Design and Evaluation of ZD06519, a Novel Camptothecin Payload for Antibody Drug Conjugates.

In recent years, the field of antibody drug conjugates (ADC) has seen a resurgence, largely driven by the clinical benefit observed in patients treated with ADCs incorporating camptothecin-based topoisomerase I inhibitor payloads. Herein, we present the development of a novel camptothecin ZD06519 (FD1), which has been specifically designed for its application as an ADC payload. A panel of camptothecin analogs with different substituents at the C-7 and C-10 positions of the camptothecin core was prepared and tested in vitro. Selected compounds spanning a range of potency and hydrophilicity were elaborated into drug-linkers, conjugated to trastuzumab, and evaluated in vitro and in vivo. ZD06519 was selected on the basis of its favorable properties as a free molecule and as an antibody conjugate, which include moderate free payload potency (∼1 nmol/L), low hydrophobicity, strong bystander activity, robust plasma stability, and high-monomeric ADC content. When conjugated to different antibodies using a clinically validated MC-GGFG-based linker, ZD06519 demonstrated impressive efficacy in multiple cell line-derived xenograft models and noteworthy tolerability in healthy mice, rats, and non-human primates.

Motion planning around obstacles with convex optimization.

From quadrotors delivering packages in urban areas to robot arms moving in confined warehouses, motion planning around obstacles is a core challenge in modern robotics. Planners based on optimization can design trajectories in high-dimensional spaces while satisfying the robot dynamics. However, in the presence of obstacles, these optimization problems become nonconvex and very hard to solve, even just locally. Thus, when facing cluttered environments, roboticists typically fall back to sampling-based planners that do not scale equally well to high dimensions and struggle with continuous differential constraints. Here, we present a framework that enables convex optimization to efficiently and reliably plan trajectories around obstacles. Specifically, we focus on collision-free motion planning with costs and constraints on the shape, the duration, and the velocity of the trajectory. Using recent techniques for finding shortest paths in Graphs of Convex Sets (GCS), we design a practical convex relaxation of the planning problem. We show that this relaxation is typically very tight, to the point that a cheap postprocessing of its solution is almost always sufficient to identify a collision-free trajectory that is globally optimal (within the parameterized class of curves). Through numerical and hardware experiments, we demonstrate that our planner, which we name GCS, can find better trajectories in less time than widely used sampling-based algorithms and can reliably design trajectories in high-dimensional complex environments.

Assessing for prenatal risk factors associated with infant neurologic morbidity using a multivariate analysis.

OBJECTIVE: To characterize the biochemical and demographic profiles of pregnant people with maternal immune activation (MIA) and identify the prenatal characteristics associated with neurologic morbidity in offspring. STUDY DESIGN: This was a retrospective cohort study of 602 mother-infant dyads with births between 2009 and 2010 in California. Multivariable logistic regression was used to build a MIA vulnerability profile including mid-pregnancy biochemical markers and maternal demographic characteristics, and its relationship with infant neurologic morbidity was examined. RESULTS: Of the 602 mother-infant dyads, 80 mothers and 61 infants had diagnoses suggestive of MIA and neurologic morbidity, respectively. Our model, including two demographic and seven biochemical characteristics, identified mothers with MIA with good performance (AUC:0.814; 95% CI:0.7-0.8). Three demographic and five inflammatory markers together identified 80% of infants with neurological morbidity (AUC:0.802, 95% CI:0.7-0.8). CONCLUSION: Inflammatory environment in mothers with pre-existing risk factors like obesity, poverty, and prematurity renders offspring more susceptible to neurologic morbidities.

Structure-Activity Relationships of Bis-Intercalating Peptides and Their Application as Antibody-Drug Conjugate Payloads.

