Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space.

Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions, from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly and inexpensively toward improved properties is a common objective for protein engineers. Powerful high-throughput methods like fluorescent activated cell sorting and next-generation sequencing have dramatically improved directed evolution experiments. However, it is unclear how to best leverage these data to characterize protein fitness landscapes more completely and identify lead candidates. In this work, we develop a simple yet powerful framework to improve protein optimization by predicting continuous protein properties from simple directed evolution experiments using interpretable, linear machine learning models. Importantly, we find that these models, which use data from simple but imprecise experimental estimates of protein fitness, have predictive capabilities that approach more precise but expensive data. Evaluated across five diverse protein engineering tasks, continuous properties are consistently predicted from readily available deep sequencing data, demonstrating that protein fitness space can be reasonably well modeled by linear relationships among sequence mutations. To prospectively test the utility of this approach, we generated a library of stapled peptides and applied the framework to predict affinity and specificity from simple cell sorting data. We then coupled integer linear programming, a method to optimize protein fitness from linear weights, with mutation scores from machine learning to identify variants in unseen sequence space that have improved and co-optimal properties. This approach represents a versatile tool for improved analysis and identification of protein variants across many domains of protein engineering.

Optimizing Solid Tumor Treatment with Antibody-drug Conjugates Using Agent-Based Modeling: Considering the Role of a Carrier Dose and Payload Class.

INTRODUCTION: Antibody-drug conjugates (ADCs) show significant clinical efficacy in the treatment of solid tumors, but a major limitation to their success is poor intratumoral distribution. Adding a carrier dose improves both distribution and overall drug efficacy of ADCs, but the optimal carrier dose has not been outlined for different payload classes. OBJECTIVE: In this work, we study two carrier dose regimens: 1) matching payload potency to cellular delivery but potentially not reaching cells farther away from blood vessels, or 2) dosing to tumor saturation but risking a reduction in cell killing from a lower amount of payload delivered per cell. METHODS: We use a validated computational model to test four different payloads conjugated to trastuzumab to determine the optimal carrier dose as a function of target expression, ADC dose, and payload potency. RESULTS: We find that dosing to tumor saturation is more efficacious than matching payload potency to cellular delivery for all payloads because the increase in the number of cells targeted by the ADC outweighs the loss in cell killing on targeted cells. An important exception exists if the carrier dose reduces the payload uptake per cell to the point where all cell killing is lost. Likewise, receptor downregulation can mitigate the benefits of a carrier dose. CONCLUSIONS: Because tumor saturation and in vitro potency can be measured early in ADC design, these results provide insight into maximizing ADC efficacy and demonstrate the benefits of using simulation to guide ADC design.

Hitting Undruggable Targets: Viewing Stabilized Peptide Development through the Lens of Quantitative Systems Pharmacology.

Stabilized peptide therapeutics have the potential to hit currently undruggable targets, dramatically expanding the druggable genome. However, major obstacles to their development include poor intracellular delivery, rapid degradation, low target affinity, and membrane toxicity. With the emergence of multiple stabilization techniques and screening technologies, the high efficacy of various bioactive peptides has been demonstrated in vitro, albeit with limited success in vivo. We discuss here the chemical and pharmacokinetic barriers to achieving in vivo efficacy, analyze the characteristics of FDA-approved peptide drugs, and propose a developmental tool that considers the molecular properties of stabilized peptides in a comprehensive and quantitative manner to achieve the necessary rates for in vivo delivery to the target, efficacy, and ultimately clinical translation.

Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach.

