TDC-2: Multimodal Foundation for Therapeutic Science.

Therapeutics Data Commons (tdcommons.ai) is an open science initiative with unified datasets, AI models, and benchmarks to support research across therapeutic modalities and drug discovery and development stages. The Commons 2.0 (TDC-2) is a comprehensive overhaul of Therapeutic Data Commons to catalyze research in multimodal models for drug discovery by unifying single-cell biology of diseases, biochemistry of molecules, and effects of drugs through multimodal datasets, AI-powered API endpoints, new multimodal tasks and model frameworks, and comprehensive benchmarks. TDC-2 introduces over 1,000 multimodal datasets spanning approximately 85 million cells, pre-calculated embeddings from 5 state-of-the-art single-cell models, and a biomedical knowledge graph. TDC-2 drastically expands the coverage of ML tasks across therapeutic pipelines and 10+ new modalities, spanning but not limited to single-cell gene expression data, clinical trial data, peptide sequence data, peptidomimetics protein-peptide interaction data regarding newly discovered ligands derived from AS-MS spectroscopy, novel 3D structural data for proteins, and cell-type-specific protein-protein interaction networks at single-cell resolution. TDC-2 introduces multimodal data access under an API-first design using the model-view-controller paradigm. TDC-2 introduces 7 novel ML tasks with fine-grained biological contexts: contextualized drug-target identification, single-cell chemical/genetic perturbation response prediction, protein-peptide binding affinity prediction task, and clinical trial outcome prediction task, which introduce antigen-processing-pathway-specific, cell-type-specific, peptide-specific, and patient-specific biological contexts. TDC-2 also releases benchmarks evaluating 15+ state-of-the-art models across 5+ new learning tasks evaluating models on diverse biological contexts and sampling approaches. Among these, TDC-2 provides the first benchmark for context-specific learning. TDC-2, to our knowledge, is also the first to introduce a protein-peptide binding interaction benchmark.

Site-Specific Antibody Prodrugs via S-Arylation: a Bioconjugation Approach Toward Masked Tyrosine Analogues.

The utility of antibody therapeutics is hampered by potential cross-reactivity with healthy tissue. Over the past decade, significant advances have been made in the design of activatable antibodies, which increase, or create altogether, the therapeutic window of a parent antibody. Of these, antibody prodrugs (pro-antibodies) are masked antibodies that have advanced the most for therapeutic use. They are designed to reveal the active, parent antibody only when encountering proteases upregulated in the microenvironment of the targeted disease tissue, thereby minimizing off-target activity. However, current pro-antibody designs are relegated to fusion proteins that append masking groups restricted to the use of only canonical amino acids, offering excellent control of the site of introduction, but with no authority over where the masking group is installed other than the N-terminus of the antibody. Here, we present a palladium-based bioconjugation approach for the site-specific introduction of a masked tyrosine mimic in the complementary determining region of the FDA approved antibody therapeutic ipilimumab used as a model system. The approach enables the introduction of a protease cleavable group tethered to noncanonical polymers (polyethylene glycol (PEG)) resulting in 47-fold weaker binding to cells expressing CTLA-4, the target antigen of ipilimumab. Upon exposure to tumor-associated proteases, the masking group is cleaved, unveiling a tyrosine-mimic (dubbed hydroxyphenyl cysteine (HPC)) that restores (>90% restoration) binding affinity to its target antigen.

Reversibly Reactive Affinity Selection-Mass Spectrometry Enables Identification of Covalent Peptide Binders.

Covalent peptide binders have found applications as activity-based probes and as irreversible therapeutic inhibitors. Currently, there is no rapid, label-free, and tunable affinity selection platform to enrich covalent reactive peptide binders from synthetic libraries. We address this challenge by developing a reversibly reactive affinity selection platform termed ReAct-ASMS enabled by tandem high-resolution mass spectrometry (MS/MS) to identify covalent peptide binders to native protein targets. It uses mixed disulfide-containing peptides to build reversible peptide-protein conjugates that can enrich for covalent variants, which can be sequenced by MS/MS after reduction. Using this platform, we identified covalent peptide binders against two oncoproteins, human papillomavirus 16 early protein 6 (HPV16 E6) and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 protein (Pin1). The resulting peptide binders efficiently and selectively cross-link Cys58 of E6 at 37 °C and Cys113 of Pin1 at room temperature, respectively. ReAct-ASMS enables the identification of highly selective covalent peptide binders for diverse molecular targets, introducing an applicable platform to assist preclinical therapeutic development pipelines.

Assessing the Performance of Peptide Force Fields for Modeling the Solution Structural Ensembles of Cyclic Peptides.

