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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mechanistic Similarities and Differences for Hydrogenation of Aromatic Heterocycles and Aliphatic Carbonyls on Sulfided Ru Nanoparticles

This study establishes the contrasting reactivity trends for the hydrogenation of aromatic hydrocarbons (AHCs = C n H m X, X = N, S, O, and C) and aliphatic carbonyls [R a C(O)R b ; R a = alkyl group, R b = CH 3 or H] on sulfided Ru clusters arising from the difference in the elementary proton and hydride attack catalytic sequence. Both reactions require sequential additions of a proton from either Ru n+ –(SH 2 ) or S 2 –(H δ+ ) species and a hydride from Ru n+ –(H δ– ) species to the unsaturated C=X bonds. For the five-membered-ring aromatic heterocycles (AHCs = pyrrole, thiophene, and furan), an initial proton addition limits the catalytic turnovers; thus, their hydrogenation reactivity increases with increasing gas-phase proton affinities of the AHCs. Pyridine as the more basic six-membered N-AHC is more susceptible to protonation; therefore, it is more reactive, and its initial proton addition is quasi-equilibrated, followed by the kinetically relevant hydride addition. Conversely, aliphatic carbonyls prefer to undergo hydrogen additions in a reverse sequence, where a Ru n+ –(H δ– ) hydride initially attacks the electron-deficient carbonyl C atom as the kinetically relevant step before a subsequent rapid S 2 –(H δ+ ) proton addition on the electron-rich O atom, as confirmed by isotopic exchange studies with butanal-D 2 and 1-butanol-D 2 mixtures and density functional theory calculations on S-deficient RuS 2 (100) surfaces. For these reasons, their hydrogenation reactivity increases with increasing gas-phase hydride affinities of the carbonyls. On metallic Ru surfaces without sulfur, hydrogen adatoms (H*) are the only reactive hydrogen species; the reactivity of their attack on aromatic heterocycles increases with increasing reactant proton affinities much more sensitively than that on sulfided Ru surfaces. This work illustrates the distinct catalytic roles of the diverse hydrogen species in hydrogenation—the interplay between proton and hydride additions has marked catalytic consequences in shaping the free energy landscape of the reactions, which in turn leads to the observed kinetic dependences, kinetic parameters, reactivity trends, and scaling relations between the measured barriers and the appropriate kinetic descriptors, that is, proton affinity of AHCs and hydride affinity of carbonyls in hydrogenation catalysis. Here, these mechanistic similarities and differences provide explanations of the observed reactivity trends and thus have profound implications for industrial hydrogenation and hydrotreating catalysis.

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

Quantifying metal-binding specificity of Cc NikZ-II from Clostridium carboxidivorans in the presence of competing metal ions

Many proteins bind transition metal ions as cofactors to carry out their biological functions. Despite binding affinities for divalent transition metal ions being predominantly dictated by the Irving-Williams series for wild-type proteins, in vivo metal ion binding specificity is ensured by intracellular mechanisms that regulate free metal ion concentrations. However, a growing area of biotechnology research considers the use of metal-binding proteins in vitro to purify specific metal ions from wastewater, where specificity is dictated by the protein's metal binding affinities. A goal of metalloprotein engineering is to modulate these affinities to improve a protein's specificity towards a particular metal; however, the quantitative relationship between the affinities and the equilibrium metal-bound protein fractions depends on the underlying binding mechanisms. Here we demonstrate a high-throughput intrinsic tryptophan fluorescence quenching method to validate binding models in multi-metal solutions for CcNikZ-II, a nickel-binding protein from Clostridium carboxidivorans. Using our validated models, we quantify the relationship between binding affinity and specificity in different classes of metal-binding models for CcNikZ-II. In conclusion, we further illustrate the potential relevance of data-informed models to predicting engineering targets for improved specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probing surface-adsorbate interactions through active particle dynamics