Synthetic analogs based on the DNA bis-intercalating natural product peptides sandramycin and quinaldopeptin were investigated as antibody drug conjugate (ADC) payloads. Synthesis, biophysical characterization, and in vitro potency of 34 new analogs are described. Conjugation of an initial drug-linker derived from a novel bis-intercalating peptide produced an ADC that was hydrophobic and prone to aggregation. Two strategies were employed to improve ADC physiochemical properties: addition of a solubilizing group in the linker and the use of an enzymatically cleavable hydrophilic mask on the payload itself. All ADCs showed potent in vitro cytotoxicity in high antigen expressing cells; however, masked ADCs were less potent than payload matched unmasked ADCs in lower antigen expressing cell lines. Two pilot in vivo studies were conducted using stochastically conjugated DAR4 anti-FRα ADCs, which showed toxicity even at low doses, and site-specific conjugated (THIOMAB) DAR2 anti-cMet ADCs that were well tolerated and highly efficacious.

Stability Islands and the Folding Cooperativity of a Seven-Repeat Array from Topoisomerase V.

Cooperativity is a central feature of protein folding, but the thermodynamic and structural origins of cooperativity remain poorly understood. To quantify cooperativity, we measured guanidine-induced unfolding transitions of single helix-hairpin-helix (HhH)2 repeats and tandem pairs from a seven-repeat segment of Methanopyrus kandleri Topoisomerase V (Topo V) to determine intrinsic repeat stability and interfacial free energies between repeats. Most single-repeat constructs are folded and stable; moreover, several pairs have unfolding midpoints that exceed midpoints of the single repeats they comprise, demonstrating favorable coupling between repeats. Analyzing unfolding transitions with a modified Ising model, we find a broad range of intrinsic and interfacial free energies. Surprisingly, the G repeat, which lacks density in the crystal structure of Topo V without DNA, is the most stable repeat in the array. Using nuclear magnetic resonance spectroscopy, we demonstrate that the isolated G repeat adopts a canonical (HhH)2 fold and forms an ordered interface with the F-repeat but not with the H repeat. Using parameters from our paired Ising fit, we built a partition function for the seven-repeat array. The multistate unfolding transition predicted from this partition function is in excellent agreement with the experimental unfolding transition, providing strong justification for the nearest-neighbor model. The seven-repeat partition function predicts a native state in which three independent segments ("stability islands") of interacting repeats are separated by two unstable interfaces. We confirm this segmented architecture by measuring the unfolding transition of an equimolar mixture of these three separate polypeptides. This segmented structural organization may facilitate wrapping around DNA.

Generation and structure-activity relationships of novel imidazo-thienopyridine based TLR7 agonists: application as payloads for immunostimulatory antibody drug-conjugates.

Pairing immunostimulatory small molecules with the targeting capability of an antibody has emerged as a novel therapeutic modality with the potential to treat a variety of solid tumors. A series of compounds based on an imidazo-thienopyridine scaffold were synthesized and tested for their ability to agonize the innate immune sensors toll-like receptor 7 and 8 (TLR7/8). Structure-activity relationship (SAR) studies revealed that certain simple amino-substituents could enable TLR7 agonism at low nanomolar concentrations. Drug-linkers containing either payload 1 or 20h were conjugated to the HER2-targeting antibody trastuzumab at the interchain disulfide cysteine residues using a cleavable valine-citrulline dipeptide linker and stochastic thiol-maleimide chemistry. In vitro, these immune-stimulating antibody drug-conjugates (ADCs) were found to induce cytokine release in a murine splenocyte assay when co-cultured with the HER2-high NCI-N87 cancer cell line. In vivo, tumor regression was observed with a single dose in an NCI-N87 gastric carcinoma xenograft model in BALB/c nude mice.

Relay Intercropping Winter Cover Crop Effects on Spring Forage Potential of Sweet Maize Stover and Yearling Cattle Beef Performance.

