Development of an α-Klotho Recognizing High-Affinity Peptide Probe from In-Solution Enrichment.

The kidney, parathyroid gland, and choroid plexus express the aging-related transmembrane protein α-Klotho, a coreceptor of the fibroblast growth factor 23 (FGF23) receptor complex. Reduced α-Klotho levels are correlated with chronic kidney disease and other age-related diseases, wherein they are released from membranes into circulation. Klotho's potential physiological action as a hormone is of current scientific interest. Part of the challenges associated with advancing these studies, however, has been the long-standing difficulty in detecting soluble α-Klotho in biofluids. Here, we describe the discovery of peptides that recognize α-Klotho with high affinity and selectivity by applying in-solution size-exclusion-based affinity selection-mass spectrometry (AS-MS). After two rounds of AS-MS and subsequent N-terminal modifications, the peptides improved their binding affinity to α-Klotho by approximately 2300-fold compared to the reported starting peptide Pep-10, previously designed based on the C-terminal region of FGF23. The lead peptide binders were shown to enrich α-Klotho from cell lysates and to label α-Klotho in kidney cells. Our results further support the utility of in-solution, label-free AS-MS protocols to discover peptide-based binders to target proteins of interest with high affinity and selectivity, resulting in functional probes for biological studies.

Mirror-image ligand discovery enabled by single-shot fast-flow synthesis of D-proteins.

Widespread adoption of mirror-image biological systems presents difficulties in accessing the requisite D-protein substrates. In particular, mirror-image phage display has the potential for high-throughput generation of biologically stable macrocyclic D-peptide binders with potentially unique recognition modes but is hindered by the individualized optimization required for D-protein chemical synthesis. We demonstrate a general mirror-image phage display pipeline that utilizes automated flow peptide synthesis to prepare D-proteins in a single run. With this approach, we prepare and characterize 12 D-proteins - almost one third of all reported D-proteins to date. With access to mirror-image protein targets, we describe the successful discovery of six macrocyclic D-peptide binders: three to the oncoprotein MDM2, and three to the E3 ubiquitin ligase CHIP. Reliable production of mirror-image proteins can unlock the full potential of D-peptide drug discovery and streamline the study of mirror-image biology more broadly.

Electrophile Scanning Reveals Reactivity Hotspots for the Design of Covalent Peptide Binders.

Protein-protein interactions (PPIs) are intriguing targets in drug discovery and development. Peptides are well suited to target PPIs, which typically present with large surface areas lacking distinct features and deep binding pockets. To improve binding interactions with these topologies and advance the development of PPI-focused therapeutics, potential ligands can be equipped with electrophilic groups to enable binding through covalent mechanisms of action. We report a strategy termed electrophile scanning to identify reactivity hotspots in a known peptide ligand and demonstrate its application in a model PPI. Cysteine mutants of a known ligand are used to install protein-reactive modifiers via a palladium oxidative addition complex (Pd-OAC). Reactivity hotspots are revealed by cross-linking reactions with the target protein under physiological conditions. In a model PPI with the 9-mer peptide antigen VL9 and major histocompatibility complex (MHC) class I protein HLA-E, we identify two reactivity hotspots that afford up to 87% conversion to the protein-peptide conjugate within 4 h. The reactions are specific to the target protein in vitro and dependent on the peptide sequence. Moreover, the cross-linked peptide successfully inhibits molecular recognition of HLA-E by CD94-NKG2A possibly due to structural changes enacted at the PPI interface. The results illustrate the potential application of electrophile scanning as a tool for rapid discovery and development of covalent peptide binders.

Discovery of reactive peptide inhibitors of human papillomavirus oncoprotein E6.

Human papillomavirus (HPV) infections account for nearly all cervical cancer cases, which is the fourth most common cancer in women worldwide. High-risk variants, including HPV16, drive tumorigenesis in part by promoting the degradation of the tumor suppressor p53. This degradation is mediated by the HPV early protein 6 (E6), which recruits the E3 ubiquitin ligase E6AP and redirects its activity towards ubiquitinating p53. Targeting the protein interaction interface between HPV E6 and E6AP is a promising modality to mitigate HPV-mediated degradation of p53. In this study, we designed a covalent peptide inhibitor, termed reactide, that mimics the E6AP LXXLL binding motif by selectively targeting cysteine 58 in HPV16 E6 with quantitative conversion. This reactide provides a starting point in the development of covalent peptidomimetic inhibitors for intervention against HPV-driven cancers.

Branched Multimeric Peptides as Affinity Reagents for the Detection of α-Klotho Protein.

