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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Strategies and Software for Machine Learning Accelerated Discovery in Transition Metal Chemistry

Machine learning the electronic structure of open shell transition metal complexes presents unique challenges, including robust and automated data set generation. In this report we introduce tools that simplify data acquisition from density functional theory (DFT) and validation of trained machine learning models using the molSimplify automatic design (mAD) workflow. We demonstrate this workflow by training and comparing the performance of LASSO, kernel ridge regression (KRR), and artificial neural network (ANN) models using heuristic, topological revised autocorrelation (RAC) descriptors we have recently introduced for machine learning inorganic chemistry. On a series of open shell transition metal complexes, we evaluate set aside test errors of these models for predicting the HOMO level and HOMO–LUMO gap. The best performing models are ANNs, which show 0.15 and 0.25 eV test set mean absolute errors on the HOMO level and HOMO–LUMO gap, respectively. Poor performing KRR models using the full 153-feature RAC set are improved to nearly the same performance as the ANNs when trained on down-selected subsets of 20–30 features. Analysis of the essential descriptors for HOMO level and HOMO–LUMO gap prediction as well as comparison to subsets previously obtained for other properties reveal the paramount importance of nonlocal, steric properties in determining frontier molecular orbital energetics. We demonstrate our model performance on diverse complexes and in the discovery of molecules with target HOMO–LUMO gaps from a large 15,000 molecule design space in minutes rather than days that full DFT evaluation would require.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine Learning-Guided Discovery of Ternary Compounds Containing La, P, and Group 14 Elements

In this work, we integrate a deep machine learning (ML) method with first-principles calculations to efficiently search for the energetically favorable ternary compounds. Using La–Si–P as a prototype system, we demonstrate that ML-guided first-principles calculations can efficiently explore crystal structures and their relative energetic stabilities, thus greatly accelerate the pace of material discovery. A number of new La–Si–P ternary compounds with formation energies less than 30 meV/atom above the known ternary convex hull are discovered. Among them, the formation energies of La 5 SiP 3 and La 2 SiP phases are only 2 and 10 meV/atom, respectively, above the convex hull. These two compounds are dynamically stable with no imaginary phonon modes. Moreover, by replacing Si with heavier-group 14 elements in the eight lowest-energy La–Si–P structures from our ML-guided predictions, a number of low-energy La–X–P phases (X = Ge, Sn, Pb) are predicted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Phase Discovery and Selected Synthesis of Subvalent Niobium Tellurides Using a Polytelluride Flux Strategy

Transition metal subchalcogenides involve electron-rich metals and can facilitate an in-depth understanding of the relationships among quantum properties such as superconductivity, charge density wave, and topological band structures. However, effective experimental routes toward synthesizing transition metal subchalcogenides are still lacking, hindering the development of new quantum materials. Herein, we propose a eutectic polytelluride flux strategy as an excellent solution to address phase discovery and crystal growth in transition metal subtelluride systems. We report new phases easily and selectively synthesized using a eutectic “K 3 Te 4 ” polytelluride flux upon adjusting the ratio of Nb metal to flux in the starting materials (K/Nb/Te = 3:x:4). Using a high Nb content in the solvent (x = 2 and 1), crystals of KNb 3 Te 3 O 0.38 and K 0.9 Nb 3 Te 4 are obtained. Both subtellurides exhibit diverse Nb clusters, including face-sharing and edge-sharing Nb 6 octahedral columns and zig-zag Nb chains. Reducing the Nb content to x = 0.33 leads to the formation of a layered compound, K 1.06 NbTe 2 . This compound comprises a NbTe 6 trigonal prism with K intercalated between the layers. Single crystals of known binary Nb tellurides can also be grown using another eutectic flux “KTe 3 . 2 ”, and the obtained NbTe 2 exhibits a new polymorphism with extra trimerization along the b-axis in the Nb–Nb bonded double zig-zag cluster. Finally, precise control over the structural dimensionality and oxidation state, combined with the facile crystal growth process, makes our synthetic strategy an efficient route to explore quantum materials in transition metal subchalcogenides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Discovery-Synthesis, Design, and Prediction of Chalcogenide Phases