Adsorbate molecules present in a reaction mixture may bind to and block catalytic sites. Measurement of the surface coverage of these molecules via adsorption isotherms is critical for modeling and design of catalytic reactions on surfaces. However, it is challenging to measure isotherms in solution in a way that is directly relevant to catalytic activity under reaction conditions, particularly since adsorbates may bind with an enormous range of surface affinity parameters. Here we used the motion of self-propelled catalytic Janus particles, which employ the decomposition of hydrogen peroxide fuel as a propulsion mechanism, to determine the effective surface coverage of thioglycerol, furfural, and ethanol on a platinum surface as a function of concentration in aqueous solution by measuring the decrease in active motion due to the blocking of active sites. For strongly adsorbing thioglycerol, this effective coverage was compared and contrasted to the total adsorbed amount measured using inductively-coupled plasma analysis. Demonstrating the broad applicability of this approach, the surface affinity of the three adsorbates spanned more than four orders of magnitude. For each species, the adsorbate-mediated attenuation of active motion occurred over a wide concentration range and was well-described by a Langmuir isotherm. The strongly interacting thioglycerol had the highest affinity towards the surface (K a = 15.5 ± 4.3 mM –1 ) and fully deactivated the active particle motion at surface saturation. Furfural had an intermediate affinity (K a = 0.42 ± 0.07 mM –1 ) but did not fully block H 2 O 2 access to the surface at apparent saturation, consistent with a maximum fractional surface coverage of θ max = 0.67. Ethanol exhibited even lower affinity (K a = 0.0025 ± 2x10 -4 mM –1 ) and its coverage saturated at only θ max = 0.38. Analysis of isotherms at elevated temperatures enabled direct extraction of the enthalpies of adsorption. The degree of surface coverage at adsorbate saturation appeared to correlate with the relative energies of adsorption for the different adsorbate species and was consistent with adsorbate saturation of one of multiple active site populations towards H 2 O 2 decomposition. Furthermore, computational investigations into solvent effects on furfural adsorption showed good quantitative agreement with the experimental results. This work leverages unique properties of active particles to explore fundamental catalysis questions and demonstrates a novel paradigm for significant and experimentally accessible multidisciplinary research.

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

Structural basis for breadth development in the HIV-1 V3-glycan targeting DH270 antibody clonal lineage

Antibody affinity maturation enables adaptive immune responses to a wide range of pathogens. In some individuals broadly neutralizing antibodies develop to recognize rapidly mutating pathogens with extensive sequence diversity. Vaccine design for pathogens such as HIV-1 and influenza has therefore focused on recapitulating the natural affinity maturation process. Here, we determine structures of antibodies in complex with HIV-1 Envelope for all observed members and ancestral states of the broadly neutralizing HIV-1 V3-glycan targeting DH270 antibody clonal B cell lineage. These structures track the development of neutralization breadth from the unmutated common ancestor and define affinity maturation at high spatial resolution. By elucidating contacts mediated by key mutations at different stages of antibody development we identified sites on the epitope-paratope interface that are the focus of affinity optimization. Thus, our results identify bottlenecks on the path to natural affinity maturation and reveal solutions for these that will inform immunogen design aimed at eliciting a broadly neutralizing immune response by vaccination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Structural and kinetic characterization of an acetoacetyl-Coenzyme A: acetate Coenzyme A transferase from the extreme thermophile Thermosipho melanesiensis

Family 1 Coenzyme A transferases (CtfAB) from the extremely thermophilic bacterium, Thermosipho melanesiensis, has been used for in vivo acetone production up to 70°C. This enzyme has tentatively been identified as the rate-limiting step, due to its relatively low-binding affinity for acetate. However, existing kinetic and mechanistic studies on this enzyme are insufficient to evaluate this hypothesis. Here, kinetic analysis of purified recombinant T. melanesiensis CtfAB showed that it has a ping-pong bi-bi mechanism typical of Coenzyme A (CoA) transferases with Km values for acetate and acetoacetyl-CoA of 85 mM and 135 μM, respectively. Product inhibition by acetyl-CoA was competitive with respect to acetoacetyl-CoA and non-competitive with respect to acetate. Crystal structures of wild-type and mutant T. melanesiensis CtfAB were solved in the presence of acetate and in the presence or absence of acetyl-CoA. These structures led to a proposed structural basis for the competitive and non-competitive inhibition of acetyl-CoA: acetate binds independently of acetyl-CoA in an apparent low-affinity binding pocket in CtfA that is directly adjacent to a catalytic glutamate in CtfB. Similar to other CoA transferases, acetyl-CoA is bound in an apparent high-affinity binding site in CtfB with most interactions occurring between the phospho-ADP of CoA and CtfB residues far from the acetate binding pocket. This structural-based mechanism also explains the organic acid promiscuity of CtfAB. High-affinity interactions are predominantly between the conserved phospho-ADP of CoA, and the variable organic acid binding site is a low-affinity binding site with few specific interactions.

