The relationship between sequence and binding properties of an aptamer for immunoglobulin E (IgE) was investigated using custom DNA microarrays. Single, double and some triple mutations of the aptamer sequence were created to evaluate the importance of specific base composition on aptamer binding. The majority of the positions in the aptamer sequence were found to be immutable, with changes at these positions resulting in more than a 100-fold decrease in binding affinity. Improvements in binding were observed by altering the stem region of the aptamer, suggesting that it plays a significant role in binding. Results obtained for the various mutations were used to estimate the information content and the probability of finding a functional aptamer sequence by selection from a random library. For the IgE-binding aptamer, this probability is on the order of 10^-10 to 10^-9. Results obtained for the double and triple mutations also show that there are no compensatory mutations within the space defined by those mutations. Apparently, at least for this particular aptamer, the functional sequence space can be represented as a rugged landscape with sharp peaks defined by highly constrained base compositions. This makes the rational optimization of aptamer sequences using step-wise mutagenesis approaches very challenging.

There is an increasing awareness that health care must move from post-symptomatic treatment to presymptomatic intervention. An ideal system would allow regular inexpensive monitoring of health status using circulating antibodies to report on health fluctuations. Recently, we demonstrated that peptide microarrays can do this through antibody signatures (immunosignatures). Unfortunately, printed microarrays are not scalable. Here we demonstrate a platform based on fabricating microarrays (~10 M peptides per slide, 330,000 peptides per assay) on silicon wafers using equipment common to semiconductor manufacturing. The potential of these microarrays for comprehensive health monitoring is verified through the simultaneous detection and classification of six different infectious diseases and six different cancers. Besides diagnostics, these high-density peptide chips have numerous other applications both in health care and elsewhere.

Cells routinely compartmentalize enzymes for enhanced efficiency of their metabolic pathways. Here we report a general approach to construct DNA nanocaged enzymes for enhancing catalytic activity and stability. Nanocaged enzymes are realized by self-assembly into DNA nanocages with well-controlled stoichiometry and architecture that enabled a systematic study of the impact of both encapsulation and proximal polyanionic surfaces on a set of common metabolic enzymes. Activity assays at both bulk and single-molecule levels demonstrate increased substrate turnover numbers for DNA nanocage-encapsulated enzymes. Unexpectedly, we observe a significant inverse correlation between the size of a protein and its activity enhancement. This effect is consistent with a model wherein distal polyanionic surfaces of the nanocage enhance the stability of active enzyme conformations through the action of a strongly bound hydration layer. We further show that DNA nanocages protect encapsulated enzymes against proteases, demonstrating their practical utility in functional biomaterials and biotechnology.

Background: Chemistry and particularly enzymology at surfaces is a topic of rapidly growing interest, both in terms of its role in biological systems and its application in biocatalysis. Existing protein immobilization approaches, including noncovalent or covalent attachments to solid supports, have difficulties in controlling protein orientation, reducing nonspecific absorption and preventing protein denaturation. New strategies for enzyme immobilization are needed that allow the precise control over orientation and position and thereby provide optimized activity.

Methodology/Principal Findings: A method is presented for utilizing peptide ligands to immobilize enzymes on surfaces with improved enzyme activity and stability. The appropriate peptide ligands have been rapidly selected from high-density arrays and when desirable, the peptide sequences were further optimized by single-point variant screening to enhance both the affinity and activity of the bound enzyme. For proof of concept, the peptides that bound to β-galactosidase and optimized its activity were covalently attached to surfaces for the purpose of capturing target enzymes. Compared to conventional methods, enzymes immobilized on peptide-modified surfaces exhibited higher specific activity and stability, as well as controlled protein orientation.

Conclusions/Significance: A simple method for immobilizing enzymes through specific interactions with peptides anchored on surfaces has been developed. This approach will be applicable to the immobilization of a wide variety of enzymes on surfaces with optimized orientation, location and performance, and provides a potential mechanism for the patterned self-assembly of multiple enzymes on surfaces.