The discovery of new materials and their efficient syntheses is a fundamental goal of chemistry. A related objective is to identify foundational and rational approaches to enhance the art of synthesis by combining the exquisite predictability of organic synthesis with the high yields of solid-state chemistry. In contrast to so-called solid-state methods, inorganic syntheses in liquid fluxes permit bond formation, framework assembly, and crystallization at lower temperatures because of facile diffusion and chemical reactions with and within the flux itself. The fluxes are bona fide solvents similar to conventional organic or aqueous solvents. Such reactions can produce a wide range of materials, often metastable, from oxides to intermetallics, but typically the formation mechanisms are poorly understood. This article discusses how one can design, perform, observe, understand, and engineer the formation of compounds from inorganic melts. The focus is also design concepts such as "dimensional reduction", "phase homologies", and "panoramic synthesis", and their broad applicability. When well-defined building blocks are present and stable in the reaction, prospects for increased structural diversity and product control increase substantially. Common structural motifs within these materials systems may be related to structural precursors in the melt that may be controlled by tuning reaction conditions and composition. Stabilization of a particular building block is often accomplished with tuning of the flux composition, which controls the Lewis basicity and redox potential. In such tunable and dynamic fluxes, the synthesis can be directed toward new materials. Using complementary techniques of in situ X-ray diffraction, we can create time-dependent maps of reaction space and probe the mobile species present in melts. Lastly, certain thoughts toward the ultimate goal of targeted materials synthesis by controlling inorganic melt chemistry are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery

Methods that accelerate the evaluation of molecular properties are essential for chemical discovery. While some degree of ligand additivity has been established for transition metal complexes, it is underutilized in asymmetric complexes, such as the square pyramidal coordination geometries highly relevant to catalysis. To develop predictive methods beyond simple additivity, we apply a many-body expansion to octahedral and square pyramidal complexes and introduce a correction based on adjacent ligands (i.e., the cis interaction model). We first test the cis interaction model on adiabatic spin-splitting energies of octahedral Fe(II) complexes, predicting DFT-calculated values of unseen binary complexes to within an average of 1.4 kcal/mol. Uncertainty analysis reveals the optimal basis, comprising the homoleptic and mer symmetric complexes. We next show that the cis model (i.e., the cis interaction model solved for the optimal basis) infers both DFT- and CCSD(T)-calculated model catalytic reaction energies to within 1 kcal/mol on average. The cis model predicts low-symmetry complexes with reaction energies outside the range of binary complex reaction energies. We observe that trans interactions are unnecessary for most monodentate systems but can be important for some combinations of ligands, such as complexes containing a mixture of bidentate and monodentate ligands. Lastly, we demonstrate that the cis model may be combined with Δ-learning to predict CCSD(T) reaction energies from exhaustively calculated DFT reaction energies and the same fraction of CCSD(T) reaction energies needed for the cis model, achieving around 30% of the error from using the CCSD(T) reaction energies in the cis model alone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Dynamic Workflows for Routine Materials Discovery in Surface Science

The rising application of informatics and data science tools for studying inorganic crystals and small molecules has revolutionized approaches to materials discovery and driven the development of accurate machine learning structure/property relationships. In this paper, we discuss how informatics tools can accelerate research, and we present various combinations of workflows, databases, and surrogate models in the literature. This paradigm has been slower to infiltrate the catalysis community due to larger configuration spaces, difficulty in describing necessary calculations, and thermodynamic/kinetic quantities that require many interdependent calculations. We present our own informatics tool that uses dynamic dependency graphs to share, organize, and schedule calculations to enable new, flexible research workflows in surface science. This approach is illustrated for the large-scale screening of intermetallic surfaces for electrochemical catalyst activity. Similar approaches will be important to bring the benefits of informatics and data science to surface science research. Lastly, we provide our perspective on when to use these tools and considerations when creating them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Generating Protein Structures for Pathway Discovery Using Deep Learning

Resolving the intricate details of biological phenomena at the molecular level is fundamentally limited by both length- and time scales that can be probed experimentally. Molecular dynamics (MD) simulations at various scales are powerful tools frequently employed to offer valuable biological insights beyond experimental resolution. However, while it is relatively simple to observe long-lived, stable configurations of, for example, proteins, at the required spatial resolution, simulating the more interesting rare transitions between such states often takes orders of magnitude longer than what is feasible even on the largest supercomputers available today. One common aspect of this challenge is pathway discovery, where the start and end states of a scientific phenomenon are known or can be approximated, but the mechanistic details in between are unknown. Here, we propose a representation-learning-based solution that uses interpolation and extrapolation in an abstract representation space to synthesize potential transition states, which are automatically validated using MD simulations. The new simulations of the synthesized transition states are subsequently incorporated into the representation learning, leading to an iterative framework for targeted path sampling. Our approach is demonstrated by recovering the transition of a RAS-RAF protein domain (CRD) from membrane-free to interacting with the membrane using coarse-grain MD simulations.

