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.

A Nuclear Magnetic Resonance (NMR) Platform for Real-Time Metabolic Monitoring of Bioprocesses.

We present a Nuclear Magnetic Resonance (NMR) compatible platform for the automated real-time monitoring of biochemical reactions using a flow shuttling configuration. This platform requires a working sample volume of ∼11 mL and it can circulate samples with a flow rate of 28 mL/min., which makes it suitable to be used for real-time monitoring of biochemical reactions. Another advantage of the proposed low-cost platform is the high spectral resolution. As a proof of concept, we acquire 1H NMR spectra of waste orange peel, bioprocessed using Trichoderma reesei fungus, and demonstrate the real-time measurement capability of the platform. The measurement is performed over more than 60 h, with a spectrum acquired every 7 min, such that over 510 data points are collected without user intervention. The designed system offers high resolution, automation, low user intervention, and, therefore, time-efficient measurement per sample.

High-throughput screening for cell binding and repulsion peptides on multifunctionalized surfaces.

The adhesion of cells to the extracellular matrix engages cell surface receptors such as integrins, proteoglycans and other types of cell adhesion molecules such as CD44. To closely examine the determinants of cell adhesion, herein we describe the generation of high-density peptide arrays and test the growth of cells on these multifunctionalized surfaces. The peptide library used consists of over 11,000 different sequences, either random or derived from existing proteins. By applying this screen to SW620 mCherry colorectal cancer cells, we select for peptides with both maximum cell adhesion and maximum cell repulsion. All of these extreme properties are based on unique combinations of amino acids. Here, we identify peptides with maximum cell repulsion on secreted frizzled- and Dickkopf-related proteins. Peptides with strong cell repulsion are found at the poles of the TNF-alpha homotrimer. The formation of cellular patterns on alternating highly repulsive and adhesive peptides are examined. Our screen allows the identification of peptides suitable for biomedical and tissue engineering applications.

Screening for Primordial RNA-Peptide Interactions Using High-Density Peptide Arrays.

RNA-peptide interactions are an important factor in the origin of the modern mechanism of translation and the genetic code. Despite great progress in the bioinformatics of RNA-peptide interactions due to the rapid growth in the number of known RNA-protein complexes, there is no comprehensive experimental method to take into account the influence of individual amino acids on non-covalent RNA-peptide bonds. First, we designed the combinatorial libraries of primordial peptides according to the combinatorial fusion rules based on Watson-Crick mutations. Next, we used high-density peptide arrays to investigate the interaction of primordial peptides with their cognate homo-oligonucleotides. We calculated the interaction scores of individual peptide fragments and evaluated the influence of the peptide length and its composition on the strength of RNA binding. The analysis shows that the amino acids phenylalanine, tyrosine, and proline contribute significantly to the strong binding between peptides and homo-oligonucleotides, while the sum charge of the peptide does not have a significant effect. We discuss the physicochemical implications of the combinatorial fusion cascade, a hypothesis that follows from the amino acid partition used in the work.