In situ clinical measurement of receptor occupancy (RO) is challenging, particularly for solid tumors, necessitating the use of mathematical models that predict tumor receptor occupancy to guide dose decisions. A potency metric, average free tissue target to initial target ratio (AFTIR), was previously described based on a mechanistic compartmental model and is informative for near-saturating dose regimens. However, the metric fails at clinically relevant subsaturating antibody doses, as compartmental models cannot capture the spatial heterogeneity of distribution faced by some antibodies in solid tumors. Here we employ a partial differential equation (PDE) Krogh cylinder model to simulate spatiotemporal receptor occupancy and derive an analytical solution, a mechanistically weighted global AFTIR, that can better predict receptor occupancy regardless of dosing regimen. In addition to the four key parameters previously identified, a fifth key parameter, the absolute receptor density (targets/cell), is incorporated into the mechanistic AFTIR metric. Receptor density can influence equilibrium intratumoral drug concentration relative to whether the dose is saturating or not, thereby influencing the tumor penetration depth of the antibody. We derive mechanistic RO predictions based on distinct patterns of antibody tumor penetration, presented as a global AFTIR metric guided by a Thiele Modulus and a local saturation potential (drug equivalent of binding potential for positron emissions tomography imaging) and validate the results using rigorous global and local sensitivity analysis. This generalized AFTIR serves as a more accurate analytical metric to aid clinical dose decisions and rational design of antibody-based therapeutics without the need for extensive PDE simulations. SIGNIFICANCE STATEMENT: Determining antibody-receptor occupancy (RO) is critical for dosing decisions in pharmaceutical development, but direct clinical measurement of RO is often challenging and invasive, particularly for solid tumors. Significant efforts have been made to develop mathematical models and simplified analytical metrics of RO, but these often require complex computer simulations. Here we present a mathematically rigorous but simplified analytical model to accurately predict RO across a range of affinities, doses, drug, and tumor properties.

Generation of DAR1 Antibody-Drug Conjugates for Ultrapotent Payloads Using Tailored GlycoConnect Technology.

GlycoConnect technology can be readily adapted to provide different drug-to-antibody ratios (DARs) and is currently also evaluated in various clinical programs, including ADCT-601 (DAR2), MRG004a (DAR4), and XMT-1660 (DAR6). While antibody-drug conjugates (ADCs) typically feature a DAR2-8, it has become clear that ADCs with ultrapotent payloads (e.g., PBD dimers and calicheamicin) can only be administered to patients at low doses (<0.5 mg/kg), which may compromise effective biodistribution and may be insufficient to reach target receptor saturation in the tumor. Here, we show that GlycoConnect technology can be readily extended to DAR1 ADCs without the need of antibody re-engineering. We demonstrate that various ultrapotent, cytotoxic payloads are amenable to this methodology. In a follow-up experiment, HCC-1954 tumor spheroids were treated with either an AlexaFluor647-labeled DAR1 or DAR2 PBD-based ADC to study the effect on tumor penetration. Significant improvement of tumor spheroid penetration was observed for the DAR1 ADC compared to the DAR2 ADC at an equal payload dose, underlining the potential of a lower DAR for ADCs bearing ultrapotent payloads.

Simulating the Selection of Resistant Cells with Bystander Killing and Antibody Coadministration in Heterogeneous Human Epidermal Growth Factor Receptor 2-Positive Tumors.