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 OSTI2015

Fragment-based discovery of a small molecule inhibitor of Bruton’s Tyrosine Kinase

The discovery and optimization of a series of 4-aminocinnoline-3-carboxamide inhibitors of Bruton’s tyrosine kinase are reported. A fragment-based screening approach incorporating X-ray co-crystallography was used to identify a cinnoline fragment and characterize its binding mode in the ATP binding site of Btk. Optimization of the fragment hit resulted in the identification of a lead compound which reduced paw swelling in a dose- and exposure-dependent fashion in a rat model of collagen-induced arthritis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Discovery and Characterization of 2-Acylaminoimidazole Microsomal Prostaglandin E Synthase-1 Inhibitors

As part of a program aimed at the discovery of antinociceptive therapy for inflammatory conditions, a screening hit was found to inhibit microsomal prostaglandin E synthase-1 (mPGES-1) with an IC 50 of 17.4 μM. Structural information was used to improve enzyme potency by over 1000-fold. Addition of an appropriate substituent alleviated time-dependent cytochrome P450 3A4 (CYP3A4) inhibition. Further structure–activity relationship (SAR) studies led to 8, which had desirable potency (IC 50 = 12 nM in an ex vivo human whole blood (HWB) assay) and absorption, distribution, metabolism, and excretion (ADME) properties. Here, studies on the formulation of 8 identified 8·H 3 PO 4 as suitable for clinical development. Omission of a lipophilic portion of the compound led to 26, a readily orally bioavailable inhibitor with potency in HWB comparable to celecoxib. Furthermore, 26 was selective for mPGES-1 inhibition versus other mechanisms in the prostanoid pathway. These factors led to the selection of 26 as a second clinical candidate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Discovery of 2-Indole-acylsulfonamide Myeloid Cell Leukemia 1 (Mcl-1) Inhibitors Using Fragment-Based Methods

Myeloid cell leukemia-1 (Mcl-1) is a member of the Bcl-2 family of proteins responsible for the regulation of programmed cell death. Amplification of Mcl-1 is a common genetic aberration in human cancer whose overexpression contributes to the evasion of apoptosis and is one of the major resistance mechanisms for many chemotherapies. Mcl-1 mediates its effects primarily through interactions with pro-apoptotic BH3 containing proteins that achieve high affinity for the target by utilizing four hydrophobic pockets in its binding groove. Here we describe the discovery of Mcl-1 inhibitors using fragment-based methods and structure-based design. These novel inhibitors exhibit low nanomolar binding affinities to Mcl-1 and >500-fold selectivity over Bcl-xL. Additionally, X-ray structures of lead Mcl-1 inhibitors when complexed to Mcl-1 provided detailed information on how these small-molecules bind to the target and were used extensively to guide compound optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Toward the Validation of Maternal Embryonic Leucine Zipper Kinase: Discovery, Optimization of Highly Potent and Selective Inhibitors, and Preliminary Biology Insight

MELK kinase has been implicated in playing an important role in tumorigenesis. Our previous studies suggested that MELK is involved in the regulation of cell cycle and its genetic depletion leads to growth inhibition in a subset of high MELK-expressing basal-like breast cancer cell lines. Herein we describe the discovery and optimization of novel MELK inhibitors 8a and 8b that recapitulate the cellular effects observed by short hairpin ribonucleic acid (shRNA)-mediated MELK knockdown in cellular models. We also discovered a novel fluorine-induced hydrophobic collapse that locked the ligand in its bioactive conformation and led to a 20-fold gain in potency. Here, these novel pharmacological inhibitors achieved high exposure in vivo and were well tolerated, which may allow further in vivo evaluation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Discovery of the 3-Imino-1,2,4-thiadiazinane 1,1-Dioxide Derivative Verubecestat (MK-8931)–A β-Site Amyloid Precursor Protein Cleaving Enzyme 1 Inhibitor for the Treatment of Alzheimer’s Disease

Verubecestat 3 (MK-8931), a diaryl amide-substituted 3-imino-1,2,4-thiadiazinane 1,1-dioxide derivative, is a high-affinity β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitor currently undergoing Phase 3 clinical evaluation for the treatment of mild to moderate and prodromal Alzheimer’s disease. Although not selective over the closely related aspartyl protease BACE2, verubecestat has high selectivity for BACE1 over other key aspartyl proteases, notably cathepsin D, and profoundly lowers CSF and brain Aβ levels in rats and nonhuman primates and CSF Aβ levels in humans. In this annotation, we describe the discovery of 3, including design, validation, and selected SAR around the novel iminothiadiazinane dioxide core as well as aspects of its preclinical and Phase 1 clinical characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Discovery of ( S )-1-(1-(4-Chloro-3-fluorophenyl)-2-hydroxyethyl)-4-(2-((1-methyl-1 H -pyrazol-5-yl)amino)pyrimidin-4-yl)pyridin-2(1 H )-one (GDC-0994), an Extracellular Signal-Regulated Kinase 1/2 (ERK1/2) Inhibitor in Early Clinical Development