Biochemistry & Molecular Biology↗
DOE OSTI2024

The Uranium-Containing and Thorium-Containing Anions Studied by Photoelectron Spectroscopy

An in-depth knowledge of actinide chemistry is fundamental to many aspects of nuclear science and technology, including the synthesis and processing of materials and the remediation of waste disposal sites. Among the actinides, the chemical bonding behaviors of actinium and thorium resemble those of the transition metals; the 5f-electrons of protactinium, uranium, neptunium, and plutonium often play important roles in their bonding; and among the still heavier elements, their bonding tends to mimic the lanthanide elements in terms of electron shielding and their f-electron contributions. Bonding that involves 5f-electrons, however, is especially important, in part because of the significance of uranium and plutonium, but also because these elements are among the few where f-electron participation in bonding is relatively common. This work focused on studying uranium-containing and thorium-containing anions in the gas phase using negative ion photoelectron spectroscopy. Since this technique directly probed valence electrons, it was uniquely positioned to address open questions regarding molecular bonding and electron configurations. A particularly important issue concerned how bonding in actinide-containing molecules was affected by modifications to their actinide atoms’ environment, i.e., due to their interaction with ligands. A closely related question was how actinide atoms’ suborbitals were qualitatively reordered and their energies quantitatively shifted as a result of their ligated environments. These were especially relevant issues in regard to uranium due to it having multiple possible oxidation states (OS) and the potential for 5f electron participation in bonding. The effects of ligands on oxidation states and 5f-orbital energies in uranium bonding was expected to be pronounced. Both ligands and excess electrons were seen as probes of actinide atoms within actinide-containing molecules. Our strategy for advancing knowledge of chemical bonding in the actinide-containing species utilized the synergy between experiments and theory, where in some cases experimental results validated theory and where in others computational results assisted in interpreting experiments. Calculations on actinide systems are terrifically challenging due to large spin-orbit interactions, relativistic effects, and just the sheer number of electrons involved. Even in the simplest species, e.g., U and U2, the most sophisticated, modern calculations carried out by the most experienced theorists often only approximate experimentally-measured values, such as electron affinities. For theory to provide confident predictions that can be used to solve real problems it needed an iterative and ultimately corrective mechanism by which its methods can develop further. Experiments can be used to identify when theory has failed; whereupon the subsequent process of using the experiment-theory interplay can be used to find the cause of the failure. Upon fixing it in one case, different test species can be proposed and studied by the experiment-theory combination to determine whether the problem has been corrected. Thus, experiments not only measure the values of molecular properties, they also provide navigational 3 beacons that keep computations off the reefs in an otherwise dark sea with few reference points. Experimental measurements in the actinide field are not only important, they are in actuality essential to computational progress. While it was not always possible to compare the theoreticallydetermined quantity of interest directly with the same experimentally-measured observable, it was usually possible to compare consequential properties that are both calculable and measurable. In the work completed here electron affinities and electronic state spacings were often sensitive consequential parameters. Reasonable agreement between measured and computational values signaled that a calculation that was very likely to be on-track. We had established collaborative relationships with five computational groups, all of which have expertise in computational actinide chemistry. Their PI’s are L. Cheng, D. Dixon, L. Gagliardi, K. Peterson, and B. Vlaisavljevich. Our close interaction with our theory partners led to us suggesting systems to them and them to us. This reciprocal interaction between our experimental and their computational results was among the most important strengths of this work and was a thread woven throughout. Even though anion photoelectron spectroscopic studies are conducted on anions, much of the information that they provide, pertains to the electronic structure of the neutral counterparts of those anions; among these are electron affinities and electronically excited state spacings. Our experimental tools included several specialized ion sources for forming the anionic species of interest, a mass spectrometer for identifying and mass-selecting them, and an anion photoelectron spectrometer for determining their electron affinities (EA) and characterizing the electronic states of the selected anions’ neutral counterparts. Anion photoelectron spectroscopy is conducted by crossing a mass-selected beam of anions with a fixed-frequency laser beam and energy-analyzing the resultant photodetached electrons. The photodetachment process is governed by the energyconserving relationship: hν = EBE + EKE, where hν is the photon’s energy, EBE is the electron binding (photodetachment transition) energy, and EKE is the electron’s kinetic energy. In our apparatus mass-selection is accomplished via time-of-flight mass spectrometry (TOF-MS), electron energy analysis is achieved with either a magnetic bottle or by velocity mapped imaging. Photodetachment of electrons from anions is implemented via either Nd:YAG or excimer lasers. The photodetachment transition energy, i.e., the EBE, between the ground vibrational and electronic state of an anion and the ground vibrational and electronic state of that anion’s neutral counterpart is the adiabatic electron affinity (EA) of that neutral molecule. Likewise, photodetachment transitions between the ground vibrational and electronic state of an anion and the various electronically-excited states of that anion’s corresponding neutral map the electronic spectrum of that neutral species, i.e., the spectral spacings in the photoelectron spectrum are a mirror image of the neutral’s electronic spectrum. It was, of course, crucial to be able to form the anionic species of interest. There, we had a particularly broad field of anion sources from which to choose. These included several variants of pulsed laser vaporization (LV), laser photoemission, infrared desorption plus photoemission, pulsed arc discharge (PACIS), electrospray ionization (ESI), and Rydberg electron transfer (RET). Each of these anion sources were readily combined with, i.e., connected to, the anion photoelectron spectroscopic portion of our apparatus as described above. Among the sources that utilize lasers, visible light for LV sources as well as IR for desorption sources are provided by Nd:YAG lasers. Ultraviolet photons are provided by both Nd:YAG and excimer lasers, whereas the excitation wavelengths for RET experiments come from two Nd:YAG-pumped dye lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Opioid agonists binding and responses in SH-SY5Y cells

