Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons.

Antigen processing is critical for therapeutic vaccines to generate epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often limits the quantity of epitopes released. We address this challenge using machine learning to ascribe a proteasomal degradation score to epitope sequences. Epitopes with varying scores were translocated into cells using nontoxic anthrax proteins. Epitopes with a low score show pronounced immunogenicity due to antigen processing, but epitopes with a high score show limited immunogenicity. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by these vaccines in clinical settings.

Development of an antibody fused with an antimicrobial peptide targeting Pseudomonas aeruginosa: A new approach to prevent and treat bacterial infections.

The increase in emerging drug resistant Gram-negative bacterial infections is a global concern. In addition, there is growing recognition that compromising the microbiota through the use of broad-spectrum antibiotics can impact long term patient outcomes. Therefore, there is the need to develop new bactericidal strategies to combat Gram-negative infections that would address these specific issues. In this study, we report and characterize one such approach, an antibody-drug conjugate (ADC) that combines (i) targeting the surface of a specific pathogenic organism through a monoclonal antibody with (ii) the high killing activity of an antimicrobial peptide. We focused on a major pathogenic Gram-negative bacterium associated with antibacterial resistance: Pseudomonas aeruginosa. To target this organism, we designed an ADC by fusing an antimicrobial peptide to the C-terminal end of the VH and/or VL-chain of a monoclonal antibody, VSX, that targets the core of P. aeruginosa lipopolysaccharide. This ADC demonstrates appropriately minimal levels of toxicity against mammalian cells, rapidly kills P. aeruginosa strains, and protects mice from P. aeruginosa lung infection when administered therapeutically. Furthermore, we found that the ADC was synergistic with several classes of antibiotics. This approach described in this study might result in a broadly useful strategy for targeting specific pathogenic microorganisms without further augmenting antibiotic resistance.

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons.

Antigen processing is critical for producing epitope peptides that are presented by HLA molecules for T cell recognition. Therapeutic vaccines aim to harness these epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often reduces vaccine efficacy through limiting the quantity of epitopes released. Here, we set out to improve antigen processing by harnessing protein degradation signals called degrons from the ubiquitin-proteasome system. We used machine learning to generate a computational model that ascribes a proteasomal degradation score between 0 and 100. Epitope peptides with varying degron activities were synthesized and translocated into cells using nontoxic anthrax proteins: protective antigen (PA) and the N-terminus of lethal factor (LFN). Immunogenicity studies revealed epitope sequences with a low score (<25) show pronounced T-cell activation but epitope sequences with a higher score (>75) provide limited activation. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity, through conserving the epitope region but varying the flanking sequence. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by vaccine therapeutics in clinical settings.

Peptide-based urinary monitoring of fibrotic nonalcoholic steatohepatitis by mass-barcoded activity-based sensors.

Noninvasive detection of nonalcoholic steatohepatitis (NASH), the progressive form of nonalcoholic fatty liver disease, promises to improve patient screening, accelerate drug trials, and reduce health care costs. On the basis of protease dysregulation of the biological pathways of fibrotic NASH, we developed the Glympse Bio Test System (GBTS) for multiplexed quantification of liver protease activity. GBTS-NASH comprises a mixture of 19 mass-barcoded PEGylated peptides that is administered intravenously and senses liver protease activity by releasing mass-barcoded reporters into urine for analysis by mass spectrometry. To identify a protease signature of NASH, transcriptomic analysis of 355 human liver biopsies identified a 13-protease panel that discriminated clinically relevant NASH ≥F2 fibrosis from F0-F1 with high classification accuracy across two independent patient datasets. We screened 159 candidate substrates to identify a panel of 19 peptides that exhibited high activity for our 13-protease panel. In the choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) mouse model, binary classifiers trained on urine samples discriminated fibrotic NASH from simple steatosis and healthy controls across a range of nondisease conditions and indicated disease regression upon diet change [area under receiver operating characteristics (AUROCs) > 0.97]. Using a hepatoprotective triple combination treatment (FXR agonist, ACC and ASK1 inhibitors) in a rat model of NASH, urinary classification distinguished F0-F1 from ≥F2 animals and indicated therapeutic response as early as 1 week on treatment (AUROCs >0.91). Our results support GBTS-NASH to diagnose fibrotic NASH via an infusion of peptides, monitor changes in disease severity, and indicate early treatment response.

Author Correction: In-solution enrichment identifies peptide inhibitors of protein-protein interactions.

In the version of this article originally published, the peptide sequences of compounds 90, 92 and 93 in Fig. 5b and Supplementary Table 7 contained several errors. In Fig. 5b, position 6 of compound 90 should be Tyr instead of Phe. In both Fig. 5b and Supplementary Table 7, position 9 of compounds 92 and 93 should be Gln instead of Glu. Additionally, the surname of co-author Anupam Bandyopadhyay was incorrectly spelled as Bandyopdhyay. The errors have been corrected in the HTML and PDF versions of the paper and in the Supplementary Information PDF.

In-solution enrichment identifies peptide inhibitors of protein-protein interactions.

