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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models

The co-expression extrapolation (COXEN) method has been successfully used in multiple studies to select genes for predicting the response of tumor cells to a specific drug treatment. Here, we enhance the COXEN method to select genes that are predictive of the efficacies of multiple drugs for building general drug response prediction models that are not specific to a particular drug. The enhanced COXEN method first ranks the genes according to their prediction power for each individual drug and then takes a union of top predictive genes of all the drugs, among which the algorithm further selects genes whose co-expression patterns are well preserved between cancer cases for building prediction models. We apply the proposed method on benchmark in vitro drug screening datasets and compare the performance of prediction models built based on the genes selected by the enhanced COXEN method to that of models built on genes selected by the original COXEN method and randomly picked genes. Models built with the enhanced COXEN method always present a statistically significantly improved prediction performance (adjusted p-value ≤ 0.05). Our results demonstrate the enhanced COXEN method can dramatically increase the power of gene expression data for predicting drug response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1- 13 C]Pyruvate

Hyperpolarized NMR has emerged as a powerful analytical technique to significantly enhance targeted NMR signals, improving the sensitivity for investigations of unique chemical and biological dynamics. Here, we demonstrate the use of a hyperpolarization strategy based on Signal Amplification By Reversible Exchange (SABRE) to generate highly reproducible doses of a hyperpolarized [1- 13 C]pyruvate probe for benchtop characterization of yeast metabolism. This method allows rapid, scalable, and benchtop preparation of biocompatible hyperpolarized solutions suitable for live-cell experiments. We show that this production can be dove-tailed into a modular, compact workflow to characterize real-time metabolism in cell cultures, using Saccharomyces cerevisiae (Baker’s yeast) as a model organism. With high temporal resolution, we show that this method can resolve the conversion of hyperpolarized [1- 13 C]pyruvate into oxidative decarboxylation products CO 2 and bicarbonate. This conversion exhibits sustained and detectable metabolic activity for over 300 s after introduction of the agent to the cells. We model the metabolite kinetics to show decarboxylation activity and derive estimates of the pH over time from the CO 2 and bicarbonate (carbonic acid buffer system) equilibrium to probe changes in the cellular environment during active metabolism. These results highlight the utility of benchtop SABRE-hyperpolarized [1- 13 C]pyruvate as a scalable, specific probe for metabolic phenotyping of living cells using compact, low-cost instrumentation well-suited for future high-throughput applications across microbial engineering, drug response profiling, and dynamic metabolic screening.

fungi↗
DOE OSTI2024

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Synthesis, Characterization, and Biological Activity of Hybrid Thiosemicarbazone–Alkylthiocarbamate Metal Complexes

A series of hybrid ligands (H 2 L 1 –H 2 L 3 ) derived from 4-methyl-3-thiosemicarbazide and hydrazinecarbothioic acid O-alkyl esters were synthesized and characterized by NMR. The ligands were chelated with copper (4–6), nickel (7–9), and zinc (10–12) and characterized by spectroscopy, electrochemistry, and single crystal X-ray crystallography. The chelated metals displayed substantial anodic shifts in the Cu II/I reduction potential of ~160 mV relative to their bis(thiosemicarbazone) analogues. The metal chelates 4–12 were evaluated for potential anticancer activity by MTT assays, and selected results were confirmed by clonogenic and trypan blue assays. The copper derivatives 4 and 6 were found to have potent and cancer-selective antiproliferative effects, with GI 50 values less than 100 nM in A549 lung adenocarcinoma cells compared with at least 20-fold less activity in IMR90 nonmalignant lung fibroblasts. In comparison, the nickel complexes were much less active and had little cancer-selectivity. Varying by ligand, the zinc complexes were less potent or had comparable activity compared to that of the corresponding copper complex. UV–visible spectroscopy indicated that zinc complex 10 was transmetalated in the presence of equimolar copper, whereas nickel complex 7 was not. Copper complexes 4 and 6 were also assessed in the NCI60 screen and were found to have cytotoxic activity against most solid tumor cell lines. In MTT assays, 4 and 6 were substantially more active against A549 cancer cells than Cu(ATSM) and were more cancer-selective (for A549 compared to IMR-90) than Cu(GTSM). Finally, our results suggest that hybrid thiosemicarbazone–alkylthiocarbamate copper complexes have potential for development as new anticancer agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Discovery of AG-270, a First-in-Class Oral MAT2A Inhibitor for the Treatment of Tumors with Homozygous MTAP Deletion