α-Klotho, an aging-related protein found in the kidney, parathyroid gland, and choroid plexus, acts as an essential co-receptor with the fibroblast growth factor 23 receptor complex to regulate serum phosphate and vitamin D levels. Decreased levels of α-Klotho are a hallmark of age-associated diseases. Detecting or labeling α-Klotho in biological milieu has long been a challenge, however, hampering the understanding of its role. Here, we developed branched peptides by single-shot parallel automated fast-flow synthesis that recognize α-Klotho with improved affinity relative to their monomeric versions. These peptides were further shown to selectively label Klotho for live imaging in kidney cells. Our results demonstrate that automated flow technology enables rapid synthesis of complex peptide architectures, showing promise for future detection of α-Klotho in physiological settings.

In-Cell Penetration Selection-Mass Spectrometry Produces Noncanonical Peptides for Antisense Delivery.

Peptide-mediated delivery of macromolecules in cells has significant potential therapeutic benefits, but no therapy employing cell-penetrating peptides (CPPs) has reached the market after 30 years of investigation due to challenges in the discovery of new, more efficient sequences. Here, we demonstrate a method for in-cell penetration selection-mass spectrometry (in-cell PS-MS) to discover peptides from a synthetic library capable of delivering macromolecule cargo to the cytosol. This method was inspired by recent in vivo selection approaches for cell-surface screening, with an added spatial dimension resulting from subcellular fractionation. A representative peptide discovered in the cytosolic extract, Cyto1a, is nearly 100-fold more active toward antisense phosphorodiamidate morpholino oligomer (PMO) delivery compared to a sequence identified from a whole cell extract, which includes endosomes. Cyto1a is composed of d-residues and two non-α-amino acids, is more stable than its all-l isoform, and is less toxic than known CPPs with comparable activity. Pulse-chase and microscopy experiments revealed that while the PMO-Cyto1a conjugate is likely taken up by endosomes, it can escape to localize to the nucleus without nonspecifically releasing other endosomal components. In-cell PS-MS introduces a means to empirically discover unnatural synthetic peptides for subcellular delivery of therapeutically relevant cargo.

Rapid Single-Shot Synthesis of the 214 Amino Acid-Long N-Terminal Domain of Pyocin S2.

The impermeable outer membrane of Pseudomonas aeruginosa is bypassed by antibacterial proteins known as S-type pyocins. Because of their properties, pyocins are investigated as a potential new class of antimicrobials against Pseudomonas infections. Their production and modification, however, remain challenging. To address this limitation, we employed automated fast-flow peptide synthesis for the rapid production of a pyocin S2 import domain. The N-terminal domain sequence (PyS2NTD) was synthesized in under 10 h and purified to yield milligram quantities of the desired product. To our knowledge, the 214 amino acid sequence of PyS2NTD is among the longest peptides produced from a "single-shot" synthesis, i.e., made in a single stepwise route without the use of ligation techniques. Biophysical characterization of the PyS2NTD with circular dichroism was consistent with the literature reports. Fluorescently labeled PyS2NTD binds to P. aeruginosa expressing the cognate ferripyoverdine receptor and is taken up into the periplasm. This selective uptake was validated with confocal and super resolution microscopy, flow cytometry, and fluorescence recovery after photobleaching. These modified, synthetic S-type pyocin domains can be used to probe import mechanisms of P. aeruginosa and leveraged to develop selective antimicrobial agents that bypass the outer membrane.

Machine Learning Guides Peptide Nucleic Acid Flow Synthesis and Sequence Design.

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 R2 = 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.

A Tumor-Homing Peptide Platform Enhances Drug Solubility, Improves Blood-Brain Barrier Permeability and Targets Glioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common and deadliest malignant primary brain tumor, contributing significant morbidity and mortality among patients. As current standard-of-care demonstrates limited success, the development of new efficacious GBM therapeutics is urgently needed. Major challenges in advancing GBM chemotherapy include poor bioavailability, lack of tumor selectivity leading to undesired side effects, poor permeability across the blood-brain barrier (BBB), and extensive intratumoral heterogeneity. METHODS: We have previously identified a small, soluble peptide (BTP-7) that is able to cross the BBB and target the human GBM extracellular matrix (ECM). Here, we covalently attached BTP-7 to an insoluble anti-cancer drug, camptothecin (CPT). RESULTS: We demonstrate that conjugation of BTP-7 to CPT improves drug solubility in aqueous solution, retains drug efficacy against patient-derived GBM stem cells (GSC), enhances BBB permeability, and enables therapeutic targeting to intracranial GBM, leading to higher toxicity in GBM cells compared to normal brain tissues, and ultimately prolongs survival in mice bearing intracranial patient-derived GBM xenograft. CONCLUSION: BTP-7 is a new modality that opens the door to possibilities for GBM-targeted therapeutic approaches.