Molecular dynamics simulation is a powerful tool for characterizing the solution structural ensembles of cyclic peptides. However, the ability of simulation to recapitulate experimental results and make accurate predictions largely depends on the force fields used. In our work here, we evaluate the performance of seven state-of-the-art force fields in recapitulating the experimental NMR results in water of 12 benchmark cyclic peptides, consisting of 6 cyclic pentapeptides, 4 cyclic hexapeptides, and 2 cyclic heptapeptides. The results show that RSFF2+TIP3P, RSFF2C+TIP3P, and Amber14SB+TIP3P exhibit similar and the best performance, all recapitulating the NMR-derived structure information on 10 cyclic peptides. Amber19SB+OPC successfully recapitulates the NMR-derived structure information on 8 cyclic peptides. In contrast, OPLS-AA/M+TIP4P, Amber03+TIP3P, and Amber14SBonlysc+GB-neck2 could only recapitulate the NMR-derived structure information on 5 cyclic peptides, the majority of which are not well-structured.

Automated Flow Peptide Synthesis Enables Engineering of Proteins with Stabilized Transient Binding Pockets.

Engineering at the amino acid level is key to enhancing the properties of existing proteins in a desired manner. So far, protein engineering has been dominated by genetic approaches, which have been extremely powerful but only allow for minimal variations beyond the canonical amino acids. Chemical peptide synthesis allows the unrestricted incorporation of a vast set of unnatural amino acids with much broader functionalities, including the incorporation of post-translational modifications or labels. Here we demonstrate the potential of chemical synthesis to generate proteins in a specific conformation, which would have been unattainable by recombinant protein expression. We use recently established rapid automated flow peptide synthesis combined with solid-phase late-stage modifications to rapidly generate a set of FK506-binding protein 51 constructs bearing defined intramolecular lactam bridges. This trapped an otherwise rarely populated transient pocket-as confirmed by crystal structures-which led to an up to 39-fold improved binding affinity for conformation-selective ligands and represents a unique system for the development of ligands for this rare conformation. Overall, our results show how rapid automated flow peptide synthesis can be applied to precision protein engineering.

How hydrophobicity, side chains, and salt affect the dimensions of disordered proteins.

Despite the generally accepted role of the hydrophobic effect as the driving force for folding, many intrinsically disordered proteins (IDPs), including those with hydrophobic content typical of foldable proteins, behave nearly as self-avoiding random walks (SARWs) under physiological conditions. Here, we tested how temperature and ionic conditions influence the dimensions of the N-terminal domain of pertactin (PNt), an IDP with an amino acid composition typical of folded proteins. While PNt contracts somewhat with temperature, it nevertheless remains expanded over 10-58°C, with a Flory exponent, ν, >0.50. Both low and high ionic strength also produce contraction in PNt, but this contraction is mitigated by reducing charge segregation. With 46% glycine and low hydrophobicity, the reduced form of snow flea anti-freeze protein (red-sfAFP) is unaffected by temperature and ionic strength and persists as a near-SARW, ν ~ 0.54, arguing that the thermal contraction of PNt is due to stronger interactions between hydrophobic side chains. Additionally, red-sfAFP is a proxy for the polypeptide backbone, which has been thought to collapse in water. Increasing the glycine segregation in red-sfAFP had minimal effect on ν. Water remained a good solvent even with 21 consecutive glycine residues (ν > 0.5), and red-sfAFP variants lacked stable backbone hydrogen bonds according to hydrogen exchange. Similarly, changing glycine segregation has little impact on ν in other glycine-rich proteins. These findings underscore the generality that many disordered states can be expanded and unstructured, and that the hydrophobic effect alone is insufficient to drive significant chain collapse for typical protein sequences.

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 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.

An organometallic swap strategy for bottlebrush polymer-protein conjugate synthesis.

Polymer-protein bioconjugation offers a powerful strategy to alter the physical properties of proteins, and various synthetic polymer compositions and architectures have been investigated for this purpose. Nevertheless, conjugation of molecular bottlebrush polymers (BPs) to proteins remains an unsolved challenge due to the large size of BPs and a general lack of methods to transform the chain ends of BPs into functional groups suitable for bioconjugation. Here, we present a strategy to address this challenge in the context of BPs prepared by "graft-through" ring-opening metathesis polymerization (ROMP), one of the most powerful methods for BP synthesis. Quenching ROMP of PEGylated norbornene macromonomers with an activated enyne terminator facilitates the transformation of the BP Ru alkylidene chain ends into Pd oxidative addition complexes (OACs) for facile bioconjugation. This strategy is shown to be effective for the synthesis of two BP-protein conjugates (albumin and ERG), setting the stage for a new class of BP-protein conjugates for future therapeutic and imaging applications.

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.

Enhanced Vaccine Immunogenicity Enabled by Targeted Cytosolic Delivery of Tumor Antigens into Dendritic Cells.

