In-solution affinity selection (AS) of large synthetic peptide libraries affords identification of binders to protein targets through access to an expanded chemical space. Standard affinity selection methods, however, can be...

Significance Erythrocyte-bound antigens can drive immune tolerance in an antigen-specific fashion. Exploiting this phenomenon, we developed a general strategy to promote antigen-specific tolerance by engineering peptide and protein antigens to bind erythrocytes. Here, we showed that a fully d -chiral peptide library can be selected in vivo for the de novo discovery of a robust erythrocyte binder, which we attached to peptide and protein antigens. An administration of engineered peptide and protein antigens mitigated antigen-specific inflammatory responses, suggesting the generalizability of this immune tolerance-induction strategy and validating our in vivo ligand selection technique.

Rapid discovery and development of serum-stable, selective, and high affinity peptide-based binders to protein targets are challenging. Angiotensin converting enzyme 2 (ACE2) has recently been identified as a cardiovascular disease biomarker and the primary receptor utilized by the severe acute respiratory syndrome coronavirus 2. In this study, we report the discovery of high affinity peptidomimetic binders to ACE2 via affinity selection-mass spectrometry (AS-MS). Multiple high affinity ACE2-binding peptides (ABP) were identified by selection from canonical and noncanonical peptidomimetic libraries containing 200 million members (dissociation constant, KD = 19–123 nM). The most potent noncanonical ACE2 peptide binder, ABP N1 (KD = 19 nM), showed enhanced serum stability in comparison with the most potent canonical binder, ABP C7 (KD = 26 nM). Picomolar to low nanomolar ACE2 concentrations in human serum were detected selectively using ABP N1 in an enzyme-linked immunosorbent assay. The discovery of serum-stable noncanonical peptidomimetics like ABP N1 from a single-pass selection demonstrates the utility of advanced AS-MS for accelerated development of affinity reagents to protein targets.

Peptide nucleic acids (PNAs) are potential antisense therapies for genetic, acquired, and viral diseases. Efficiently selecting candidate PNA sequences for synthesis and evaluation from a genome containing hundreds to thousands of options can be challenging. To facilitate this process, this work leverages machine learning (ML) algorithms and automated synthesis technology to predict PNA synthesis efficiency and guide rational PNA sequence design. The training data is collected from individual fluorenylmethyloxycarbonyl (Fmoc) deprotection reactions performed on a fully automated PNA synthesizer. The optimized ML model allows for 93% prediction accuracy and 0.97 Pearson's r. The predicted synthesis scores are validated to be correlated with the experimental high-performance liquid chromatography (HPLC) crude purities (correlation coefficient R 2 = 0.95). Furthermore, a general applicability of ML is demonstrated through designing synthetically accessible antisense PNA sequences from 102 315 predicted candidates targeting exon 44 of the human dystrophin gene, SARS-CoV-2, HIV, as well as selected genes associated with cardiovascular diseases, type II diabetes, and various cancers. Collectively, ML provides an accurate prediction of PNA synthesis quality and serves as a useful computational tool for informing PNA sequence design.

MicroRNAs (miRNAs) are implicated in the onset and progression of a variety of diseases. Modulating the expression of specific miRNAs is a possible option for therapeutic intervention. A promising strategy is the use of antisense oligonucleotides (ASOs) to inhibit miRNAs. Targeting ASOs to specific tissues can potentially lower the dosage and improve clinical outcomes by alleviating systemic toxicity. We leverage here automated peptide nucleic acid (PNA) synthesis technology to manufacture an anti-miRNA oligonucleotide (antagomir) covalently attached to a 12-mer peptide that binds to transferrin receptor 1. Our PNA-peptide conjugate is active in cells and animals, effectively inhibiting the expression of miRNA-21 both in cultured mouse cardiomyocytes and different mouse organs (heart, liver, kidney, lung, and spleen), while remaining well-tolerated in animals up to the highest tested dose of 30 mg/kg. Conjugating the targeting ligand to the PNA antagomir significantly improved inhibition of miRNA-21 in the heart by over 50% relative to the PNA alone. Given the modulation of biodistribution observed with our PNA-peptide conjugate, we anticipate this antagomir platform to serve as a starting point for pre-clinical development studies.Table of Contents EntrySynopsisConjugating T12, a peptide targeting transferrin receptor 1 (TfR1), to a peptide nucleic acid (PNA) oligonucleotide targeting microRNA-21 increases delivery of the PNA-T12 conjugate to cardiac tissue relative to PNA alone.