Evolution in silico

Evolution in silico - From Neutral Networks to Multi-stable Molecules... 

Ibarra RU, Edwards JS, Palsson BO. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 2002 420 186-9. 

The constant refinement of techniques for directed protein evolution also involves the development of increasingly sophisticated in silico tools. This co-evolution of experimental and computational methods enriches our toolkit for finding the sequence that fits. It is this mutual impact which makes ProSa a valuable component in designing both experiments and proteins. 

Fig. 2.4. The flow reactor as a device for RNA structure optimization. RNA molecules with different shapes are produced through replication and mutation. New sequences obtained by mutation are folded into minimum free energy secondary structures. Replication rate constants are computed from structures by means of predefined rules (see text). For example, the replication rate is a function of the distance to a target structure, which was chosen to be the clover leaf shaped tRNA shown above (white shape) in the reactor. Input parameters of an evolution experiment in silico are the population size N, the chain length X of the RNA molecules as well as the mutation rate p.

Rea, G., Lambreva, M., Polticelli, F, Bertalan, I., Antonacci, A, Pastorelli, S, Damasso, M., Johanningmeier, U., and Giardi, M.T. (2011) Directed evolution and in silico analysis of reaction centre proteins reveal molecular signatures of photosynthesis adaptation to radiation pressure. PLoS One, 6 (1), el6216. 

Hua Q, Joyce R, Fong SS, Palsson B0 (2006) Metabolic analysis of adaptive evolution for in silico-designed lactate-producing strains. Biotechnol Bioeng 95 992-1002. doi 10.1002/bit. 21073... 

To develop a biocatalytic process, screening of commercially available transaminases by Merck and Codexis provided no enz3une with detectable activity for amination of tile prositagliptin ketone 6 [28]. They therefore applied a combination of in silico design and directed evolution in an effort to confer such an enzyme. 

This model has the conceptual advantage of containing looping or self-consistent QSAR information that is in line with the recursive evolution of cancer at the cellular level. It has also an apparent weakness in that it requires prior knowledge of the observed activity, even for the untested compounds or those that are designed in silico. However, such a drawback may now be avoided with the advent of unified databases with the aid of... 

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