Intratumoral heterogeneity is a leading cause of treatment failure resulting in tumor recurrence. For the antibody-drug conjugate (ADC) ado-trastuzumab emtansine (T-DM1), two major types of resistance include changes in human epidermal growth factor receptor 2 (HER2) expression and reduced payload sensitivity, which is often exacerbated by heterogenous HER2 expression and ADC distribution during treatment. ADCs with bystander payloads, such as trastuzumab-monomethyl auristatin E (T-MMAE), can reach and kill adjacent cells with lower receptor expression that cannot be targeted directly with the ADC. Additionally, coadministration of T-DM1 with its unconjugated antibody, trastuzumab, can improve distribution and minimize heterogeneous delivery. However, the effectiveness of trastuzumab coadministration and ADC bystander killing in heterogenous tumors in reducing the selection of resistant cells is not well understood. Here, we use an agent-based model to predict outcomes with these different regimens. The simulations demonstrate that both T-DM1 and T-MMAE benefit from trastuzumab coadministration for tumors with high average receptor expression (up to 70% and 40% decrease in average tumor volume, respectively), with greater benefit for nonbystander payloads. However, the benefit decreases as receptor expression is reduced, reversing at low concentrations (up to 360% and 430% increase in average tumor volume for T-DM1 and T-MMAE, respectively) for this mechanism that impacts both ADC distribution and efficacy. For tumors with intrinsic payload resistance, coadministration uniformly exhibits better efficacy than ADC monotherapy (50%-70% and 19%-36% decrease in average tumor volume for T-DM1 and T-MMAE, respectively). Finally, we demonstrate that several regimens select for resistant cells at clinical tolerable doses, which highlights the need to pursue other mechanisms of action for durable treatment responses. SIGNIFICANCE STATEMENT: Experimental evidence demonstrates heterogeneity in the distribution of both the antibody-drug conjugate and the target receptor in the tumor microenvironment, which can promote the selection of resistant cells and lead to recurrence. This study quantifies the impact of increasing the antibody dose and utilizing bystander payloads in heterogeneous tumors. Alternative cell-killing mechanisms are needed to avoid enriching resistant cell populations.

Directed Evolution Using Stabilized Bacterial Peptide Display.

Chemically stabilized peptides have attracted intense interest by academics and pharmaceutical companies due to their potential to hit currently "undruggable" targets. However, engineering an optimal sequence, stabilizing linker location, and physicochemical properties is a slow and arduous process. By pairing non-natural amino acid incorporation and cell surface click chemistry in bacteria with high-throughput sorting, we developed a method to quantitatively select high affinity ligands and applied the Stabilized Peptide Evolution by E. coli Display technique to develop disrupters of the therapeutically relevant MDM2-p53 interface. Through in situ stabilization on the bacterial surface, we demonstrate rapid isolation of stabilized peptides with improved affinity and novel structures. Several peptides evolved a second loop including one sequence (Kd = 1.8 nM) containing an i, i+4 disulfide bond. NMR structural determination indicated a bent helix in solution and bound to MDM2. The bicyclic peptide had improved protease stability, and we demonstrated that protease resistance could be measured both on the bacterial surface and in solution, enabling the method to test and/or screen for additional drug-like properties critical for biologically active compounds.

Oral Administration and Detection of a Near-Infrared Molecular Imaging Agent in an Orthotopic Mouse Model for Breast Cancer Screening.

Molecular imaging is advantageous for screening diseases such as breast cancer by providing precise spatial information on disease-associated biomarkers, something neither blood tests nor anatomical imaging can achieve. However, the high cost and risks of ionizing radiation for several molecular imaging modalities have prevented a feasible and scalable approach for screening. Clinical studies have demonstrated the ability to detect breast tumors using nonspecific probes such as indocyanine green, but the lack of molecular information and required intravenous contrast agent does not provide a significant benefit over current noninvasive imaging techniques. Here we demonstrate that negatively charged sulfate groups, commonly used to improve solubility of near-infrared fluorophores, enable sufficient oral absorption and targeting of fluorescent molecular imaging agents for completely noninvasive detection of diseased tissue such as breast cancer. These functional groups improve the pharmacokinetic properties of affinity ligands to achieve targeting efficiencies compatible with clinical imaging devices using safe, nonionizing radiation (near-infrared light). Together, this enables development of a "disease screening pill" capable of oral absorption and systemic availability, target binding, background clearance, and imaging at clinically relevant depths for breast cancer screening. This approach should be adaptable to other molecular targets and diseases for use as a new class of screening agents.

Population dynamics of islet-infiltrating cells in autoimmune diabetes.