Palladium-Mediated Incorporation of Carboranes into Small Molecules, Peptides, and Proteins.

Carboranes represent a class of compounds with increasing therapeutic potential. However, few general approaches to readily embed carboranes into small molecules, peptides, and proteins are available. We report a strategy based on palladium-mediated C-X (X = C, S, and N) bond formation for the installation of carborane-containing moieties onto small molecules and peptides. We demonstrate the ability of Pd-based reagents with appropriate ligands to overcome the high hydrophobicity of the carborane group and enable chemoselective conjugation of cysteine residues at room temperature in aqueous buffer. Accordingly, carboranes can be efficiently installed on proteins by employing a combination of a bis-sulfonated biarylphosphine-ligated Pd reagent in an aqueous histidine buffer. This method is successfully employed on nanobodies, a fully synthetic affibody, and the antibody therapeutics trastuzumab and cetuximab. The conjugates of the affibody ZHER2 and the trastuzumab antibody retained binding to their target antigens. Conjugated proteins maintain their activity in cell-based functional assays in HER2-positive BT-474 cell lines. This approach enables the rapid incorporation of carborane moieties into small molecules, peptides, and proteins for further exploration in boron neutron capture therapy, which requires the targeted delivery of boron-dense groups.

Automated Flow Synthesis of Peptide-PNA Conjugates.

Antisense peptide nucleic acids (PNAs) have yet to translate to the clinic because of poor cellular uptake, limited solubility, and rapid elimination. Cell-penetrating peptides (CPPs) covalently attached to PNAs may facilitate clinical development by improving uptake into cells. We report an efficient technology that utilizes a fully automated fast-flow instrument to manufacture CPP-conjugated PNAs (PPNAs) in a single shot. The machine is rapid, with each amide bond being formed in 10 s. Anti-IVS2-654 PPNA synthesized with this instrument presented threefold activity compared to transfected PNA in a splice-correction assay. We demonstrated the utility of this approach by chemically synthesizing eight anti-SARS-CoV-2 PPNAs in 1 day. A PPNA targeting the 5' untranslated region of SARS-CoV-2 genomic RNA reduced the viral titer by over 95% in a live virus infection assay (IC50 = 0.8 µM). Our technology can deliver PPNA candidates to further investigate their potential as antiviral agents.

Rapid de novo discovery of peptidomimetic affinity reagents for human angiotensin converting enzyme 2.

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.

Cell-Penetrating d-Peptides Retain Antisense Morpholino Oligomer Delivery Activity.

Cell-penetrating peptides (CPPs) can cross the cell membrane to enter the cytosol and deliver otherwise nonpenetrant macromolecules such as proteins and oligonucleotides. For example, recent clinical trials have shown that a CPP attached to phosphorodiamidate morpholino oligomers (PMOs) resulted in higher muscle concentration, increased exon skipping, and dystrophin production relative to another study of the PMO alone in patients of Duchenne muscular dystrophy. Therefore, effective design and the study of CPPs could help enhance therapies for difficult-to-treat diseases. So far, the study of CPPs for PMO delivery has been restricted to predominantly canonical l-peptides. We hypothesized that mirror-image d-peptides could have similar PMO delivery activity as well as enhanced proteolytic stability, facilitating their characterization and quantification from biological milieu. We found that several enantiomeric peptide sequences could deliver a PMO-biotin cargo with similar activities while remaining stable against serum proteolysis. The biotin label allowed for affinity capture of fully intact PMO-peptide conjugates from whole-cell and cytosolic lysates. By profiling a mixture of these constructs in cells, we determined their relative intracellular concentrations. When combined with PMO activity, these concentrations provide a new metric for delivery efficiency, which may be useful for determining which peptide sequence to pursue in further preclinical studies.

Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers.

Therapeutic macromolecules such as proteins and oligonucleotides can be highly efficacious but are often limited to extracellular targets due to the cell's impermeable membrane. Cell-penetrating peptides (CPPs) are able to deliver such macromolecules into cells, but limited structure-activity relationships and inconsistent literature reports make it difficult to design effective CPPs for a given cargo. For example, polyarginine motifs are common in CPPs, promoting cell uptake at the expense of systemic toxicity. Machine learning may be able to address this challenge by bridging gaps between experimental data in order to discern sequence-activity relationships that evade our intuition. Our earlier data set and deep learning model led to the design of miniproteins (>40 amino acids) for antisense delivery. Here, we leveraged and expanded our model with data augmentation in the short CPP sequence space of the data set to extrapolate and discover short, low-arginine-content CPPs that would be easier to synthesize and amenable to rapid conjugation to desired cargo, and with minimal in vivo toxicity. The lead predicted peptide, termed P6, is as active as a polyarginine CPP for the delivery of an antisense oligomer, while having only one arginine side chain and 18 total residues. We determined the pentalysine motif and the C-terminal cysteine of P6 to be the main drivers of activity. The antisense conjugate was able to enhance corrective splicing in an animal model to produce functional eGFP in heart tissue in vivo while remaining nontoxic up to a dose of 60 mg/kg. In addition, P6 was able to deliver an enzyme to the cytosol of cells. Our findings suggest that, given a data set of long CPPs, we can discover by extrapolation short, active sequences that deliver antisense oligomers.

