA RNA Biosci Rep 27:327–333CrossRefGoogle Scholar
  4. Gillespie DT (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J Comput Phys 22:403–434CrossRefGoogle Scholar
  5. Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81:2340–2361CrossRefGoogle Scholar
  6. Gillespie DT (1992) Markov processes: an introduction for physical scientists. Academic Press, San DiegoGoogle Scholar
  7. Gillespie DT (2007) Stochastic simulation of chemical kinetics. Annu Rev Phys Chem 58:35–55CrossRefPubMedGoogle Scholar
  8. Gillespie DT (2009) Deterministic limit of the stochastic chemical kinetics. J Phys Chem 113:1640–1644Google Scholar
  9. Lecca P (2007) Simulating the cellular passive transport of glucose using a time-dependent extension of Gillespie algorithm for stochastic pi-calculus. Int J Data Mim Bioinf 1:315–336CrossRefGoogle Scholar
  10. Li H, Cao Y, Petzold LR, Gillespie DT (2008) Algorithms and software for stochastic simulation of biochemical reacting systems. Biotechnol Prog 24:56–61CrossRefPubMedGoogle Scholar
  11. Lincoln TA, Joyce GF (2009) Self-sustained replication of an RNA enzyme. Science 323:1229–1232CrossRefPubMedGoogle Scholar
  12. Lu T, Volfson D, Tsimring L, Hasty J (2004) Cellular growth and division in the Gillespie algorithm. Syst Biol 1:121–128CrossRefGoogle Scholar
  13. Luisi PL (1998) About various definitions of life. Orig Life Evol Biosph 28:613–622CrossRefPubMedGoogle Scholar
  14. Luisi PL (2003) Autopoiesis: a review and a reappraisal. Naturwissensch 90:49–59Google Scholar
  15. Mansy SS, Szostak JW (2008) Thermostability of model protocell membranes. PNAS 105:13351–13355CrossRefPubMedGoogle Scholar
  16. Mansy SS, Schrum JP et al (2008) Template directed synthesis of a genetic polymer in a model protocell. Nature 454:122–126CrossRefPubMedGoogle Scholar
  17. Mavelli F, Lerario M, Ruiz-Mirazo K (2008) ‘Environment’: a stochastic simulation platform to study protocell dynamics. In: Arabnia HR et al (eds) BIO-COMP’08 proceedings, vol II. CSREA Press, New YorkGoogle Scholar
  18. Mavelli F, Piotto S (2006) Stochastic simulations of homogeneous chemically reacting systems. J Mol Struct 771:55–64Google Scholar
  19. Mavelli F, Ruiz-Mirazo K (2007) Stochastic simulations of minimal self-reproducing cellular systems. Phil Trans Royal Soc B 362:1789–1802CrossRefGoogle Scholar
  20. Mavelli F, Ruiz-Mirazo K (2010) Environment: a computational platform to stochastically simulate self-replicating reacting vesicles. Phys Biol 7:036002Google Scholar
  21. Mavelli F, Stano P (2010) Kinetic models for autopoietic chemical systems: role of fluctuations in homeostatic regime. Phys Biol 7:16010Google Scholar
  22. McAdams HH, Arkin AP (1997) Stochastic mechanisms in gene expression. Proc Natl Acad Sci U S A 94:814–819CrossRefPubMedGoogle Scholar
  23. McQuarry DA (1975) Probability theory and stochastic processes. In: Henderson D (ed) Physical chemistry, an advanced treatise XIB. Academic Press, New YorkGoogle Scholar
  24. Ruiz-Mirazo K, Mavelli F (2007) Simulation model for functionalized vesicles: lipid-peptide integration in minimal protocells. In: Almeida F (ed) Advances in artificial life. Springer, BerlinGoogle Scholar
  25. Ruiz-Mirazo K, Mavelli F (2008) On the way towards basic autonomous systems: stochastic simulations of minimal lipid-peptide cells. Biosystems 91:374–387CrossRefPubMedGoogle Scholar
  26. Sacerdote MG, Szostak JW (2005) Semipermeable lipid bilayers exhibit diastereo-selectivity favoring ribose. PNAS 102:6004–6008CrossRefPubMedGoogle Scholar
  27. Samoilov M, Plyasunov S, Arkin AP (2005) Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations. Proc Natl Acad Sci USA 102:2310–2315Google Scholar
  28. Stage-Zimmermann TK, Uhlenbeck OC (1998) Hammerhead ribozyme kinetics. RNA 4:875–889CrossRefPubMedGoogle Scholar
  29. Szostak JW, Bartel DP and Luisi PL (2001) Synthesizing life. Nature 409:387–390.Google Scholar
  30. Tsoi PY, Yang M (2002) Surface plasmon resonance study of human polymerase β binding to DNA. Biochem J 361:317–325Google Scholar
  31. Van Kampen NG (1981) Stochastic processes in physics and chemistry. Elsevier, AmsterdamGoogle Scholar

Copyright information

© Springer Netherlands 2011

Authors and Affiliations

  1. 1.Chemistry DepartmentUniversity of BariBariItaly

Personalised recommendations