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At least 847 records · Page 47

Selective Lanthanide Sensing with Gold Nanoparticles and Hydroxypyridinone Chelators

The octadentate hydroxypyridinone chelator 3,4,3-LI(1,2-HOPO) is a promising therapeutic agent because of its high affinity for f-block elements and noncytotoxicity at medical dosages. The interaction between 3,4,3-LI(1,2-HOPO) and other biomedically relevant metals such as gold, however, has not been explored. Gold nanoparticles functionalized with chelators have demonstrated great potential in theranostics, yet thus far, no protocol that combines 3,4,3-LI(1,2-HOPO) and colloidal gold has been developed. Here, we characterize the solution thermodynamic properties of the complexes formed between 3,4,3-LI(1,2-HOPO) and Au 3+ ions and demonstrate how under specific pH conditions the chelator promotes the growth of gold nanoparticles, acting as both reducing and stabilizing agent. 3,4,3-LI(1,2-HOPO) ligands on the nanoparticle surface remain active and selective toward f-block elements, as evidenced by gold nanoparticle selective aggregation. Finally, a new colorimetric assay capable of reaching the detection levels necessary for the quantification of lanthanides in waste from industrial processes is developed based on the inhibition of particle growth by lanthanides.

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Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

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Identification of Small-Molecule Inhibitors of Fibroblast Growth Factor 23 Signaling via In Silico Hot Spot Prediction and Molecular Docking to α-Klotho

Fibroblast growth factor 23 (FGF23) is a therapeutic target for treating hereditary and acquired hypophosphatemic disorders, such as X-linked hypophosphatemic (XLH) rickets and tumor-induced osteomalacia (TIO), respectively. FGF23-induced hypophosphatemia is mediated by signaling through a ternary complex formed by FGF23, the FGF receptor (FGFR), and α-Klotho. Currently, disorders of excess FGF23 are treated with an FGF23-blocking antibody, burosumab. Small-molecule drugs that disrupt protein/protein interactions necessary for the ternary complex formation offer an alternative to disrupting FGF23 signaling. In this study, the FGF23:α-Klotho interface was targeted to identify small-molecule protein/protein interaction inhibitors since it was computationally predicted to have a large fraction of hot spots and two druggable residues on α-Klotho. We further identified Tyr433 on the KL1 domain of α-Klotho as a promising hot spot and α-Klotho as an appropriate drug-binding target at this interface. Subsequently, we performed in silico docking of ~5.5 million compounds from the ZINC database to the interface region of α-Klotho from the ternary crystal structure. Following docking, 24 and 20 compounds were in the final list based on the lowest binding free energies to α-Klotho and the largest number of contacts with Tyr433, respectively. Herein, five compounds were assessed experimentally by their FGF23-mediated extracellular signal-regulated kinase (ERK) activities in vitro, and two of these reduced activities significantly. Both these compounds were predicted to have favorable binding affinities to α-Klotho but not have a large number of contacts with the hot spot Tyr433. ZINC12409120 was found experimentally to disrupt FGF23:α-Klotho interaction to reduce FGF23-mediated ERK activities by 70% and have a half maximal inhibitory concentration (IC50) of 5.0 ± 0.23 μM. Molecular dynamics (MD) simulations of the ZINC12409120:α-Klotho complex starting from in silico docking poses reveal that the ligand exhibits contacts with residues on the KL1 domain, the KL1–KL2 linker, and the KL2 domain of α-Klotho simultaneously, thereby possibly disrupting the regular function of α-Klotho and impeding FGF23:α-Klotho interaction. ZINC12409120 is a candidate for lead optimization.

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AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2

Direct-acting antivirals for the treatment of the COVID-19 pandemic caused by the SARS-CoV-2 virus are needed to complement vaccination efforts. Given the ongoing emergence of new variants, automated experimentation, and active learning based fast workflows for antiviral lead discovery remain critical to our ability to address the pandemic’s evolution in a timely manner. While several such pipelines have been introduced to discover candidates with noncovalent interactions with the main protease (M pro ), here we developed a closed-loop artificial intelligence pipeline to design electrophilic warhead-based covalent candidates. Here, this work introduces a deep learning-assisted automated computational workflow to introduce linkers and an electrophilic “warhead” to design covalent candidates and incorporates cutting-edge experimental techniques for validation. Using this process, promising candidates in the library were screened, and several potential hits were identified and tested experimentally using native mass spectrometry and fluorescence resonance energy transfer (FRET)-based screening assays. We identified four chloroacetamide-based covalent inhibitors of M pro with micromolar affinities (K I of 5.27 μM) using our pipeline. Experimentally resolved binding modes for each compound were determined using room-temperature X-ray crystallography, which is consistent with the predicted poses. The induced conformational changes based on molecular dynamics simulations further suggest that the dynamics may be an important factor to further improve selectivity, thereby effectively lowering KI and reducing toxicity. These results demonstrate the utility of our modular and data-driven approach for potent and selective covalent inhibitor discovery and provide a platform to apply it to other emerging targets.