The metabolic enzyme methionine adenosyltransferase 2A (MAT2A) was recently implicated as a synthetic lethal target in cancers with deletion of the methylthioadenosine phosphorylase (MTAP) gene, which is adjacent to the CDKN2A tumor suppressor and codeleted with CDKN2A in approximately 15% of all cancers. Previous attempts to target MAT2A with small-molecule inhibitors identified cellular adaptations that blunted their efficacy. Here, we report the discovery of highly potent, selective, orally bioavailable MAT2A inhibitors that overcome these challenges. Fragment screening followed by iterative structure-guided design enabled >10 000-fold improvement in potency of a family of allosteric MAT2A inhibitors that are substrate noncompetitive and inhibit release of the product, S-adenosyl methionine (SAM), from the enzyme’s active site. We demonstrate that potent MAT2A inhibitors substantially reduce SAM levels in cancer cells and selectively block proliferation of MTAP-null cells both in tissue culture and xenograft tumors. These data supported progressing AG-270 into current clinical studies (ClinicalTrials.gov NCT03435250).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

The human gamma-herpesviruses Epstein–Barr virus (EBV) (HHV-4) and Kaposi’s sarcoma-associated herpesvirus (KSHV) (HHV-8) are responsible for a number of diseases, including various types of cancer. Epstein–Barr nuclear antigen 1 (EBNA1) from EBV and latency-associated nuclear antigen (LANA) from KSHV are viral-encoded DNA-binding proteins that are essential for the replication and maintenance of their respective viral genomes during latent, oncogenic infection. As such, EBNA1 and LANA are attractive targets for the development of small-molecule inhibitors. To this end, we performed a biophysical screen of EBNA1 and LANA using a fragment library by saturation transfer difference (STD)–NMR spectroscopy and surface plasmon resonance (SPR). We identified and validated a number of unique fragment hits that bind to EBNA1 or LANA. We also determined the high-resolution crystal structure of one fragment bound to EBNA1. Results from this screening cascade provide new chemical starting points for the further development of potent inhibitors for this class of viral proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An in vitro BRAF activation assay elucidates molecular mechanisms driving disassembly of the autoinhibited BRAF state

The RAF kinases (ARAF, BRAF, and CRAF) are essential components of the RAS-ERK signaling pathway, which controls vital cellular processes and is frequently dysregulated in human disease. Notably, mutations that alter BRAF function are prominent drivers of human cancer and certain RASopathy disorders, making BRAF an important target for therapeutic intervention. Despite extensive research, several aspects of BRAF regulation remain unclear. In this study, we developed an in vitro BRAF activation assay using purified autoinhibited BRAF:14-3-3 2 :MEK complexes. Our results show that fully processed, active-state KRAS alone can promote dimer-dependent BRAF activation. Moreover, we found that phosphatidylserine (PS)-containing liposomes synergized with KRAS to promote BRAF activation, achieving activity levels comparable to those observed with BRAF proteins that constitutively dimerize. In contrast, the SMP phosphatase complex had only a minimal effect on BRAF catalytic activity in this system but mediated the dephosphorylation of the negative regulatory pS365 14-3-3 binding site in a manner that was accelerated by the presence of KRAS alone or KRAS and 30% PS liposomes. Finally, we show that inhibitors blocking the BRAF RBD:KRAS interaction were able to suppress the in vitro activation of BRAF, underscoring the critical role of RAS binding in initiating the disassembly of the BRAF autoinhibited state. Thus, this assay provides valuable insights into the steps required for BRAF activation and can serve as an effective screening tool for identifying compounds that may inhibit this process and have therapeutic potential.

BRAF↗
DOE OSTI2022

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76–85% for guideline uterotrophic assays, and 3) 87–88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. Finally, as part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Preclinical tumor organoid models in personalized cancer therapy: Not everyone fits the mold

Highlights: • In personalized cancer medicine, each patient receives a specific treatment. • The tumor microenvironment and interpersonal differences can affect treatment. • Organoid culture systems fully recapitulate the tumor microenvironments. In contrast to conventional cancer treatment, in personalized cancer medicine each patient receives a specific treatment. The response to therapy, clinical outcomes, and tumor behavior such as metastases, tumor progression, carcinogenesis can be significantly affected by the heterogeneous tumor microenvironment (TME) and interpersonal differences. Therefore, using native tumor microenvironment mimicking models is necessary to improving personalized cancer therapy. Both in vitro 2D cell culture and in vivo animal models poorly recapitulate the heterogeneous tumor (immune) microenvironments of native tumors. The development of 3D culture models, native tumor microenvironment mimicking models, made it possible to evaluate the chemoresistance of tumor tissue and the functionality of drugs in the presence of cell-extracellular matrix and cell-cell interactions in a 3D construction. Various personalized tumor models have been designed to preserving the native tumor microenvironment, including patient-derived tumor xenografts and organoid culture strategies. In this review, we will discuss the patient-derived organoids as a native tumor microenvironment mimicking model in personalized cancer therapy. In addition, we will also review the potential and the limitations of organoid culture systems for predicting patient outcomes and preclinical drug screening. Finally, we will discuss immunotherapy drug screening in tumor organoids by using microfluidic technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Early Drug Discovery and Development of Novel Cancer Therapeutics Targeting DNA Polymerase Eta (POLH)

