Using this method, 96 variant peptides are constructed on a microarray plate. These enhanced variants are screened against a desired protein for binding affinity and a map is produced displaying this affinity from low to high. The most successful variants can then be assembled into a new high affinity peptide, whose binding strength is the sum of the components.
This simple, algorithmic process can rapidly optimize random sequence peptides, improving their binding affinity by 100 to 1000 times. The method can also be used to improve the specificity of peptides, enabling the construction of binding agents able to attach to a given protein while excluding unwanted binding targets.
The MCP study asked whether a similar random peptide microarray could assist in the process of epitope mapping, in which the active binding regions of antibodies are identified. Epitope mapping is one method for determining if a given antibody is suitable for a particular application, and a faster, more cost-effective method would be of significant biomedical value.
For these experiments, antibodies of known epitope were screened against random sequence peptides on a microarray. High affinity peptides were identified and bioinformatics techniques were used to see if the random peptides could help identify the antibody epitopes.
Two techniques were applied; one in which high affinity random sequence peptides were compared side by side with the antibody epitopes they bound with and similarities statistically analyzed. The other method searched the peptides for signature "motifs"consisting of at least 7 amino acids (or two shorter motifs in combination). Lead author Rebecca Halperin and colleagues were able to show that statistically useful information on epitopes could inde
|Contact: Joe Caspermeyer|
Arizona State University