Michnik, M. L. | bioRxiv Science

bioRxiv2026

Genetically-encoded discovery and development of peptide-macrocycle imaging agents for PD-L1

The unique cell surface composition of tumor cells forms the molecular basis for many targeting and cell-based therapies. Here, we describe the development of novel peptide-based targeting agents for programmed death ligand 1 (PD-L1). Molecular imaging by peptide agents, coupled with therapeutic intervention using the same modality, represents a critical advancement in cancer management. Whole-body PET imaging of PD-L1 expression offers a superior alternative to traditional immuno-histochemistry, making PD-L1 radiodiagnostic imaging a highly sought-after modality. PD-L1 targeting modalities developed for clinical imaging to date can be divided into antibodies, protein domains, and small macrocyclic peptides with fewer than 20 amino acids. The latter modalities can address many challenges seen in antibody-based targeting vectors. All potent PD-L1 targeting peptide modalities reported to date rely extensively on non-canonical amino acids (ncAAs). Here, we report a comprehensive structure-activity relationship (SAR) analysis of a family of macrocycles discovered from an Sx2Cx8Cx2 phage-display library composed entirely of natural amino acids (x represents 19 natural amino acids excluding Cys). Using >10,000 variants in ''focused'' phage-display libraries, we optimized these macrocycles to achieve single-digit-nanomolar potency in protein- and cell-based assays. En route to this optimization, the activity of 216 synthetic macrocycles towards PD-L1 was measured in five distinct assays; two leads have been evaluated by imaging in tumor xenografts in mice, and the X-ray structure of one advanced lead in complex with PD-L1 has been determined at 2.78 [A] resolution. This publication demonstrates the development potential of PD-L1-targeting macrocycles that do not require extensive incorporation of ncAAs and the democratization of discovery by mapping the optimization path to single-digit-nanomolar assets for targeted radiopharmaceuticals via canonical phage-display technology.

pharmacology and toxicology↗

bioRxiv2026

Universal Baseline for in vitro Selection of Genetically Encoded Libraries

Genetically encoded (GE) libraries enable identification of high-affinity ligands for diverse molecular targets through iterative in vitro selection and DNA sequencing or next-generation sequencing (NGS). Despite their impact in therapeutic development, a systematic framework for evaluating reproducibility in GE-molecular discoveries remains limited. To aid such analysis, we introduce the concept of baseline response, which reproducibly partitions active and inactive members of in vitro selection. The baseline response is provided by spiking a random DNA-barcoded population. We calibrated the baseline concept using Bioconductor EdgeR differential enrichment (DE) analysis of NGS of phage-displayed selection on oligosaccharide chitin and hepatitis virus NS3a* protease as model targets. We further show that mixing discovery campaigns also offers an effective baseline: chitin-enriched peptides serve as a baseline for DE-analysis of NS3a* selection and NS3a*-enriched peptides serve as a baseline for chitin binders. We applied baseline-stratified DE-analysis to 66 parallel selections performed in 3-5 replicates across 22 extracellular targets, including HER1-3, EpCAM, CAIX, PD-L1, and eight integrin receptors. Automated DE-analysis across hundreds of NGS files produced hits validated in a secondary screen and yielded synthetic macrocyclic ligands with mid-nanomolar affinity confirmed in 2-3 biophysical assays. For PD-L1, we further demonstrated how baseline-calibrated NGS data provide decision-enabling information for optimization of peptide macrocycles to yield potent single-digit nanomolar ligands for the cell-surface receptor. We anticipate that baseline-based analyses of NGS data from in vitro selection procedures will offer a scalable framework for reproducible hit discovery and standardized analysis across diverse in vitro selection campaigns. Significance StatementGenetically encoded selection technologies such as phage, mRNA and ribosome display, have produced FDA-approved therapeutics and numerous clinical candidates. Yet reproducibility in such in vitro discovery systems is rarely evaluated against a defined experimental baseline. Here, we establish a universal baseline by spiking unrelated, DNA-barcoded peptide sequences into selection libraries and quantifying their binding alongside target-enriched populations. This composition-agnostic strategy enables rigorous normalization, confidence assessment, and cross-target comparison of molecular discovery outcomes. Our framework introduces practical standards for reproducibility and statistical benchmarking across genetically encoded display platforms.

biochemistry↗