60 APPLIED LIFE SCIENCES↗

Ligand-Based Compound Activity Prediction via Few-Shot Learning

Predicting the activities of new compounds against biophysical or phenotypic assays based on the known activities of one or a few existing compounds is a common goal in early stage drug discovery. This problem can be cast as a “few-shot learning” challenge, and prior studies have developed few-shot learning methods to classify compounds as active versus inactive. However, the ability to go beyond classification and rank compounds by expected affinity is more valuable. We describe Few-Shot Compound Activity Prediction (FS-CAP), a novel neural architecture trained on a large bioactivity data set to predict compound activities against an assay outside the training set, based on only the activities of a few known compounds against the same assay. Our model aggregates encodings generated from the known compounds and their activities to capture assay information and uses a separate encoder for the new compound whose activity is to be predicted. The new method provides encouraging results relative to traditional chemical-similarity-based techniques as well as other state-of-the-art few-shot learning methods in tests on a variety of ligand-based drug discovery settings and data sets.

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CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. Here, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A 2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ~1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

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Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

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Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions

Alchemical relative binding free energy calculations have recently found important applications in drug optimization. A series of congeneric compounds are generated from a preidentified lead compound, and their relative binding affinities to a protein are assessed in order to optimize candidate drugs. While methods based on equilibrium thermodynamics have been extensively studied, an approach based on nonequilibrium methods has recently been reported together with claims of its superiority. However, these claims pay insufficient attention to the basis and reliability of both methods. Here we report a comparative study of the two approaches across a large data set, comprising more than 500 ligand transformations spanning in excess of 300 ligands binding to a set of 14 diverse protein targets. Ensemble methods are essential to quantify the uncertainty in these calculations, not only for the reasons already established in the equilibrium approach but also to ensure that the nonequilibrium calculations reside within their domain of validity. If and only if ensemble methods are applied, we find that the nonequilibrium method can achieve accuracy and precision comparable to those of the equilibrium approach. Compared to the equilibrium method, the nonequilibrium approach can reduce computational costs but introduces higher computational complexity and longer wall clock times. There are, however, cases where the standard length of a nonequilibrium transition is not sufficient, necessitating a complete rerun of the entire set of transitions. This significantly increases the computational cost and proves to be highly inconvenient during large-scale applications. Our findings provide a key set of recommendations that should be adopted for the reliable implementation of nonequilibrium approaches to relative binding free energy calculations in ligand-protein systems.

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Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

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Garcinoic Acid Is a Natural and Selective Agonist of Pregnane X Receptor

Pregnane X receptor (PXR) is a master xenobiotic-sensing transcription factor and a validated target for immune and inflammatory diseases. The identification of chemical probes to investigate the therapeutic relevance of the receptor is still highly desired. In fact, currently available PXR ligands are not highly selective and can exhibit toxicity and/or potential off-target effects. In this study, we have identified garcinoic acid as a selective and efficient PXR agonist. The properties of this natural molecule as a specific PXR agonist were demonstrated by the screening on a panel of nuclear receptors, the assessment of the physical and thermodynamic binding affinity, and the determination of the PXR-garcinoic acid complex crystal structure. Cytotoxicity, transcriptional, and functional properties were investigated in human liver cells, and compound activity and target engagement were confirmed in vivo in mouse liver and gut tissue. In conclusion, garcinoic acid is a selective natural agonist of PXR and a promising lead compound toward the development of new PXR-regulating modulators.

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Rationally Designed, Short-Acting RPE65 Inhibitors for Visual Cycle-Associated Retinopathies

Abstract The visual cycle is a metabolic pathway essential for visual function. The bisretinoid byproducts of this pathway can induce retinal toxicity, as occurs in Stargardt disease type 1 (STGD1). Emixustat, which inhibits bisretinoid production, is a visual cycle modulator (VCM) that targets RPE65. However, it causes visual impairment due to its unfavorable duration of action. Here, we report ester-containing analogs of emixustat that are susceptible to hydrolytic clearance and function as short-acting VCMs. We show that the esterase-mediated metabolism of these compounds can be tuned while maintaining high-affinity RPE65 targeting. Compounds 6 (EYE-002) and 7 (EYE-003) containing diethyl acetate and valproate esters, respectively, allowed faster recovery of visual cycle function compared to emixustat. These molecules protected against retinal degeneration in mouse models of photic retinopathy and STGD1. These data demonstrate that shorter attenuation of the visual cycle can therapeutically intervene in retinal diseases with fewer visual side effects compared to emixustat.