Polymerase eta (or Pol η or POLH) is a specialized DNA polymerase that is able to bypass certain blocking lesions, such as those generated by ultraviolet radiation (UVR) or cisplatin, and is deployed to replication foci for translesion synthesis as part of the DNA damage response (DDR). Inherited defects in the gene encoding POLH (a.k.a., XPV) are associated with the rare, sun-sensitive, cancer-prone disorder, xeroderma pigmentosum, owing to the enzyme’s ability to accurately bypass UVR-induced thymine dimers. In standard-of-care cancer therapies involving platinum-based clinical agents, e.g., cisplatin or oxaliplatin, POLH can bypass platinum-DNA adducts, negating benefits of the treatment and enabling drug resistance. POLH inhibition can sensitize cells to platinum-based chemotherapies, and the polymerase has also been implicated in resistance to nucleoside analogs, such as gemcitabine. POLH overexpression has been linked to the development of chemoresistance in several cancers, including lung, ovarian, and bladder. Co-inhibition of POLH and the ATR serine/threonine kinase, another DDR protein, causes synthetic lethality in a range of cancers, reinforcing that POLH is an emerging target for the development of novel oncology therapeutics. Using a fragment-based drug discovery approach in combination with an optimized crystallization screen, we have solved the first X-ray crystal structures of small novel drug-like compounds, i.e., fragments, bound to POLH, as starting points for the design of POLH inhibitors. The intrinsic molecular resolution afforded by the method can be quickly exploited in fragment growth and elaboration as well as analog scoping and scaffold hopping using medicinal and computational chemistry to advance hits to lead. An initial small round of medicinal chemistry has resulted in inhibitors with a range of functional activity in an in vitro biochemical assay, leading to the rapid identification of an inhibitor to advance to subsequent rounds of chemistry to generate a lead compound. Importantly, our chemical matter is different from the traditional nucleoside analog-based approaches for targeting DNA polymerases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Quantifying the Impact of Excluding the Submersion Exposure Route for Existing Superfund Radionuclide Screening Level Calculator Soil and Tap Water Models

The U.S. Environmental Protection Agency (EPA) provides initial data screening guidelines for radionuclide-contaminated Superfund sites using preliminary remediation goals (PRGs) and dose compliance concentrations (DCCs). PRGs and DCCs are target concentration values based on acceptable excess lifetime cancer risk and annual dose limits, respectively. They are calculated for various environmental media that may be encountered by residential and worker land uses. PRGs and DCCs typically consist of multiple exposure routes. One of these routes is submersion, which is exposure to a gaseous or particulate radionuclide that is suspended in air. Currently, submersion is only included in air calculations. This study focused on determining whether factoring submersion into total PRG/DCC calculations for soil and tap water created a significant difference in the target concentrations. New equations for individual submersion PRGs/DCCs for each land use of interest for soil and tap water were developed. A wind-driven particulate emission factor and Andelman’s constant were used to model the amount of soil and vapor in the air from soil and household use of tap water, respectively. The submersion PRG/DCC was then included in the total PRG/DCC for each radionuclide, followed by a percent difference comparison of the old and new totals to quantify the impact of the change. For total soil PRGs/DCCs, with and without submersion, the difference was less than 1 percent; however, many of the tap water radionuclides analyzed – including multiple radon and polonium isotopes – showed as high as a 200 percent difference.This technical memorandum (TM) presents recommendations for updates to current EPA guidelines for initial data screens of radionuclide contaminated tap water.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Identification of a Covalent Molecular Inhibitor of Anti-apoptotic BFL-1 by Disulfide Tethering

The BCL-2 family is composed of anti- and pro-apoptotic members that respectively protect or disrupt mitochondrial integrity. Anti-apoptotic overexpression can promote oncogenesis by trapping the BCL-2 homology 3 (BH3) “killer domains” of pro-apoptotic proteins in a surface groove, blocking apoptosis. Groove inhibitors, such as the relatively large BCL-2 drug venetoclax (868 Da), have emerged as cancer therapies. BFL-1 remains an undrugged oncogenic protein and can cause venetoclax resistance. Having identified a unique C55 residue in the BFL-1 groove, we performed a disulfide tethering screen to determine if C55 reactivity could enable smaller molecules to block BFL-1's BH3-binding functionality. We found that a disulfide-bearing N-acetyltryptophan analog (304 Da adduct) effectively targeted BFL-1 C55 and reversed BFL-1-mediated suppression of mitochondrial apoptosis. Structural analyses implicated the conserved leucine-binding pocket of BFL-1 as the interaction site, resulting in conformational remodeling. Thus, therapeutic targeting of BFL-1 may be achievable through the design of small, cysteine-reactive drugs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Massively parallel, computationally guided design of a proenzyme

Proteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally guided method to design inactive proenzymes or zymogens, which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these proenzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically relevant protein carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80 to 98% and are partially to fully reactivatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner. Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to redesign any chosen enzyme to be similarly stimulus responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for proenzyme design. For a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of the most effectively designed variants shows that they are inhibited by ∼80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro- and catalytic domains based on the design models increases the degree of inhibition to 98% but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing proenzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the prodomain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of proproteins with precise spatial regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Small-molecule allosteric inhibitors of GPX4

Here, encouraged by the dependence of drug-resistant, metastatic cancers on GPX4, we examined biophysical mechanisms of GPX4 inhibition, which revealed an unexpected allosteric site. We found that this site was involved in native regeneration of GPX4 under low glutathione conditions. Covalent binding of inhibitors to this allosteric site caused a conformational change, inhibition of activity, and subsequent cellular GPX4 protein degradation. To verify this site in an unbiased manner, we screened a library of compounds and identified and validated that an additional compound can covalently bind in this allosteric site, inhibiting and degrading GPX4. We determined co-crystal structures of six different inhibitors bound in this site. We have thus identified an allosteric mechanism for small molecules targeting aggressive cancers dependent on GPX4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Discovery of an autoinhibited conformation in mesotrypsin reveals a strategy for selective serine protease inhibition

Selective inhibition of the more than 100 S1 family serine proteases is a long-standing challenge due to their active site similarity. Mesotrypsin, implicated in cancer progression, exemplifies these difficulties; no current inhibitors achieve selectivity over other human trypsins. We found an unexpected autoinhibited conformation of mesotrypsin via x-ray crystallography, revealing a cryptic pocket adjacent to the active site. Using high-throughput virtual screening targeting this cryptic pocket, we identified a conformationally selective small-molecule inhibitor that stabilizes the inactive state of mesotrypsin. This inhibitor demonstrates selectivity for mesotrypsin over other trypsins. Our findings challenge the accepted view of digestive trypsins as constitutively active enzymes lacking potential for allosteric regulation. Furthermore, analyses of other structures suggest that dynamic sampling of closed states with analogous allosteric cryptic pockets appears widespread among S1 serine proteases. These observations point to a potentially generalizable strategy to achieve selective inhibition, offering broad implications for drug development targeting serine proteases in cancer and other diseases.

Coban, Matt↗
DOE OSTI2021

Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Identifying genomic alterations of cancer proteins has guided the development of targeted therapies, but proteomic analyses are required to validate and reveal new treatment opportunities. Herein, we develop a new algorithm, OPPTI, to discover overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data of 1,071 cases. OPPTI outperforms existing methods by leveraging multiple co-expressed markers to identify targets overexpressed in a subset of tumors. OPPTI-identified overexpression of ERBB2 and EGFR proteins correlates with genomic amplifications, while CDK4/6, PDK1, and MET protein overexpression frequently occur without corresponding DNA- and RNA-level alterations. Analyzing CRISPR screen data, we confirm expression-driven dependencies of multiple currently-druggable and new target kinases whose expressions are validated by immunochemistry. Identified kinases are further associated with up-regulated phosphorylation levels of corresponding signaling pathways. Collectively, our results reveal protein-level aberrations—sometimes not observed by genomics—represent cancer vulnerabilities that may be targeted in precision oncology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Structural basis for substrate recognition and chemical inhibition of oncogenic MAGE ubiquitin ligases

Testis-restricted melanoma antigen (MAGE) proteins are frequently hijacked in cancer and play a critical role in tumorigenesis. MAGEs assemble with E3 ubiquitin ligases and function as substrate adaptors that direct the ubiquitination of novel targets, including key tumor suppressors. However, how MAGEs recognize their targets is unknown and has impeded the development of MAGE-directed therapeutics. Here, we report the structural basis for substrate recognition by MAGE ubiquitin ligases. Biochemical analysis of the degron motif recognized by MAGE-A11 and the crystal structure of MAGE-A11 bound to the PCF11 substrate uncovered a conserved substrate binding cleft (SBC) in MAGEs. Mutation of the SBC disrupted substrate recognition by MAGEs and blocked MAGE-A11 oncogenic activity. A chemical screen for inhibitors of MAGE-A11:substrate interaction identified 4-Aminoquinolines as potent inhibitors of MAGE-A11 that show selective cytotoxicity. These findings provide important insights into the large family of MAGE ubiquitin ligases and identify approaches for developing cancer-specific therapeutics.

60 APPLIED LIFE SCIENCES↗