The extracellular signal-regulated kinases ERK1/2 represent an essential node within the RAS/RAF/MEK/ERK signaling cascade that is commonly activated by oncogenic mutations in BRAF or RAS or by upstream oncogenic signaling. While targeting upstream nodes with RAF and MEK inhibitors has proven effective clinically, resistance frequently develops through reactivation of the pathway. Simultaneous targeting of multiple nodes in the pathway, such as MEK and ERK, offers the prospect of enhanced efficacy as well as reduced potential for acquired resistance. Here, described herein is the discovery and characterization of GDC-0994 (22), an orally bioavailable small molecule inhibitor selective for ERK kinase activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Discovery of 3-(3-(4-(1-Aminocyclobutyl)phenyl)-5-phenyl-3 H -imidazo[4,5- b ]pyridin-2-yl)pyridin-2-amine (ARQ 092): An Orally Bioavailable, Selective, and Potent Allosteric AKT Inhibitor

The work in this paper describes the optimization of the 3-(3-phenyl-3H-imidazo[4,5-b]pyridin-2-yl)pyridin-2-amine chemical series as potent, selective allosteric inhibitors of AKT kinases, leading to the discovery of ARQ 092 (21a). The cocrystal structure of compound 21a bound to full-length AKT1 confirmed the allosteric mode of inhibition of this chemical class and the role of the cyclobutylamine moiety. Compound 21a demonstrated high enzymatic potency against AKT1, AKT2, and AKT3, as well as potent cellular inhibition of AKT activation and the phosphorylation of the downstream target PRAS40. Compound 21a also served as a potent inhibitor of the AKT1-E17K mutant protein and inhibited tumor growth in a human xenograft mouse model of endometrial adenocarcinoma.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Structure-Based Design of Macrocyclic Factor XIa Inhibitors: Discovery of the Macrocyclic Amide Linker

A novel series of macrocyclic FXIa inhibitors was designed based on our lead acyclic phenyl imidazole chemotype. Our initial macrocycles, which were double-digit nanomolar FXIa inhibitors, were further optimized with assistance from utilization of structure-based drug design and ligand bound X-ray crystal structures. This effort resulted in the discovery of a macrocyclic amide linker which was found to form a key hydrogen bond with the carbonyl of Leu41 in the FXIa active site, resulting in potent FXIa inhibitors. Here, the macrocyclic FXIa series, exemplified by compound 16, had a FXIa K i = 0.16 nM with potent anticoagulant activity in an in vitro clotting assay (aPTT EC 1.5x = 0.27 μM) and excellent selectivity against the relevant blood coagulation enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Discovery of an Acrylic Acid Based Tetrahydroisoquinoline as an Orally Bioavailable Selective Estrogen Receptor Degrader for ERα+ Breast Cancer

Tetrahydroisoquinoline 40 has been identified as a potent ERα antagonist and selective estrogen receptor degrader (SERD), exhibiting good oral bioavailability, antitumor efficacy, and SERD activity in vivo. We outline the discovery and chemical optimization of the THIQ scaffold leading to THIQ 40 and showcase the racemization of the scaffold, pharmacokinetic studies in preclinical species, and the in vivo efficacy of THIQ 40 in a MCF-7 human breast cancer xenograft model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Discovery of Potent and Selective Inhibitors for G9a-Like Protein (GLP) Lysine Methyltransferase

G9a-like protein (GLP) and G9a are highly homologous protein lysine methyltransferases (PKMTs) sharing approximately 80% sequence identity in their catalytic domains. GLP and G9a form a heterodimer complex and catalyze mono- and dimethylation of histone H3 lysine 9 and nonhistone substrates. Although they are closely related, GLP and G9a possess distinct physiological and pathophysiological functions. Thus, GLP or G9a selective small-molecule inhibitors are useful tools to dissect their distinct biological functions. We previously reported potent and selective G9a/GLP dual inhibitors including UNC0638 and UNC0642. Here we report the discovery of potent and selective GLP inhibitors including 4 (MS0124) and 18 (MS012), which are >30-fold and 140-fold selective for GLP over G9a and other methyltransferases, respectively. The cocrystal structures of GLP and G9a in the complex with either 4 or 18 displayed virtually identical binding modes and interactions, highlighting the challenges in structure-based design of selective inhibitors for either enzyme.

59 BASIC BIOLOGICAL SCIENCES↗