SH-SY5Y (human neuroblastoma) cultured cells, known to have mu-opioid receptors, have been used to assess and compare the ability of eight representative mu-selective compounds from diverse opioid families to recognize and activate these receptors. A wide range of receptor affinities spanning a factor of 10,000 was found between the highest affinity fentanyl analogs (Ki = 0.1nM) and the lowest affinity analog, meperidine (Ki = 1 microM). A similar range was found for inhibition of PGE1-stimulated cAMP accumulation with a rank order of activities that closely paralleled binding affinities. Maximum inhibition of cAMP accumulation by each compound was about 80%. Maximum stimulation of GTPase activity (approximately 50%) was also similar for all compounds except the lowest affinity meperidine. Both effects were naloxone reversible. These results provide further evidence that mu-receptors are coupled to inhibition of adenylate cyclase and that the SH-SY5Y cell line is a good system for assessment of mu-agonists functional responses.

Non-NASA Center↗
DOE OSTI2022

Modeling receptor flexibility in the structure-based design of KRAS G12C inhibitors

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A machine learning approach for identifying variables associated with risk of developing neutralizing antidrug antibodies to factor VIII

A key unmet need in the management of hemophilia A (HA) is the lack of clinically validated markers that are associated with the development of neutralizing antibodies to Factor VIII (FVIII) (commonly referred to as inhibitors). This study aimed to identify relevant biomarkers for FVIII inhibition using Machine Learning (ML) and Explainable AI (XAI) using the My Life Our Future (MLOF) research repository. The dataset includes biologically relevant variables such as age, race, sex, ethnicity, and the variants in the F8 gene. In addition, we previously carried out Human Leukocyte Antigen Class II (HLA-II) typing on samples obtained from the MLOF repository. Using this information, we derived other patient-specific biologically and genetically important variables. These included identifying the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity calculated using NetMHCIIpan. The data were processed and trained with multiple ML classification models to identify the top performing models. The top performing model was then chosen to apply XAI via SHAP, (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patient. Using XAI we provide a robust and ranked identification of variables that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. These variables could be validated as biomarkers and used in making clinical decisions and during drug development. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles), (iv) the minimum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