Type-1 diabetes in the nonobese diabetic (NOD) mouse starts with an insulitis stage, wherein a mixed population of leukocytes invades the pancreas, followed by overt diabetes once enough insulin-producing ß-cells are destroyed by invading immunocytes. Little is known of the dynamics of lymphocyte movement into the pancreas during disease progression. We used the Kaede transgenic mouse, whose photoconvertible fluorescent reporter permits noninvasive labeling and subsequent tracking of immunocytes, to investigate pancreatic infiltrate dynamics and the requirement for antigen specificity during progression of autoimmune diabetes in the unmanipulated NOD mouse. Our results indicate that the insulitic lesion is very open with constant cell influx and active turnover, predominantly of B and T lymphocytes, but also CD11b(+)c(+) myeloid cells. Both naïve- and memory-phenotype lymphocytes trafficked to the insulitis, but Foxp3(+) regulatory T cells circulated less than their conventional CD4(+) counterparts. Receptor specificity for pancreatic antigens seemed irrelevant for this homing, because similar kinetics were observed in polyclonal and antigen-specific transgenic contexts. This "open" configuration was also observed after reversal of overt diabetes by anti-CD3 treatment. These results portray insulitis as a dynamic lesion at all stages of disease, continuously fed by a mixed influx of immunocytes, and thus susceptible to evolve over time in response to immunologic or environmental influences.

Tracking Antibody Distribution with Near-Infrared Fluorescent Dyes: Impact of Dye Structure and Degree of Labeling on Plasma Clearance.

Monoclonal antibodies labeled with near-infrared (NIR) fluorophores have potential use in disease detection, intraoperative imaging, and pharmacokinetic characterization of therapeutic antibodies in both the preclinical and clinical setting. Recent work has shown conjugation of NIR fluorophores to antibodies can potentially alter antibody disposition at a sufficiently high degree of labeling (DoL); however, other reports show minimal impact after labeling with NIR fluorophores. In this work, we label two clinically approved antibodies, Herceptin (trastuzumab) and Avastin (bevacizumab), with NIR dyes IRDye 800CW (800CW) or Alexa Fluor 680 (AF680), at 1.2 and 0.3 dyes/antibody and examine the impact of fluorophore conjugation on antibody plasma clearance and tissue distribution. At 0.3 DoL, AF680 conjugates exhibited similar clearance to unlabeled antibody over 17 days while 800CW conjugates diverged after 4 days, suggesting AF680 is a more suitable choice for long-term pharmacokinetic studies. At the 1.2 DoL, 800CW conjugates cleared faster than unlabeled antibodies after several hours, in agreement with other published reports. The tissue biodistribution for bevacizumab-800CW and -AF680 conjugates agreed well with literature reported biodistributions using radiolabels. However, the greater tissue autofluorescence at 680 nm resulted in limited detection above background at low (∼2 mg/kg) doses and 0.3 DoL for AF680, indicating that 800CW is more appropriate for short-term biodistribution measurements and intraoperative imaging. Overall, our work shows a DoL of 0.3 or less for non-site-specifically labeled antibodies (with a Poisson distribution) is ideal for limiting the impact of NIR fluorophores on antibody pharmacokinetics.

A Helix-Stabilizing Linker Improves Subcutaneous Bioavailability of a Helical Peptide Independent of Linker Lipophilicity.

Stabilized peptides address several limitations to peptide-based imaging agents and therapeutics such as poor stability and low affinity due to conformational flexibility. There is also active research in developing these compounds for intracellular drug targeting, and significant efforts have been invested to determine the effects of helix stabilization on intracellular delivery. However, much less is known about the impact on other pharmacokinetic parameters such as plasma clearance and bioavailability. We investigated the effect of different fluorescent helix-stabilizing linkers with varying lipophilicity on subcutaneous (sc) bioavailability using the glucagon-like peptide-1 (GLP-1) receptor ligand exendin as a model system. The stabilized peptides showed significantly higher protease resistance and increased bioavailability independent of linker hydrophilicity, and all subcutaneously delivered conjugates were able to successfully target the islets of Langerhans with high specificity. The lipophilic peptide variants had slower absorption and plasma clearance than their respective hydrophilic conjugates, and the absolute bioavailability was also lower likely due to the longer residence times in the skin. Their ease and efficiency make double-click helix stabilization chemistries a useful tool for increasing the bioavailability of peptide therapeutics, many of which suffer from rapid in vivo protease degradation. Helix stabilization using linkers of varying lipophilicity can further control sc absorption and clearance rates to customize plasma pharmacokinetics.