Pharmacology & Pharmacy↗

Discovery of Macrocyclic Myeloid Cell Leukemia 1 (Mcl-1)Inhibitors that Demonstrate Potent Cellular Efficacy and In Vivo Activity in a Mouse Solid Tumor Xenograft Model

Abstract The B cell lymphoma 2 (Bcl-2) family of proteins are key regulators of intrinsic apoptosis. The antiapoptotic protein myeloid cell leukemia 1 (Mcl-1), which is associated with high tumor grade, poor survival, and resistance to treatment, has emerged as a promising candidate for treating hematological and solid cancers. Herein, we report the structure-guided design of small molecule macrocyclic Mcl-1 inhibitors based on the (R)-methyl-dihydropyrazinoindolone scaffold our group has previously disclosed. The macrocyclic inhibitors bind Mcl-1 with subnanomolar affinity and offer improved potency in cell culture growth inhibition assays. Inhibitor 13 achieved tumor regression in a lung cancer-derived tumor xenograft model in mice as a monotherapy. The improved potency of the macrocyclic series allowed replacement of heretofore conserved indole carboxylic acid moiety, resulting in neutral inhibitors. Amide inhibitor 25 displayed a >10-fold increase in oral bioavailability as compared to acid-containing macrocyclic or acyclic inhibitors.

Pharmacology & Pharmacy↗

Identification of KLHL12 Ligands Using Fragment-Based Methods

Targeted protein degradation can be induced by recruiting a protein of interest to an E3 ligase, resulting in its ubiquitination and subsequent proteasome-mediated degradation. However, only a small number of E3 ligases have been utilized for degradation. Expansion of the repertoire of useful E3 ligases via the identification of ligands to those ligases could broaden the scope and applicability of the degradation paradigm. We have identified KLHL12 as an E3 ligase with higher expression in cancer over normal tissues. We report here the use of NMR-based screening to identify fragments that bind to KLHL12, and X-ray structures of a fragment hit bound to KLHL12. Using this structural information, we optimized the hits, leading to the first reported small molecules that bind to KLHL12 with submicromolar affinity. Derivatives of these compounds may be useful for the construction of PROTACs to selectively degrade protein targets in tumors while sparing normal cells.

Amines↗

Discovery and Structure-Based Optimization of Potent and Selective WD Repeat Domain 5 (WDR5) Inhibitors Containing a Dihydroisoquinolinone Bicyclic Core

WD repeat domain 5 (WDR5) is a member of the WD40-repeat protein family that plays a critical role in multiple chromatin-centric processes. Overexpression of WDR5 correlates with a poor clinical outcome in many human cancers, and WDR5 itself has emerged as an attractive target for therapy. Most drug-discovery efforts center on the WIN site of WDR5 that is responsible for the recruitment of WDR5 to chromatin. In this paper, we describe discovery of a novel WDR5 WIN site antagonists containing a dihydroisoquinolinone bicyclic core using a structure-based design. These compounds exhibit picomolar binding affinity and selective concentration-dependent antiproliferative activities in sensitive MLL-fusion cell lines. Furthermore, these WDR5 WIN site binders inhibit proliferation in MYC-driven cancer cells and reduce MYC recruitment to chromatin at MYC/WDR5 co-bound genes. Thus, these molecules are useful probes to study the implication of WDR5 inhibition in cancers and serve as a potential starting point toward the discovery of anti-WDR5 therapeutics.

60 APPLIED LIFE SCIENCES↗

Multi-Ion Complexes and Competition from Bulky BArF – Anions for Chloride Binding in Ion Pairing Conditions

Cationic charges have long been used to enhance anion binding. Embedding charge introduces strong ion pairing for target anions but also for off-target ions, ultimately generating a mixture of multi-ion species that are hard to identify and quantify. While many sidestep this problem using polar solvents and weakly coordinating ions, these approaches exclude a substantial cross-section of conditions found in applications spanning recognition, assembly, separations, templation, and catalysis. To confront this complexity, we study the binding of an anion to a cationic receptor featuring low shape complementarity in a low-polarity solvent to maximize ionic interactions. We prepared the receptor as a salt of the weakly coordinating tetrakis­[3,5-bis­(trifluoromethyl)­phenyl]­borate (BArF – ) anion and studied the binding of small chloride (Cl – ) and medium-sized iodide (I – ) anions. Surprisingly, the use of the bulky BArF – anion does not suppress ion pairing interactions, with 65% of the receptor being paired at 0.5 mM in dichloromethane. We observe multi-ion receptor-Cl – complexes (2:1, 1:1, 1:2), reinforcing the complexity that emerges when working in low-polarity media. Here, we reveal the dependence of affinity on anion charge density and size and that bulky BArF – counteranions compete for chloride binding. These studies reveal the noninnocence of BArF – anions and strategies to quantify multi-ion species.

