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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 19 records

Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge

Elucidating protein–ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein–ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein–ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein–ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein–ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein–ligand interactions on cryo-EM data using prior structural information.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced Configurational Sampling Approaches to Alchemical Ligand Binding Free Energy Simulations: Current Status and Challenges

In this study, ligand binding free energy simulations (LB-FES) have been routine tasks in modern drug discovery campaign. A long-standing challenge for LB-FES is the difficulty in adequately sampling nontrivial environmental reorganizations in response to ligand binding. Therefore, various enhanced configurational sampling (ECS) approaches were devised to speed up fluctuations of relevant slow degrees of freedom (SDOF) and ensure simulation convergence. However, in contrast to the achievements in parametrization, software performance, and workflow automation, efficient ECS methodology suitable for high throughput screening remains in an early stage of development. Here, a review of ECS developments with LB-FES is presented, revisiting current approaches and underlining the major technical pitfalls and challenges. This Perspective focuses on alchemical LB-FES on account of their predominant role in high throughput drug screening as well as the established partnership with ECS. The critical aspects of designing ECS approaches, from both theoretical and applied perspectives, are described. This work is intended to provide a contemporary review of the scientific, technical, and practical issues associated with the accelerating convergence of alchemical LBFES.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. Finally, we provide an analysis of the results and discuss insights into determined best practice methods.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning‐Augmented Molecular Dynamics Simulations (MD) Reveal Insights Into the Disconnect Between Affinity and Activation of ZTP Riboswitch Ligands

Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Chemistry↗

In situ ligand restraints from quantum-mechanical methods

In macromolecular crystallographic structure refinement, ligands present challenges for the generation of geometric restraints due to their large chemical variability, their possible novel nature and their specific interaction with the binding pocket of the protein. Quantum-mechanical approaches are useful for providing accurate ligand geometries, but can be plagued by the number of minima in flexible molecules. In an effort to avoid these issues, the Quantum Mechanical Restraints (QMR) procedure optimizes the ligand geometry in situ , thus accounting for the influence of the macromolecule on the local energy minima of the ligand. The optimized ligand geometry is used to generate target values for geometric restraints during the crystallographic refinement. As demonstrated using a sample of >2330 ligand instances in >1700 protein–ligand models, QMR restraints generally result in lower deviations from the target stereochemistry compared with conventionally generated restraints. In particular, the QMR approach provides accurate torsion restraints for ligands and other entities.

59 BASIC BIOLOGICAL SCIENCES↗

Benchtop access to anhydrous actinide N-donor coordination complexes using ionic liquids [plus supplemental information]

By dehydrating actinide salts with an ionic liquid containing a common anion and subsequent reaction with N-heterocyclic ligands, we challenge the concept that actinides prefer O- over N-donors; rather the acidic hydrogen atoms of protic solvents hinder the formation of more elusive f-element N-donor coordination complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ligand effects on electronic structure and bonding in U(iii) coordination complexes: a combined MCD, EPR and computational study

The trivalent oxidation state of uranium has been shown to undergo unique reactivity, from its ability to activate a variety of small molecules to its role in the catalytic reduction of ethene to ethane amongst others. Central to this unique reactivity and ability to rationally design ligands for isotope separation is the underlying uranium electronic structure. While electronic structure studies of U(IV), U(V), and U(VI) have been extensive, by comparison, analogous studies of more reduced oxidation states such as U(III) remains underdeveloped. Herein we report a combined MCD and EPR spectroscopic approach along with density functional theory and multireference wavefunction calculations to elucidate the effects of ligand perturbation in three uranium(III) Tp* complexes. Overall, the experimental and computational insight suggests that the change in ligand environment across this series of U(III) complexes resulted in only minor perturbations in the uranium electronic structure. This combined approach was also used to redefine the electronic ground state of a U(III) complex with a redox non-innocent Bipy - ligand. Overall, these studies demonstrate the efficacy of the combined experimental and theoretical approach towards evaluating electronic structure and bonding in U(III) complexes and provide important insight into the challenges in altering ligand environments to modify bonding and reactivity in uranium coordination chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Room temperature colossal superparamagnetic order in aminoferrocene–graphene molecular magnets