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

Effects of SARS-CoV-2 Main Protease Mutations at Positions L50, E166, and L167 Rendering Resistance to Covalent and Noncovalent Inhibitors

SARS-CoV-2 propagation under nirmatrelvir and ensitrelvir pressure selects for main protease (MPro) drug-resistant mutations E166V (DRM2), L50F/E166V (DRM3), E166A/L167F (DRM4), and L50F/E166A/L167F (DRM5). DRM2-DRM5 undergoes N-terminal autoprocessing to produce mature MPro with dimer dissociation constants (K dimer ) 2–3 times larger than that of the wildtype. Co-selection of L50F restores catalytic activity of DRM2 and DRM4 from ~10 to 30%, relative to that of the wild-type enzyme, without altering K dimer . Binding affinities and thermodynamic profiles that parallel the drug selection pressure, exhibiting significant decreases in affinity through entropy/enthalpy compensation, were compared with GC373. Reorganization of the active sites due to mutations observed in the inhibitor-free DRM3 and DRM4 structures as compared to MPro WT may account for the reduced binding affinities, although DRM2 and DRM3 complexes with ensitrelvir are almost identical to MPro WT -ensitrelvir. In conclusion, chemical reactivity changes of the mutant active sites due to differences in electrostatic and protein dynamics effects likely contribute to losses in binding affinities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Polarity-Tolerant Chloride Binding in Foldamer Capsules by Programmed Solvent-Exclusion

Persistent anion binding in a wide range of solution environments is a key challenge that continues to motivate and demand new strategies in synthetic receptor design. Though strong binding in low-polarity solvents has become routine, our ability to maintain high affinities in high-polarity solvents has not yet reached the standard set by nature. Anions are bound and transported regularly in aqueous environments by proteins that use secondary and tertiary structure to isolate anion binding sites from water. Inspired by this principle of solvent exclusion, we created a sequence-defined foldameric capsule whose global minimum conformation displays a helical folded state and is preorganized for 1:1 anion complexation. The high stability of the folded geometry and its ability to exclude solvent were supported by solid-state and solution phase studies. This capsule then withstood a 4-fold increase in solvent dielectric constant (εr) from dichloromethane (9) to acetonitrile (36) while maintaining a high and solvent-independent affinity of 10 5 M –1 ; ΔG ~ 28 kJ mol –1 . This behavior is unusual. More typical of solvent-dependent behavior, Cl – affinities were seen to plummet in control compounds, such as aryl-triazole macrocycles and pentads, with their solvent-exposed binding cavities susceptible to dielectric screening. Finally, dimethyl sulfoxide denatures the foldamer by putative solvent binding, which then lowers the foldamer’s Cl – affinity to normal levels. Furthermore, the design of this capsule demonstrates a new prototype for the development of potent receptors that can operate in polar solvents and has the potential to help manage hydrophilic anions present in the hydrosphere and biosphere.

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

Discovery and characterization of bromodomain 2–specific inhibitors of BRDT

Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined for their ability to compete with JQ1 in BRDT and BRD4 bromodomain AlphaScreen assays. These studies identified CDD-1102 as a selective BRDT-BD2 inhibitor with low nanomolar potency and >1,000-fold selectivity over BRDT-BD1. Structure–activity relationship studies of CDD-1102 produced a series of additional BRDT-BD2/BRD4-BD2 selective inhibitors, including CDD-1302, a truncated analog of CDD-1102 with similar activity, and CDD-1349, an analog with sixfold selectivity for BRDT-BD2 versus BRD4-BD2. BROMOscan bromodomain profiling confirmed the great affinity and selectivity of CDD-1102 and CDD-1302 on all BET BD2 versus BD1 with the highest affinity for BRDT-BD2. Cocrystals of BRDT-BD2 with CDD-1102 and CDD-1302 were determined at 2.27 and 1.90 Å resolution, respectively, and revealed BRDT-BD2 specific contacts that explain the high affinity and selectivity of these compounds. These BD2-specific compounds and their binding to BRDT-BD2 are unique compared with recent reports and enable further evaluation of their nonhormonal contraceptive potential in vitro and in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Allosteric inhibition of the IZUMO1–JUNO fertilization complex by the naturally occurring antisperm antibody OBF13