Small landholders who grow sweet maize for the fresh produce market often also have cattle with little access to winter forage. Grazing cover crops with sweet maize stover can potentially increase the available nutritive value. A 3-year randomized complete block study with three replicates at New Mexico State University's Alcalde Sustainable Agriculture Science Center compared sweet maize (Zea mays var. rugosa) with sweet maize relay intercropped at the V7−9 stage with cereal rye (rye: Secale cereale L.) or hairy vetch (vetch: Vicia villosa Roth) for early spring grazing. Intercropping the rye or hairy vetch into sweet maize did not influence the sweet maize stover biomass yield or nutritive value after the winter. The dry matter (DM) yield and crude protein (CP) concentration of hairy vetch biomass was greater (p < 0.01) than rye biomass (1.46 vs. 2.94 Mg DM ha−1 for rye and hairy vetch, respectively, and 145 vs. 193 g CP kg−1 for rye and hairy vetch, respectively). Average daily gains by yearling cattle were not different when grazing maize−rye or maize−vetch. Producers should consider the spring planting timing of the primary crop and the initiation of grazing in the winter or the spring to maximize the utilization of the previous crop's residue (stover), as well as the cover crop itself.

Detecting Arsenic Contamination Using Satellite Imagery and Machine Learning.

Arsenic, a potent carcinogen and neurotoxin, affects over 200 million people globally. Current detection methods are laborious, expensive, and unscalable, being difficult to implement in developing regions and during crises such as COVID-19. This study attempts to determine if a relationship exists between soil's hyperspectral data and arsenic concentration using NASA's Hyperion satellite. It is the first arsenic study to use satellite-based hyperspectral data and apply a classification approach. Four regression machine learning models are tested to determine this correlation in soil with bare land cover. Raw data are converted to reflectance, problematic atmospheric influences are removed, characteristic wavelengths are selected, and four noise reduction algorithms are tested. The combination of data augmentation, Genetic Algorithm, Second Derivative Transformation, and Random Forest regression (R2=0.840 and normalized root mean squared error (re-scaled to [0,1]) = 0.122) shows strong correlation, performing better than past models despite using noisier satellite data (versus lab-processed samples). Three binary classification machine learning models are then applied to identify high-risk shrub-covered regions in ten U.S. states, achieving strong accuracy (=0.693) and F1-score (=0.728). Overall, these results suggest that such a methodology is practical and can provide a sustainable alternative to arsenic contamination detection.

BMP receptor blockade overcomes extrinsic inhibition of remyelination and restores neurovascular homeostasis.

Extrinsic inhibitors at sites of blood-brain barrier disruption and neurovascular damage contribute to remyelination failure in neurological diseases. However, therapies to overcome the extrinsic inhibition of remyelination are not widely available and the dynamics of glial progenitor niche remodelling at sites of neurovascular dysfunction are largely unknown. By integrating in vivo two-photon imaging co-registered with electron microscopy and transcriptomics in chronic neuroinflammatory lesions, we found that oligodendrocyte precursor cells clustered perivascularly at sites of limited remyelination with deposition of fibrinogen, a blood coagulation factor abundantly deposited in multiple sclerosis lesions. By developing a screen (OPC-X-screen) to identify compounds that promote remyelination in the presence of extrinsic inhibitors, we showed that known promyelinating drugs did not rescue the extrinsic inhibition of remyelination by fibrinogen. In contrast, bone morphogenetic protein type I receptor blockade rescued the inhibitory fibrinogen effects and restored a promyelinating progenitor niche by promoting myelinating oligodendrocytes, while suppressing astrocyte cell fate, with potent therapeutic effects in chronic models of multiple sclerosis. Thus, abortive oligodendrocyte precursor cell differentiation by fibrinogen is refractory to known promyelinating compounds, suggesting that blockade of the bone morphogenetic protein signalling pathway may enhance remyelinating efficacy by overcoming extrinsic inhibition in neuroinflammatory lesions with vascular damage.

Analysis of Tandem Repeat Protein Folding Using Nearest-Neighbor Models.

Cooperativity is a hallmark of protein folding, but the thermodynamic origins of cooperativity are difficult to quantify. Tandem repeat proteins provide a unique experimental system to quantify cooperativity due to their internal symmetry and their tolerance of deletion, extension, and in some cases fragmentation into single repeats. Analysis of repeat proteins of different lengths with nearest-neighbor Ising models provides values for repeat folding ([Formula: see text]) and inter-repeat coupling (ΔGi-1,i). In this article, we review the architecture of repeat proteins and classify them in terms of ΔGi and ΔGi-1,i; this classification scheme groups repeat proteins according to their degree of cooperativity. We then present various statistical thermodynamic models, based on the 1D-Ising model, for analysis of different classes of repeat proteins. We use these models to analyze data for highly and moderately cooperative and noncooperative repeat proteins and relate their fitted parameters to overall structural features.

