Resemblance-Ranking Peptide Library to Screen for Binders to Antibodies on a Peptidomic Scale.

A novel resemblance-ranking peptide library with 160,000 10-meric peptides was designed to search for selective binders to antibodies. The resemblance-ranking principle enabled the selection of sequences that are most similar to the human peptidome. The library was synthesized with ultra-high-density peptide arrays. As proof of principle, screens for selective binders were performed for the therapeutic anti-CD20 antibody rituximab. Several features in the amino acid composition of antibody-binding peptides were identified. The selective affinity of rituximab increased with an increase in the number of hydrophobic amino acids in a peptide, mainly tryptophan and phenylalanine, while a total charge of the peptide remained relatively small. Peptides with a higher affinity exhibited a lower sum helix propensity. For the 30 strongest peptide binders, a substitutional analysis was performed to determine dissociation constants and the invariant amino acids for binding to rituximab. The strongest selective peptides had a dissociation constant in the hundreds of the nano-molar range. The substitutional analysis revealed a specific hydrophobic epitope for rituximab. To show that conformational binders can, in principle, be detected in array format, cyclic peptide substitutions that are similar to the target of rituximab were investigated. Since the specific binders selected via the resemblance-ranking peptide library were based on the hydrophobic interactions that are widespread in the world of biomolecules, the library can be used to screen for potential linear epitopes that may provide information about the cross-reactivity of antibodies.

Renaissance Distribution for Statistically Failed Experiments.

Much of the experimental data, especially in life sciences, is considered to be useless if it demonstrates a large standard deviation from the mean value. The Renaissance distribution, as presented in this study, allows one to extract true values from such statistical data with large noise. To obtain proof of the Renaissance distribution, high-throughput synthesis of deep substitutions for a target amino acid sequence was performed, and the known epitope was identified in assay with human serum antibodies. In addition, the Renaissance distribution was shown to approach the epitope affinity maturation by the deep alanine substitution. The Renaissance distribution may have an impact in the development of novel specific drugs.

Combinatorial Synthesis of Macromolecular Arrays by Microchannel Cantilever Spotting (µCS).

Surface-bound microarrays of multiple oligo- and macromolecules (e.g., peptides, DNA) offer versatile options in biomedical applications like drug screening, DNA analysis, or medical diagnostics. Combinatorial syntheses of these molecules in situ can save significant resources in regard to processing time and material use. Furthermore, high feature densities are needed to enable high-throughput and low sample volumes as generally regarded in combinatorial chemistry. Here, a scanning-probe-lithography-based approach for the combinatorial in situ synthesis of macromolecules is presented in microarray format. Feature sizes below 40 µm allow for the creation of high-density arrays with feature densities of 62 500 features per cm2 . To demonstrate feasibility of this approach for biomedical applications, a multiplexed array of functional protein tags (HA- and FLAG-tag) is synthesized, and selective binding of respective epitope recognizing antibodies is shown. This approach uses only small amounts of base chemicals for synthesis and can be further parallelized, therefore, opening up a route to flexible, highly dense, and cost-effective microarrays.