Sperm IZUMO1 binds to egg JUNO, and this interaction is essential for mammalian fertilization. Isolated from a female mouse immunized with syngeneic sperm, the antisperm antibody OBF13 recognizes IZUMO1 and inhibits murine fertilization. How OBF13 interferes with sperm–egg interactions was unknown. Here, we present the X-ray crystal structure of IZUMO1 in complex with OBF13. OBF13 binds to the apex of the four-helix domain of IZUMO1, distant from the JUNO-binding site. Our crystal structure of OBF13-bound IZUMO1 resembles apo-IZUMO1 and differs from the structure of IZUMO1 in complex with JUNO. We identify that OBF13 carries a low level of somatic hypermutation, and through deep mutational scanning, we engineer an affinity-enhanced OBF13 variant. This OBF13 variant single-chain fragment variable decreases the apparent affinity of IZUMO1 for membrane-bound murine JUNO and blocks the binding of acrosome-reacted sperm to eggs, thereby preventing fertilization. We propose allostery between the OBF13 epitope and the JUNO-binding site. OBF13 inhibits a conformational change in IZUMO1, preventing fusion-competent sperm from adhering to murine eggs during fertilization. Surprisingly, murine IZUMO1 binds to hamster JUNO with an affinity ~20-fold higher than to murine JUNO. The decreased affinity caused by OBF13 of murine IZUMO1 for hamster JUNO is sufficient for murine sperm to bind to and fuse with hamster eggs. Our studies provide a structural and mechanistic framework for species-specific, allosteric inhibition of IZUMO1 by a naturally occurring antisperm antibody and offer insights into the development of immunocontraceptives.

Science & Technology - Other Topics↗
DOE OSTI2024

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small molecule–binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase–1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule–binding proteins with tuned interaction energies is feasible entirely from computation.

Science & Technology - Other Topics↗
DOE OSTI2025

Equivariant Graph Attention Network - 3D Conformers & Feature Fusion

EGAN-3F (Equivariant Graph Attention Network - 3D Conformers & Feature Fusion) presents an innovative approach for predicting binding affinity between small molecules and protein targets, a fundamental task in drug discovery. Traditional structure-based methods often depend on protein-ligand complex structures obtained from crystallography or molecular docking. In contrast, ligand-only machine learning models using 1D or 2D representations such as SMILES have been developed to predict binding affinity without structural information about the target; however, their accuracy is often limited due to the lack of 3D ligand information. EGAN-3F addresses this limitation by integrating spatially aware graph learning with traditional descriptor-based features. We systematically investigate how combining 2D and 3D molecular representations enhances binding affinity prediction from SMILES strings. This approach underscores the importance of modeling conformational diversity and incorporating chemically meaningful descriptors to improve predictive accuracy. The key innovation of EGAN-3F lies in its ability to achieve robust ligand-based binding affinity predictions without requiring protein-ligand complex structures, effectively bridging the gap between purely structural and ligand-only modeling paradigms.

Shim, Heesung [Lawrence Livermore National Laborat↗
DOE OSTI2022

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Blanchard, Andrew E.↗
NASA NTRS1980

Independent-particle models for light negative atomic ions

For the purposes of astrophysical, aeronomical, and laboratory application, a precise independent-particle model for electrons in negative atomic ions of the second and third period is discussed. The optimum-potential model (OPM) of Talman et al. (1979) is first used to generate numerical potentials for eight of these ions. Results for total energies and electron affinities are found to be very close to Hartree-Fock solutions. However, the OPM and HF electron affinities both depart significantly from experimental affinities. For this reason, two analytic potentials are developed whose inner energy levels are very close to the OPM and HF levels but whose last electron eigenvalues are adjusted precisely with the magnitudes of experimental affinities. These models are: (1) a four-parameter analytic characterization of the OPM potential and (2) a two-parameter potential model of the Green, Sellin, Zachor type. The system O(-) or e-O, which is important in upper atmospheric physics is examined in some detail.

Ganas, P. S.↗