The use of competitive inhibitors to disrupt protein-protein interactions (PPIs) holds great promise for the treatment of disease. However, the discovery of high-affinity inhibitors can be a challenge. Here we report a platform for improving the affinity of peptide-based PPI inhibitors using non-canonical amino acids. The platform utilizes size exclusion-based enrichment from pools of synthetic peptides (1.5-4 kDa) and liquid chromatography-tandem mass spectrometry-based peptide sequencing to identify high-affinity binders to protein targets, without the need for 'reporter' or 'encoding' tags. Using this approach-which is inherently selective for high-affinity binders-we realized gains in affinity of up to ~100- or ~30-fold for binders to the oncogenic ubiquitin ligase MDM2 or HIV capsid protein C-terminal domain, which inhibit MDM2-p53 interaction or HIV capsid protein C-terminal domain dimerization, respectively. Subsequent macrocyclization of select MDM2 inhibitors rendered them cell permeable and cytotoxic toward cancer cells, demonstrating the utility of the identified compounds as functional PPI inhibitors.

Antibody-Bactericidal Macrocyclic Peptide Conjugates To Target Gram-Negative Bacteria.

To combat antimicrobial infections, new active molecules are needed. Antimicrobial peptides, ever abundant in nature, are a fertile starting point to develop new antimicrobial agents but suffer from low stability, low specificity, and off-target toxicity. These drawbacks have limited their development. To overcome some of these limitations, we developed antibody-bactericidal macrocyclic peptide conjugates (ABCs), in which the antibody directs the bioactive macrocyclic peptide to the targeted Gram-negative bacteria. We used cysteine SN Ar chemistry to synthesize and systematically study a library of large (>30-mer) macrocyclic antimicrobial peptides (mAMPs) to discover variants with extended proteolytic stability in human serum and low hemolytic activity while maintaining bioactivity. We then conjugated, by using sortase A, these bioactive variants onto an Escherichia coli targeted monoclonal antibody. We found that these ABCs had minimized hemolytic activity and were able to kill E. coli at nanomolar concentrations. Our findings suggest macrocyclic peptides if fused to antibodies may facilitate the discovery of new agents to treat bacterial infections.

Xenoprotein engineering via synthetic libraries.

Chemical methods have enabled the total synthesis of protein molecules of ever-increasing size and complexity. However, methods to engineer synthetic proteins comprising noncanonical amino acids have not kept pace, even though this capability would be a distinct advantage of the total synthesis approach to protein science. In this work, we report a platform for protein engineering based on the screening of synthetic one-bead one-compound protein libraries. Screening throughput approaching that of cell surface display was achieved by a combination of magnetic bead enrichment, flow cytometry analysis of on-bead screens, and high-throughput MS/MS-based sequencing of identified active compounds. Direct screening of a synthetic protein library by these methods resulted in the de novo discovery of mirror-image miniprotein-based binders to a ∼150-kDa protein target, a task that would be difficult or impossible by other means.

Nitrogen Arylation for Macrocyclization of Unprotected Peptides.

We describe an efficient and mild method for the synthesis of macrocyclic peptides via nitrogen arylation from unprotected precursors. Various electrophiles and lysine-based nucleophiles were investigated and showed high-yielding product formation, even for a macrocyclization scan with 14 variants. We found that nitrogen-linked aryl products were more stable to base and oxidation when compared to thiol arylated species, thereby highlighting the utility of this methodology. Finally, N-aryl macrocyclization was performed on a p53 peptide inhibitor of MDM2 and resulted in identification of a nanomolar binder with improved proteolytic stability and cell permeability.

Magnetogenesis in water induced by a chemical analyte.

This Minireview aims to shed light on the emergent field of inducing a change in the magnetic properties of a solution-phase sample by exposing it to a chemical analyte. A considerable body of knowledge exists on materials that alter their magnetic characteristics after a change in the surrounding physical conditions and a number of cases even exist of solution-phase samples that do so under these same circumstances. However, examples of dissolved molecules or particles that react in this fashion under constant conditions and in response to an analyte are limited. Although some cases in organic solvents are discussed, the emphasis of this Minireview is on water. Our aim is to provide the reader with guidelines for designing new magnetogenic probes for the detection of the desired chemical analyte.

Magnetogenesis under physiological conditions with probes that report on (bio-)chemical stimuli.

Switched on: A molecular concept allows the generation of magnetism in an aqueous sample under the influence of a freshly added (bio-)chemical analyte. The analyte (a chemical reagent or enzyme) triggers the conversion of the probe, a diamagnetic chelate compound, into a paramagnetic compound (see scheme). The two probes prepared are easily accessible iron(II) chelates, and are operative at physiological conditions and/or in serum.

Awakening of a ferrous complex's electronic spin in an aqueous solution induced by a chemical stimulus.

A low-spin, macrocyclic iron(II) complex in an aqueous solution responds to the addition of a chemical reactant (dithionite) by transformation into a high-spin complex, detectable by measurement of the longitudinal relaxation time (T(1)) of surrounding water hydrogen nuclear spins. The initial compound does not modify T(1) of pure water at concentrations as high as 4 mM. The response is pH-dependent, and the complex is robust at a variety of conditions.

An electroneutral macrocyclic iron(II) complex that enhances MRI contrast in vivo.

The first example of a macrocyclic ferrous complex, where two tetrazolyl pendent arms compensate the charge of the metal center, is synthesized and examined for its capacity to enhance MRI contrast in vitro and in vivo in the mouse.