Protein sequence space

Finally, the region of accessible protein sequence space was extended by developing a modified version of Stemmer s combinatorial multiple-cassette mutagenesis (CMCM)... 

These initial systematic studies regarding the directed evolution of PAL allowed several conclusions to be made. Protein sequence space can be explored successfully by applying the following strategies [8c,33j ... 

The choice of the particular upward pathway in the kinetic resolution of rac-19, that is, the specific order of choosing the sites in ISM, appeared arbitrary. Indeed, the pathway B C D F E, without utilizing A, was the first one that was chosen, and it led to a spectacular increase in enantioselectivity (Figure 2.15). The final mutant, characterized by nine mutations, displays a selectivity factor of E=115 in the model reaction [23]. This result is all the more remarkable in that only 20000 clones were screened, which means that no attempt was made to fully cover the defined protein sequence space. Indeed, relatively small libraries were screened. The results indicate the efficiency of iterative CASTing and its superiority over other strategies such as repeating cycles of epPCR. 

Reetz MT, Wang LW, Bocola M (2006) Directed evolution of enantioselective enzymes iterative cycles of CASTing for probing protein-sequence space. Angew Chem Int Ed 45 1236-1241... 

Clearly, all of these strategies for navigating in protein sequence space are successful, but it is not obvious which ones are optimal. 

The results of these and other experiments are summarized in Fig. 17. A total of only 40 000 mutants was screened, which is actually a small number in our context. It is likely that upon exploration of larger portions of protein sequence space efficiently, even better lipase-variants can be identified. The assumption that millions of potential variants in the vast protein sequence space are highly enan-tioselective is not unfounded. 

Even if we restrict our design to a small number of sites in the protein, the combinatorial possibilities quickly approach astronomical dimensions. If we consider mutations at 10 sites and a subset of 10 amino acids, we have 1010 possible variants. Although experimental approaches are under development that can actually search large subsets of protein sequence space, it is not at all a small feat to identify those variants that give rise to a stable structure and at the same time come close to the desired features. Therefore, computational approaches that, with some reliability, are able to pick those variants having a stable structure are desirable instruments in the protein engineer s toolbox. 

A. Babajide, R. Farber, I.L. Hofacker, J. Inman, A.S. Lapedes, and P.F. Stadler. Exploring protein-sequence space using knowledge-based potentials. J. Theo. Biol, 212 35—46,2001. 

Subsequent directed evolution work on Pseudomonas aeruginosa demonstrates that protein sequence space with respect to enantioselectivity is best explored by a three-step procedure (Reetz, 2001) (i) generation of mutants by error-prone PCR at a high-mutation rate (ii) identification of hot regions and spots in the enzyme by error-prone PCR and substantiation by simplified combinatorial multiple-cassette mutagenesis (iii) extension of the process of combinatorial multiple-cassette mutagenesis to cover a defined region of protein sequence space. 

O Toole, N., Raymond, S., and Cygler, M. (2003) Coverage of protein sequence space by current structural genomics. J. Struct. Func. Genomics 4,47-55. 

Although the existence of neutral networks has been well established for RNA, it is important to note the difference between RNA and protein landscapes. Most important, all RNA sequences fold into some structure, whereas it is likely that the vast majority of protein sequence space is devoid of well-defined structure. It may be possible to overcome this problem because protein sequence space has a higher dimensionality, there are more chances to produce a connected network. In a preliminary study, Stadler and coworkers estimated the neutral structure of... 

Protein sequence space was postulated as a useful tool for discussing protein evolution already in 1970 [54]. Later on most extensive model studies were more or less... 

It is worth mentioning in this context that there seems to be a general difference between RNA and protein landscapes Certain amino acid composition ratios between hydrophobic and hydrophilic amino acids presumably give rise to insoluble aggregates and this may lead to holes in protein sequence space. Perhaps, the concept of holey adaptive landscapes as favored in a series of recent papers on models of evolution [62] might be useful in this context. 

The superior performance of proteins in respect to functional diversity, specificity, and efficiency has attracted scientists and engineers alike to create tailor-made catalysts by protein engineering. Customizing a protein towards practical applications such as industrial catalysts, biosensors, and therapeutics offers many economic incentives. At the same time, protein engineering can address fundamental questions of protein design in respect to their structure and function. This can then lead to the development of new technologies facilitating the more directed exploration of protein sequence space. 

Fig. 11.12. An evolutionary tree illustrating the complexity of protein sequence space with respect to enantioselectivity [9], The simplified scheme is actually much more complicated. The numbers denote positive enzyme-variants obtained from repetitive cycles of mutagenesis and screening in the respective generations. The arrows pointing down symbolize inferior variants which of course outnumber the few positive variants.

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