Deep learning to design nuclear-targeting abiotic miniproteins.

There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of abiotic nuclear-targeting miniproteins to traffic antisense oligomers to the nucleus of cells. We combined high-throughput experimentation with a directed evolution-inspired deep-learning approach in which the molecular structures of natural and unnatural residues are represented as topological fingerprints. The model is able to predict activities beyond the training dataset, and simultaneously deciphers and visualizes sequence-activity predictions. The predicted miniproteins, termed 'Mach', reach an average mass of 10 kDa, are more effective than any previously known variant in cells and can also deliver proteins into the cytosol. The Mach miniproteins are non-toxic and efficiently deliver antisense cargo in mice. These results demonstrate that deep learning can decipher design principles to generate highly active biomolecules that are unlikely to be discovered by empirical approaches.

Automated affinity selection for rapid discovery of peptide binders.

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 time-consuming, low-throughput, or provide hits that display low selectivity to the target. Here we report an automated bio-layer interferometry (BLI)-assisted affinity selection platform. When coupled with tandem mass spectrometry (MS), this method enables both rapid de novo discovery and affinity maturation of known peptide binders with high selectivity. The BLI-assisted AS-MS technology also features real-time monitoring of the peptide binding during the library selection process, a feature unattainable by current selection approaches. We show the utility of the BLI AS-MS platform toward rapid identification of novel nanomolar (dissociation constant, K D < 50 nM) non-canonical binders to the leukemia-associated oncogenic protein menin. To our knowledge, this is the first application of BLI to the affinity selection of synthetic peptide libraries. We believe our approach can significantly accelerate the use of synthetic peptidomimetic libraries in drug discovery.

An in vivo selection-derived d-peptide for engineering erythrocyte-binding antigens that promote immune tolerance.

When displayed on erythrocytes, peptides and proteins can drive antigen-specific immune tolerance. Here, we investigated a straightforward approach based on erythrocyte binding to promote antigen-specific tolerance to both peptides and proteins. We first identified a robust erythrocyte-binding ligand. A pool of one million fully d-chiral peptides was injected into mice, blood cells were isolated, and ligands enriched on these cells were identified using nano-liquid chromatography-tandem mass spectrometry. One round of selection yielded a murine erythrocyte-binding ligand with an 80 nM apparent dissociation constant, Kd We modified an 83-kDa bacterial protein and a peptide antigen derived from ovalbumin (OVA) with the identified erythrocyte-binding ligand. An administration of the engineered bacterial protein led to decreased protein-specific antibodies in mice. Similarly, mice given the engineered OVA-derived peptide had decreased inflammatory anti-OVA CD8+ T cell responses. These findings suggest that our tolerance-induction strategy is applicable to both peptide and protein antigens and that our in vivo selection strategy can be used for de novo discovery of robust erythrocyte-binding ligands.

Fully automated fast-flow synthesis of antisense phosphorodiamidate morpholino oligomers.

Rapid development of antisense therapies can enable on-demand responses to new viral pathogens and make personalized medicine for genetic diseases practical. Antisense phosphorodiamidate morpholino oligomers (PMOs) are promising candidates to fill such a role, but their challenging synthesis limits their widespread application. To rapidly prototype potential PMO drug candidates, we report a fully automated flow-based oligonucleotide synthesizer. Our optimized synthesis platform reduces coupling times by up to 22-fold compared to previously reported methods. We demonstrate the power of our automated technology with the synthesis of milligram quantities of three candidate therapeutic PMO sequences for an unserved class of Duchenne muscular dystrophy (DMD). To further test our platform, we synthesize a PMO that targets the genomic mRNA of SARS-CoV-2 and demonstrate its antiviral effects. This platform could find broad application not only in designing new SARS-CoV-2 and DMD antisense therapeutics, but also for rapid development of PMO candidates to treat new and emerging diseases.

A reactive peptide interface for site-selective cysteine bioconjugation.

We report aqueous, site-selective modification of proteins using a reactive peptide interface comprising a nine-residue sequence. This interface is the fastest (second-order rate constant of 152 M-1 s-1) catalyst-free, cysteine-based method for modifying proteins available to date, and enables near-quantitative labeling of antibodies in cell lysate.