Intensive studies are published for graphene-based molecular magnets due to their remarkable electric, thermal, and mechanical properties. However, to date, most of all produced molecular magnets are ligand based and subject to challenges regarding the stability of the ligand(s). The lack of long-range coupling limits high operating temperature and leads to a short-range magnetic order. Herein, we introduce an aminoferrocene-based graphene system with room temperature superparamagnetic behavior in the long-range magnetic order that exhibits colossal magnetocrystalline anisotropy of 8 × 10 5 and 3 × 10 7 J/m 3 in aminoferrocene and graphene-based aminoferrocene, respectively. These values are comparable to and even two orders of magnitude larger than pure iron metal. Aminoferrocene [C 10 H 11 FeN] + is synthesized by an electrophilic substitution reaction. It was then reacted with graphene oxide that was prepared by the modified Hammers method. The phase structure and functionalization of surface groups were characterized and confirmed by XRD, FT-IR, and Raman spectroscopy. To model the behavior of the aminoferrocene between two sheets of hydroxylated graphene, we have used density functional theory by placing the aminoferrocene molecule between two highly ordered hydroxylated sheets and allowing the structure to relax. Here, the strong bowing of the isolated graphene sheets suggests that the charge transfer and resulting magnetization could be strongly influenced by pressure effects. In contrast to strategies based on ligands surface attachment, our present work that uses interlayer intercalated aminoferrocene opens routes for future molecular magnets as well as the design of qubit arrays and quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bidentate N‐based Ligands for Highly Reusable, Ligand‐coordinated, Supported Pt Hydrosilylation Catalysts

Abstract A significant challenge in designing supported metal‐ligand catalysts for solution‐phase reactions is the stabilization of the metal active sites against leaching into solution. Here, we examine alkene hydrosilylation reactions as model systems to improve the stability of highly dispersed Pt using a metal‐ligand coordination strategy on high surface area oxide supports. By evaluating a series of bidentate N‐based ligands, we demonstrate several design strategies to improve stability of the highly dispersed Pt 2+ centers against leaching, while maintaining a high level of catalytic activity, selectivity, and recyclability for alkene hydrosilylation batch reactions under mild conditions. These involve a bi‐functional approach to ligand design, which considers interaction to the support and a well‐defined coordination environment for the metal active site. Three strategies are reported: modifying ligands for stronger interaction with oxide surfaces, mixing ligands, and pre‐depositing an “anchoring ligand” to the support before loading the metal‐ligand catalyst. Each of these is successful in enhancing Pt recyclability. Particularly, two Pt‐phenanthroline catalysts exhibit excellent reusability for multiple batch reaction cycles, due to high stability of the active Pt species. Addressing the active site leaching problem significantly enhances the utility of ligand‐coordinated supported metal catalysts as highly stable and selective catalysts for solution‐phase reactions.

Chen, Linxiao↗

Structure-guided approach to modulate small molecule binding to a promiscuous ligand-activated protein

Ligand-binding promiscuity in detoxification systems protects the body from toxicological harm but is a roadblock to drug development due to the difficulty in optimizing small molecules to both retain target potency and avoid metabolic events. Immense effort is invested in evaluating metabolism of molecules to develop safer, more effective treatments, but engineering specificity into or out of promiscuous proteins and their ligands is a challenging task. To better understand the promiscuous nature of detoxification networks, we have used X-ray crystallography to characterize a structural feature of pregnane X receptor (PXR), a nuclear receptor that is activated by diverse molecules (with different structures and sizes) to up-regulate transcription of drug metabolism genes. We found that large ligands expand PXR’s ligand-binding pocket, and the ligand-induced expansion occurs through a specific unfavorable compound-protein clash that likely contributes to reduced binding affinity. Removing the clash by compound modification resulted in more favorable binding modes with significantly enhanced binding affinity. We then engineered the unfavorable ligand-protein clash into a potent, small PXR ligand, resulting in marked reduction in PXR binding and activation. Structural analysis showed that PXR is remodeled, and the modified ligands reposition in the binding pocket to avoid clashes, but the conformational changes result in less favorable binding modes. Thus, ligand-induced binding pocket expansion increases ligand-binding potential of PXR but is an unfavorable event; therefore, drug candidates can be engineered to expand PXR’s ligand-binding pocket and reduce their safety liability due to PXR binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward accelerating rare-earth metal extraction using equivariant neural networks

