Biotinyl-CBP501 Affinity Peptide

Peptides, as a large group of molecules, are composed of amino acid residues and can be divided into linear or cyclic peptides according to the structure. Over 13,000 molecules of natural peptides have been found and many of them have been well studied. In artificial peptide libraries, the number of peptide diversity could be up to 1 × 1013. Peptides have more complex structures and higher affinity to target proteins comparing with small molecular compounds. Recently, the development of targeting cancer immune checkpoint (CIP) inhibitors is having a very important role in tumor therapy. Peptides targeting ligands or receptors in CIP have been designed based on three-dimensional structures of target proteins or directly selected by random peptide libraries in biological display systems. Most of these targeting peptides work as inhibitors of protein-protein interaction and improve CD8+ cytotoxic T-lymphocyte (CTL) activation in the tumor microenvironment, for example, PKHB1, Ar5Y4 and TPP1. Peptides could be designed to regulate CIP protein degradation in vivo, such as PD-LYSO and PD-PALM. Besides its use in developing therapeutic drugs for targeting CIP, targeting peptides could be used in drug's targeted delivery and diagnosis in tumor immune therapy.

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.

Designed armadillo repeat proteins (dArmRPs) are modular peptide binders composed of N- and C-terminal capping repeats Y and A and a variable number of internal modules M that each specifically recognize two amino acids of the target peptide. Complementary fragments of dArmRPs obtained by splitting the protein between helices H1 and H2 of an internal module show conditional and specific assembly only in the presence of a target peptide (Michel, E., Plückthun, A., and Zerbe, O. (2018). Peptide-guided assembly of repeat protein fragments. Angew. Chem. Int. Ed. 57, 4576-4579). Here, we investigate dArmRP fragments that already spontaneously assemble with high affinity, e.g. those obtained from splits between entire modules or between helices H2 and H3. We find that the interaction of the peptide with the assembled fragments induces distal conformational rearrangements that suggest an induced fit on a global protein level. A population analysis of an equimolar mixture of an N-terminal and three C-terminal fragments with various affinities for the target peptide revealed predominant assembly of the weakest peptide binder. However, adding a target peptide to this mixture altered the population of the protein complexes such that the combination with the highest affinity for the peptide increased and becomes predominant when adding excess of peptide, highlighting the feasibility of peptide-induced enrichment of best binders from inter-modular fragment mixtures.