In earlier work, Johnston's group showed that high-affinity antibody mimics can be produced synthetically by simple means. Their technique turns the traditional production approach on its head. Rather than beginning with a given protein and trying to generate a corresponding antibody, the new method involves building a synthetic antibody first, later determining the protein it effectively binds with, by screening it against a library of potential protein mates.
The first step in this process is to generate random strings of 20 amino acids. Roughly 10,000 such random peptides are then spotted onto a glass microarray slide. The protein one is seeking an antibody to is screened against this random sequence array and peptides with high binding affinity are identified. Two such peptides can be linked together to form a synbody, whose binding affinity is the product of each separate peptide. In this way, two weakly binding peptides join forces to form a high affinity unit, useful for investigations into the proteome, the vast domain of proteins essential to virtually all biological processes.
In the PloS ONE study, lead author Matthew Greving and his collegues describe a strategy for further refinement of binding affinity in random sequence peptides. "The problem," Johnston explains, is that the microarray contains about 10,000 peptides, but that is less than a quadrillionth of the possible peptides by sequence. So we're sampling a very small part of the sequence space. " A consequence of this is that the probability of generating a 20 amino acid sequence, that binds with optimal affinity, is pretty low.
To improve sequence affinity, a lead sequence is first selected. In the study, one such sequence was the 17 amino acid peptide TNF-1, a key regulator of immune cells. The lead sequence is then used as a template f
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Arizona State University