Dual-purpose linker for alpha helix stabilization and imaging agent conjugation to glucagon-like peptide-1 receptor ligands.

Peptides display many characteristics of efficient imaging agents such as rapid targeting, fast background clearance, and low non-specific cellular uptake. However, poor stability, low affinity, and loss of binding after labeling often preclude their use in vivo. Using glucagon-like peptide-1 receptor (GLP-1R) ligands exendin and GLP-1 as a model system, we designed a novel α-helix-stabilizing linker to simultaneously address these limitations. The stabilized and labeled peptides showed an increase in helicity, improved protease resistance, negligible loss or an improvement in binding affinity, and excellent in vivo targeting. The ease of incorporating azidohomoalanine in peptides and efficient reaction with the dialkyne linker enable this technique to potentially be used as a general method for labeling α helices. This strategy should be useful for imaging beta cells in diabetes research and in developing and testing other peptide targeting agents.

Reactive polymer enables efficient in vivo bioorthogonal chemistry.

There has been intense interest in the development of selective bioorthogonal reactions or "click" chemistry that can proceed in live animals. Until now however, most reactions still require vast surpluses of reactants because of steep temporal and spatial concentration gradients. Using computational modeling and design of pharmacokinetically optimized reactants, we have developed a predictable method for efficient in vivo click reactions. Specifically, we show that polymer modified tetrazines (PMT) are a key enabler for in vivo bioorthogonal chemistry based on the very fast and catalyst-free [4 + 2] tetrazine/trans-cyclooctene cycloaddition. Using fluorescent PMT for cellular resolution and (18)F labeled PMT for whole animal imaging, we show that cancer cell epitopes can be easily reacted in vivo. This generic strategy should help guide the design of future chemistries and find widespread use for different in vivo bioorthogonal applications, particularly in the biomedical sciences.

Accurate measurement of pancreatic islet beta-cell mass using a second-generation fluorescent exendin-4 analog.

The hallmark of type 1 diabetes is autoimmune destruction of the insulin-producing ß-cells of the pancreatic islets. Autoimmune diabetes has been difficult to study or treat because it is not usually diagnosed until substantial ß-cell loss has already occurred. Imaging agents that permit noninvasive visualization of changes in ß-cell mass remain a high-priority goal. We report on the development and testing of a near-infrared fluorescent ß-cell imaging agent. Based on the amino acid sequence of exendin-4, we created a neopeptide via introduction of an unnatural amino acid at the K(12) position, which could subsequently be conjugated to fluorophores via bioorthogonal copper-catalyzed click-chemistry. Cell assays confirmed that the resulting fluorescent probe (E4(×12)-VT750) had a high binding affinity (~3 nM). Its in vivo properties were evaluated using high-resolution intravital imaging, histology, whole-pancreas visualization, and endoscopic imaging. According to intravital microscopy, the probe rapidly bound to ß-cells and, as demonstrated by confocal microscopy, it was internalized. Histology of the whole pancreas showed a close correspondence between fluorescence and insulin staining, and there was an excellent correlation between imaging signals and ß-cell mass in mice treated with streptozotocin, a ß-cell toxin. Individual islets could also be visualized by endoscopic imaging. In short, E4(×12)-VT750 showed strong and selective binding to glucose-like peptide-1 receptors and permitted accurate measurement of ß-cell mass in both diabetic and nondiabetic mice. This near-infrared imaging probe, as well as future radioisotope-labeled versions of it, should prove to be important tools for monitoring diabetes, progression, and treatment in both experimental and clinical contexts.

Clinical translation of antibody drug conjugate dosing in solid tumors from preclinical mouse data.