Molecular vaccines comprising antigen peptides and inflammatory cues make up a class of therapeutics that promote immunity against cancer and pathogenic diseases but often exhibit limited efficacy. Here, we engineered an antigen peptide delivery system to enhance vaccine efficacy by targeting dendritic cells and mediating cytosolic delivery. The delivery system consists of the nontoxic anthrax protein, protective antigen (PA), and a single-chain variable fragment (scFv) that recognizes the XCR1 receptor on dendritic cells (DCs). Combining these proteins enabled selective delivery of the N-terminus of lethal factor (LFN) into XCR1-positive cross-presenting DCs. Incorporating immunogenic epitope sequences into LFN showed selective protein translocation in vitro and enhanced the priming of antigen-specific T cells in vivo. Administering DC-targeted constructs with tumor antigens (Trp1/gp100) into mice bearing aggressive B16-F10 melanomas improved mouse outcomes when compared to free antigen, including suppressed tumor growth up to 58% at 16 days post tumor induction (P < 0.0001) and increased survival (P = 0.03). These studies demonstrate that harnessing DC-targeting anthrax proteins for cytosolic antigen delivery significantly enhances the immunogenicity and antitumor efficacy of cancer vaccines.

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.

Automated Fast-Flow Synthesis of Chromosome 9 Open Reading Frame 72 Dipeptide Repeat Proteins.

An expansion of the hexanucleotide (GGGGCC) repeat sequence in chromosome 9 open frame 72 (c9orf72) is the most common genetic mutation in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The mutation leads to the production of toxic dipeptide repeat proteins (DPRs) that induce neurodegeneration. However, the fundamental physicochemical properties of DPRs remain largely unknown due to their limited availability. Here, we synthesized the c9orf72 DPRs poly-glycine-arginine (poly-GR), poly-proline-arginine (poly-PR), poly-glycine-proline (poly-GP), poly-proline-alanine (poly-PA), and poly-glycine-alanine (poly-GA) using automated fast-flow peptide synthesis (AFPS) and achieved single-domain chemical synthesis of proteins with up to 200 amino acids. Circular dichroism spectroscopy of the synthetic DPRs revealed that proline-containing poly-PR, poly-GP, and poly-PA could adopt polyproline II-like helical secondary structures. In addition, structural analysis by size-exclusion chromatography indicated that longer poly-GP and poly-PA might aggregate. Furthermore, cell viability assays showed that human neuroblastoma cells cultured with poly-GR and poly-PR with longer repeat lengths resulted in reduced cell viability, while poly-GP and poly-PA did not, thereby reproducing the cytotoxic property of endogenous DPRs. This research demonstrates the potential of AFPS to synthesize low-complexity peptides and proteins necessary for studying their pathogenic mechanisms and constructing disease models.

Rapid Chemical Synthesis of Serine Protease Inhibitor Kazal-type 13 (SPINK13) Glycoform by a Combined Method with Glycan Insertion Strategy and Fast-Flow Fmoc SPPS.

Serine protease inhibitor Kazal type 13 (SPINK13) is a secreted protein that has been recently studied as a therapeutic drug and an interesting biomarker for cancer cells. Although SPINK13 has a consensus sequence (Pro-Asn-Val-Thr) for N-glycosylation, the existence of N-glycosylation and its functions are still unclear. In addition to this, the preparation of glycosylated SPINK 13 has not been examined by both the cell expression method and chemical synthesis. Herein we report the chemical synthesis of the scarce N-glycosylated form of SPINK13 by a rapid synthetic method combined with the chemical glycan insertion strategy and a fast-flow SPPS method. Glycosylated asparagine thioacid was designed to chemoselectively be inserted between two peptide segments where is the sterically bulky Pro-Asn(N-glycan)-Val junction by two coupling reactions which consist of diacyl disulfide coupling (DDC) and thioacid capture ligation (TCL). This insertion strategy successfully afforded the full-length polypeptide of SPINK13 within two steps from glycosylated asparagine thioacid. Because the two peptides used for this synthesis were prepared by a fast-flow SPPS, the total synthetic time of glycoprotein was considerably shortened. This synthetic concept enables us to repetitively synthesize a target glycoprotein easily. Folding experiments afforded well-folded structure confirmed by CD and disulfide bond map. Invasion assays of glycosylated SPINK13 and non-glycosylated SPINK13 with pancreatic cancer cells showed that non-glycosylated SPINK-13 was more potent than that of glycosylated SPINK13.

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.

Abiotic peptides as carriers of information for the encoding of small-molecule library synthesis.

Encoding small-molecule information in DNA has been leveraged to accelerate the discovery of ligands for therapeutic targets such as proteins. However, oligonucleotide-based encoding is hampered by inherent limitations of information stability and density. In this study, we establish abiotic peptides for next-generation information storage and apply them for the encoding of diverse small-molecule synthesis. The chemical stability of the peptide-based tag allows the use of palladium-mediated reactions to efficiently synthesize peptide-encoded libraries (PELs) with broad chemical diversity and high purity. We demonstrate the successful de novo discovery of small-molecule protein ligands from PELs by affinity selection against carbonic anhydrase IX and the oncogenic protein targets BRD4(1) and MDM2. Collectively, this work establishes abiotic peptides as carriers of information for the encoding of small-molecule synthesis, leveraged herein for the discovery of protein ligands.

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.