Ion pairing↗

Gas-Phase Complexes of Americium and Lanthanides with a Bis-triazinyl Pyridine: Reactivity and Bonding of Archetypes for F-Element Separations

Bis-triazinyl pyridines (BTPs) exhibit solution selectivity for trivalent americium over lanthanides (Ln), the origins of which remain uncertain. Here in this paper, electrospray ionization was used to generate gas-phase complexes [ML 3 ] 3+ , where M = La, Lu, or Am and L is EtBTP 2,6-bis(5,6-diethyl-1,2,4-triazin-3-yl)-pyridine. Collision-induced dissociation (CID) of [ML 3 ] 3+ in the presence of H 2 O yielded a protonated ligand [L(H)] + and hydroxide [ML 2 (OH)] 2+ or hydrate [ML(L–H)(H 2 O)] 2+ , where (L–H) - is a deprotonated ligand. Although solution affinities indicate stronger binding of BTPs toward Am 3+ versus Ln 3+ , the observed CID process is contrastingly more facile for M = Am versus Ln. To understand the disparity, density functional theory was employed to compute potential energy surfaces for two possible CID processes, for M = La and Am. In accordance with the CID results, both the rate determining transition state barrier and the net energy are lower for [AmL 3 ] 3+ versus [LaL 3 ] 3+ and for both product isomers, [ML 2 (OH)] 2+ and [ML(L–H)(H 2 O)] 2+ . More facile removal of a ligand from [AmL 3 ] 3+ by CID does not necessarily contradict stronger Am 3+ –L binding, as inferred from solution behavior. In particular, the formation of new bonds in the products can distort kinetics and thermodynamics expected for simple bond cleavage reactions. In addition to correctly predicting the seemingly anomalous CID behavior, the computational results indicate greater participation of Am 5f versus La 4f orbitals in metal–ligand bonding.

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Velocity-Map Imaging and Magnetic-Bottle Photoelectron Spectroscopy of [SeCCH] – : Electronic Properties and Spin–Orbit Splitting

In this work, the recently synthesized acetylide compound KSeCCH containing the main group element selenium within the novel and in crystalline form unprecedented [SeCCH] – anion was successfully investigated in the gas phase by high-resolution velocity-map imaging (VMI) and magnetic-bottle (MB) photoelectron spectroscopy coupled with an electrospray ionization source. Both VMI and MB spectra exhibited identical electron affinities (EA, 2.517 ± 0.002 eV), spin–orbit coupling (SOC) splittings (1492 ± 20 cm –1 ), and Se–C stretching frequencies (573 ± 20 cm –1 ) of the corresponding neutral tetra-atomic radical [SeCCH] • with the VMI spectrum possessing six times higher spectral resolution compared with the MB spectrum. These experimental values were well reproduced by calculations at the CCSD(T) level, in which both the isolated [SeCCH] – anion and the [SeCCH] • radical adopted linear geometries. The simulated spectra based on the calculated Franck–Condon factors, the SOC splitting, and the experimental line width matched well with the measured spectra. Furthermore, comparisons of the EA and SOC splitting values with the previously reported isolobal species [SeCN] • are also made and discussed. The decrease in the EA and SOC splitting of [SeCCH] • is ascribed to the differences in the electronegativities between C and N atoms as well as the electron density on the Se atom in its singly occupied molecular orbital (SOMO).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping the Electronic Structure of the Uranium(VI) Dinitride Molecule, UN 2

A combined anion photoelectron spectroscopic and relativistic electronic-structure computational study of the electronic structure of the UN 2 molecule is reported. Since the photoelectron spectrum of uranium dinitride’s negative ion, UN 2 - , (UN 2 plus an additional electron) directly reflects the electronic structure of neutral UN 2 , we have measured and relied upon the photoelectron spectrum of the UN 2 – anion as a means of mapping the electronic structure of neutral UN 2 . In addition to the electron affinity of the UN 2 ground state (the energy released when attaching an electron to UN 2 molecule), energy levels of the UN 2 excited states (electronic states with higher energies than the ground state) were well characterized by the close interplay between experiment and high-level theory. We found that both electron attachment and electronic excitation significantly bend the UN 2 molecule and elongate its U≡N bond. Implications for the activation of UN 2 are discussed.

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