Antibody drug conjugates (ADCs) have made impressive strides in the clinic in recent years with 11 Food and Drug Administration approvals, including 6 for the treatment of patients with solid tumors. Despite this success, the development of new agents remains challenging with a high failure rate in the clinic. Here, we show that current approved ADCs for the treatment of patients with solid tumors can all show substantial efficacy in some mouse models when administered at a similar weight-based [milligrams per kilogram (mg/kg)] dosing in mice that is tolerated in the clinic. Mechanistically, equivalent mg/kg dosing results in a similar drug concentration in the tumor and a similar tissue penetration into the tumor due to the unique delivery features of ADCs. Combined with computational approaches, which can account for the complex distribution within the tumor microenvironment, these scaling concepts may aid in the evaluation of new agents and help design therapeutics with maximum clinical efficacy.

Design of Crosslinking Antibodies For T-Cell Activation: Experimental and Computational Analysis of PD-1/CD137 Bispecific Agents.

Bispecific and multispecific agents have become increasingly utilized in cancer treatment and immunotherapy, yet their complex design parameters present a challenge in developing successful therapeutics. Bispecifics that crosslink receptors on two opposing cells can provide specific activation of a receptor only when these cells are in close spatial proximity, such as an immune cell and cancer cell in a tumor. These agents, including T cell activating bispecifics, can avoid off-tumor toxicity through activation only in the tumor microenvironment by utilizing a tumor target to cluster T-cell receptors for a selective costimulatory signal. Here, we investigate a panel of PD-1/CD137 targeted Humabody VH domains to determine the key factors for T cell activation, such as affinity, valency, expression level, domain orientation, and epitope location. Target expression is a dominant factor determining both specificity and potency of T cell activation. Given an intrinsic expression level, the affinity can be tuned to modulate the level of activation and IC50 and achieve specificity between low and high expression levels. Changing the epitope location and linker length showed minor improvements to activation at low expression levels, but increasing the valency for the target decreased activation at all expression levels. By combining non-overlapping epitopes for the target, we achieved higher receptor activation at low expression levels. A kinetic model was able to capture these trends, offering support for the mechanistic interpretation. This work provides a framework to quantify factors for T cell activation by cell-crosslinking bispecific agents and guiding principles for the design of new agents.

Impact of tissue penetration and albumin binding on design of T cell targeted bispecific agents.

Bispecific agents are a rapidly growing class of cancer therapeutics, and immune targeted bispecific agents have the potential to expand functionality well beyond monoclonal antibody agents. Humabodies⁎ are fully human single domain antibodies that can be linked in a modular fashion to form multispecific therapeutics. However, the effect of heterogeneous delivery on the efficacy of crosslinking bispecific agents is currently unclear. In this work, we utilize a PSMA-CD137 Humabody with an albumin binding half-life extension (HLE) domain to determine the impact of tissue penetration on T cell activating bispecific agents. Using heterotypic spheroids, we demonstrate that increased tissue penetration results in higher T cell activation at sub-saturating concentrations. Next, we tested the effect of two different albumin binding moieties on tissue distribution using albumin-specific HLE domains with varying affinities for albumin and a non-specific lipophilic dye. The results show that a specific binding mechanism to albumin does not influence tissue penetration, but a non-specific mechanism reduced both spheroid uptake and distribution in the presence of albumin. These results highlight the potential importance of tissue penetration on bispecific agent efficacy and describe how the design parameters including albumin-binding domains can be selected to maximize the efficacy of bispecific agents.

Improving Intracellular Delivery of an Antibody-Drug Conjugate Targeting Carcinoembryonic Antigen Increases Efficacy at Clinically Relevant Doses In Vivo.