Antarctic Water Masses and Ice Shelves: Visualizing the Physics.

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth's many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. The impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.

Racial and ethnic disparities in outcomes through 1 year of life in infants born prematurely: a population based study in California.

OBJECTIVES: To investigate racial/ethnic differences in rehospitalization and mortality rates among premature infants over the first year of life. STUDY DESIGN: A retrospective cohort study of infants born in California from 2011 to 2017 (n = 3,448,707) abstracted from a California Office of Statewide Health Planning and Development database. Unadjusted Kaplan-Meier tables and logistic regression controlling for health and sociodemographic characteristics were used to predict outcomes by race/ethnicity. RESULTS: Compared to White infants, Hispanic and Black early preterm infants were more likely to be readmitted; Black late/moderate preterm (LMPT) infants were more likely to be readmitted and to die after discharge; Hispanic and Black early preterm infants with BPD were more likely to be readmitted; Black LMPT infants with RDS were more likely to be readmitted and die after discharge. CONCLUSIONS: Racial/ethnic disparities in readmission and mortality rates exist for premature infants across several co-morbidities. Future studies are needed to improve equitability of outcomes.

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases.

A collection of programs for one-dimensional Ising analysis of linear repeat proteins with point substitutions.

A collection of programs is presented to analyze the thermodynamics of folding of linear repeat proteins using a 1D Ising model to determine intrinsic folding and interfacial coupling free energies. Expressions for folding transitions are generated for a series of constructs with different repeat numbers and are globally fitted to transitions for these constructs. These programs are designed to analyze Ising parameters for capped homopolymeric consensus repeat constructs as well as heteropolymeric constructs that contain point substitutions, providing a rigorous framework for analysis of the effects of mutation on intrinsic and directional (i.e., N- vs. C-terminal) interfacial coupling free-energies. A bootstrap analysis is provided to estimate parameter uncertainty as well as correlations among fitted parameters. Rigorous statistical analysis is essential for interpreting fits using the complex models required for Ising analysis of repeat proteins, especially heteropolymeric repeat proteins. Programs described here are available at https://github.com/barricklab-at-jhu/Ising_programs.

Newborn metabolic vulnerability profile identifies preterm infants at risk for mortality and morbidity.

BACKGROUND: Identifying preterm infants at risk for mortality or major morbidity traditionally relies on gestational age, birth weight, and other clinical characteristics that offer underwhelming utility. We sought to determine whether a newborn metabolic vulnerability profile at birth can be used to evaluate risk for neonatal mortality and major morbidity in preterm infants. METHODS: This was a population-based retrospective cohort study of preterm infants born between 2005 and 2011 in California. We created a newborn metabolic vulnerability profile wherein maternal/infant characteristics along with routine newborn screening metabolites were evaluated for their association with neonatal mortality or major morbidity. RESULTS: Nine thousand six hundred and thirty-nine (9.2%) preterm infants experienced mortality or at least one complication. Six characteristics and 19 metabolites were included in the final metabolic vulnerability model. The model demonstrated exceptional performance for the composite outcome of mortality or any major morbidity (AUC 0.923 (95% CI: 0.917-0.929). Performance was maintained across mortality and morbidity subgroups (AUCs 0.893-0.979). CONCLUSIONS: Metabolites measured as part of routine newborn screening can be used to create a metabolic vulnerability profile. These findings lay the foundation for targeted clinical monitoring and further investigation of biological pathways that may increase the risk of neonatal death or major complications in infants born preterm. IMPACT: We built a newborn metabolic vulnerability profile that could identify preterm infants at risk for major morbidity and mortality. Identifying high-risk infants by this method is novel to the field and outperforms models currently in use that rely primarily on infant characteristics. Utilizing the newborn metabolic vulnerability profile for precision clinical monitoring and targeted investigation of etiologic pathways could lead to reductions in the incidence and severity of major morbidities associated with preterm birth.

