Regenerate ligation site transcription

Fig. 35.16. Selection experiment for a self-ligating ribozyme.

[125, 126], peptide bond formation [127], and Diels-Alder cycloadditions [128]. While these ribozymes are often poorly active, in some cases very high levels of catalysis have been achieved through the further optimization of an initial ''lead''

The direct selection of highly efficient self-ligating ribozymes (i.e. phosphoryl transferases) from large RNA combinatorial libraries is one of the most impressive accomplishments thus far in the field of nucleotide-based catalysis (Fig. 35.16)

[130]. A library of @1015 different RNAs with 220 random nucleotides was constructed, and from this ensemble roughly 1 in 1013 members had the desired ligase activity. Further cycles of diversification and selection were then used to evolve the initially selected group of ligase ribozymes, and one of these was subsequently reengineered with the ability to catalyze an intermolecular ligation with multiple turnovers [131]. This enzyme exhibited a rate constant of >1 s-1, which corresponds to a rate acceleration approaching 109 over background.

Nucleic acid-based receptors and catalysts from combinatorial libraries are orthogonal analogs of their protein counterparts, and have potential value as drugs or diagnostic agents. The strategies used in their creation and selection, observations of how the initially identified ''hits'' further evolve to optimize function, and insight into the comparative advantages and disadvantages with respect to proteins should prove useful in our efforts to create and optimize novel protein catalysts (see Section 35.3.3).

Peptide Combinatorial Libraries

Short peptides are good inhibitors for a number of enzymes, and are thus suitable lead structures for developing potent nonpeptide inhibitors, which may have increased bioavailability and half-lives in vivo. Peptide ligands and inhibitors are also valuable for collecting a wealth of information about the structure, specificity, and size of receptor binding pockets and enzyme active sites. Since it is often difficult to predict which peptide sequence will have optimal inhibitory activity, selection from combinatorial peptide libraries is attractive. Additionally, the selection results may reveal new, previously unidentified components of the targeted pathway, which may, in turn, represent formidable targets for inhibition by small organic molecules.

Because short peptides are often quickly degraded in the cell, peptide libraries for in vivo selection are usually displayed inside a larger protein scaffold. For example, combinatorial hexadecameric peptide libraries were displayed (by insertion at the genetic level) into a surface loop of a biologically inert carrier protein (an inactive mutant of staphylococcal nuclease) [132]. From a @106-member yeast-transformed library, three peptides that inhibited the spindle checkpoint and 29 peptides that inhibited a mating pheromone signaling pathway (29 peptides) were identified by in vivo genetic selection in cleverly engineered yeast strains. The putative in vivo targets were subsequently identified using yeast two-hybrid analysis [133] and genetic dissection of the target pathways. A similar in vivo genetic selection approach was recently used to identify members from a combinatorial non-apeptide library that block intracellular dimerization of HIV-1 protease, albeit in E. coli [134].

Peptide combinatorial libraries can also be evaluated in vitro for binding or inhibitory activity. As opposed to in vivo peptide selections, in vitro selection has three particular advantages. First, no carrier protein is required to protect the short peptides from in vivo degradation. Of course, this freedom also increases the conformations available to the peptide, which may reduce the affinity of the peptide to a potential target [135, 136]. Secondly, much larger (@ 1013) peptide libraries can be assayed in vitro than in vivo (maximally 109, which is the practical upper limit because of plasmid transformation efficiencies [137,138]). Finally, unnatural amino

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