Solid tumor antibody-drug conjugates (ADC) have experienced more clinical success in the last 5 years than the previous 18-year span since the first ADC approval in 2000. While recent advances in protein engineering, linker design, and payload variations have played a role in this success, high expression and readily internalized targets have also been crucial to solid tumor therapy. However, these factors are also paradoxically connected to poor tissue penetration and lower efficacy. Previous work shows that potent ADCs can benefit from slower internalization under subsaturating doses to improve tissue penetration and increase tumor response. In contrast, faster internalization is predicted to increase efficacy under higher, tumor saturating doses. In this work, the intracellular delivery of SN-38 conjugated to an anti-carcinoembryonic antigen (anti-CEA) antibody (Ab) is increased by coadministering a noncompeting (cross-linking) anti-CEA Ab to improve efficacy in a colorectal carcinoma animal model. The SN-38 payload enables broad tumor saturation with clinically-tolerable doses, and under these saturating conditions, using a second CEA receptor cross-linking Ab yields faster internalization, which increases tumor killing efficacy. Our spheroid results show indirect bystander killing can also occur, but the more efficient direct cell killing from targeted intracellular payload release drives a greater tumor response. These results provide a strategy to increase therapeutic effectiveness with improved intracellular delivery under tumor saturating doses with the potential to expand the ADC target repertoire.

In vivo Auto-tuning of Antibody-Drug Conjugate Delivery for Effective Immunotherapy using High-Avidity, Low-Affinity Antibodies.

Antibody-drug conjugates (ADCs) have experienced a surge in clinical approvals in the past five years. Despite this success, a major limitation to ADC efficacy in solid tumors is poor tumor penetration, which leaves many cancer cells untargeted. Increasing antibody doses or co-administering ADC with an unconjugated antibody can improve tumor penetration and increase efficacy when target receptor expression is high. However, it can also reduce efficacy in low-expression tumors where ADC delivery is limited by cellular uptake. This creates an intrinsic problem because many patients express different levels of target between tumors and even within the same tumor. Here, we generated High-Avidity, Low-Affinity (HALA) antibodies that can automatically tune the cellular ADC delivery to match the local expression level. Using HER2 ADCs as a model, HALA antibodies were identified with the desired HER2 expression-dependent competitive binding with ADCs in vitro. Multi-scale distribution of trastuzumab emtansine and trastuzumab deruxtecan co-administered with the HALA antibody were analyzed in vivo, revealing that the HALA antibody increased ADC tumor penetration in high-expression systems with minimal reduction in ADC uptake in low-expression tumors. This translated to greater ADC efficacy in immunodeficient mouse models across a range of HER2 expression levels. Furthermore, Fc-enhanced HALA antibodies showed improved Fc-effector function at both high and low expression levels and elicited a strong response in an immunocompetent mouse model. These results demonstrate that HALA antibodies can expand treatment ranges beyond high expression targets and leverage strong immune responses.

Rapid Evaluation of Staple Placement in Stabilized α Helices Using Bacterial Surface Display.

There are a wealth of proteins involved in disease that cannot be targeted by current therapeutics because they are inside cells, inaccessible to most macromolecules, and lack small-molecule binding pockets. Stapled peptides, where two amino acids are covalently linked, form a class of macrocycles that have the potential to penetrate cell membranes and disrupt intracellular protein-protein interactions. However, their discovery relies on solid-phase synthesis, greatly limiting queries into their complex design space involving amino acid sequence, staple location, and staple chemistry. Here, we use stabilized peptide engineering by Escherichia coli display (SPEED), which utilizes noncanonical amino acids and click chemistry for stabilization, to rapidly screen staple location and linker structure to accelerate peptide design. After using SPEED to confirm hotspots in the mdm2-p53 interaction, we evaluated different staple locations and staple chemistry to identify several novel nanomolar and sub-nanomolar antagonists. Next, we evaluated SPEED in the B cell lymphoma 2 (Bcl-2) protein family, which is responsible for regulating apoptosis. We report that novel staple locations modified in the context of BIM, a high affinity but nonspecific naturally occurring peptide, improve its specificity against the highly homologous proteins in the Bcl-2 family. These compounds demonstrate the importance of screening linker location and chemistry in identifying high affinity and specific peptide antagonists. Therefore, SPEED can be used as a versatile platform to evaluate multiple design criteria for stabilized peptide engineering.