Author Correction: Transcriptional profiling and therapeutic targeting of oxidative stress in neuroinflammation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Transcriptional profiling and therapeutic targeting of oxidative stress in neuroinflammation.

Oxidative stress is a central part of innate immune-induced neurodegeneration. However, the transcriptomic landscape of central nervous system (CNS) innate immune cells contributing to oxidative stress is unknown, and therapies to target their neurotoxic functions are not widely available. Here, we provide the oxidative stress innate immune cell atlas in neuroinflammatory disease and report the discovery of new druggable pathways. Transcriptional profiling of oxidative stress-producing CNS innate immune cells identified a core oxidative stress gene signature coupled to coagulation and glutathione-pathway genes shared between a microglia cluster and infiltrating macrophages. Tox-seq followed by a microglia high-throughput screen and oxidative stress gene network analysis identified the glutathione-regulating compound acivicin, with potent therapeutic effects that decrease oxidative stress and axonal damage in chronic and relapsing multiple sclerosis models. Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune populations and may enable discovery of selective neuroprotective strategies.

Chemical synthesis of Shiga toxin subunit B using a next-generation traceless "helping hand" solubilizing tag.

The application of solid-phase peptide synthesis and native chemical ligation in chemical protein synthesis (CPS) has enabled access to synthetic proteins that cannot be produced recombinantly, such as site-specific post-translationally modified or mirror-image proteins (D-proteins). However, CPS is commonly hampered by aggregation and insolubility of peptide segments and assembly intermediates. Installation of a solubilizing tag consisting of basic Lys or Arg amino acids can overcome these issues. Through the introduction of a traceless cleavable linker, the solubilizing tag can be selectively removed to generate native peptide. Here we describe the synthesis of a next-generation amine-reactive linker N-Fmoc-2-(7-amino-1-hydroxyheptylidene)-5,5-dimethylcyclohexane-1,3-dione (Fmoc-Ddap-OH) that can be used to selectively introduce semi-permanent solubilizing tags ("helping hands") onto Lys side chains of difficult peptides. This linker has improved stability compared to its predecessor, a property that can increase yields for multi-step syntheses with longer handling times. We also introduce a new linker cleavage protocol using hydroxylamine that greatly accelerates removal of the linker. The utility of this linker in CPS was demonstrated by the preparation of the synthetically challenging Shiga toxin subunit B (StxB) protein. This robust and easy-to-use linker is a valuable addition to the CPS toolbox for the production of challenging synthetic proteins.

Synthesis of hydrophobic insulin-based peptides using a helping hand strategy.

The introduction of solid-phase peptide synthesis in the 1960s improved the chemical synthesis of both the A- and B-chains of insulin and insulin analogs. However, the subsequent elaboration of the synthetic peptides to generate active hormones continues to be difficult and complex due in part to the hydrophobicity of the A-chain. Over the past decade, several groups have developed different methods to enhance A-chain solubility. Two of the most popular methods are use of isoacyl dipeptides, and the attachment of an A-chain C-terminal pentalysine tag with a base-labile 4-hydroxymethylbenzoic acid linker. These methods have proven effective but can be limited in scope depending on the peptide sequence of a specific insulin. Herein we describe an auxiliary approach to enhance the solubility of insulin-based peptides by incorporating a tri-lysine tag attached to a cleavable Fmoc-Ddae-OH linker. Incorporation of this linker, or "helping hand", on the N-terminus greatly improved the solubility of chicken insulin A-chain, which is analogous to human insulin, and allowed for coupling of the insulin A- and B-chain via directed disulfide bond formation. After formation of the insulin heterodimer, the linker and tag could be easily removed using a hydrazine buffer (pH 7.5) to obtain an overall 12.6% yield based on A-chain. This strategy offers an efficient method to enhance the solubility of hydrophobic insulin-based peptides as well as other traditionally difficult peptides.