The separation of rare-earth metals, vital for numerous advanced technologies, is hampered by their similar chemical properties, making ligand discovery a significant challenge. Traditional experimental and quantum chemistry approaches for identifying effective ligands are often resource-intensive. We introduce a machine learning protocol based on an equivariant neural network, Allegro, for the rapid and accurate prediction of binding energies in rare-earth complexes. Key to this work is our newly curated dataset of rare-earth metal complexes—made publicly available to foster further research—systematically generated using the Architector program. This dataset distinctively features functionalized derivatives of proven rare-earth-chelating scaffolds, hydroxypyridinone (HOPO), catecholamide (CAM), and their thio-analogues, selected for their established efficacy in binding these elements. Trained on this valuable resource, our Allegro models demonstrate excellent performance, particularly when trained to directly predict DFT-level binding energies, yielding highly accurate results that closely correlate with theoretical calculations on a diverse test set. Furthermore, this strategy exhibited strong out-of-sample generalization, accurately predicting binding energies for an isomeric HOPO-derivative ligand not seen during training. By substantially reducing computational demands, this machine learning framework, alongside the provided dataset, represent powerful tools to accelerate the high-throughput screening and rational design of novel ligands for efficient rare-earth metal separation.

Gupta, Ankur K. [Lawrence Berkeley National Labora↗

Hybrid Carbon Dioxide Reduction Photocatalysts Consisting of Macrocyclic Cobalt(III) Complexes Deposited on Semiconductor Surfaces

Hybrid photocatalysts can be prepared by coupling metal ligand complexes with light-harvesting semiconductors. It is often challenging and time consuming to derivatize ligands with anchoring groups to effectively attach onto surfaces. In this study, we synthesized hybrid carbon dioxide reduction photocatalysts by directly depositing two macrocyclic Co(III) complexes on three different semiconductor surfaces (TiO 2 , N-Ta 2 O 5 and C 3 N 4 ). The resulting hybrid photocatalysts were characterized with various techniques and tested in CO 2 reduction reactions under different light conditions. Excellent visible-light CO 2 -reduction activity was obtained using C 3 N 4 as the light-harvesting semiconductor. Furthermore, density functional theory calculations were conducted to help understand interactions between the cobalt complexes with a model TiO 2 surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Changes in nitrate binding with lanthanides in BLPhen complexes

Preorganized ligands such as bis-lactam-1,10-phenanthroline (BLPhen) offer unique selectivity trends in solvent extraction of rare-earth ions, particularly from aqueous nitrate solutions. However, due to the ligand’s lipophilicity it is experimentally challenging to obtain crystal structures of the corresponding lanthanide (Ln):ligand complexes to describe the local structure of the first coordination shell and the role of the nitrate ions in the organic phase. In this work, we report first principles molecular dynamics (FPMD) simulations of the complexation of trivalent lanthanide ions (La, Nd, and Eu) with the BLPhen ligand in the presence of nitrate ions in the dichloroethane (DCE) solvent. We find that two nitrate anions are present in the first solvation shell and the third nitrate anion is far from the first solvation shell in all three [Ln(BLPhen) 2 ] 3+ complexes examined. Moving along the lanthanide series from La to Nd to Eu, the binding pocket formed by the two BLPhen ligands shrinks in size; as a result, the two nitrate configuration changes from one-monodentate/one-bidentate binding mode for La and Nd to all monodentate for Eu. Meanwhile, the total coordination number drops from 11 for La and Nd to 10 for Eu. More interestingly, the bidentate binding in [La(BLPhen) 2 ] 3+ and [Nd(BLPhen) 2 ] 3+ complexes is highly dynamic, frequently switching to monodentate and back. The FPMD insights into the differing modes and dynamics of nitrates in the first coordination shell will be useful for further atomistic understanding of the complex structure, formation, and stability in the organic phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure and Reactivity of a High-Spin, Nonheme Iron(III)- Superoxo Complex Supported by Phosphinimide Ligands

Nonheme iron oxygenases utilize dioxygen to accomplish challenging chemical oxidations. Additionally, a further understanding of the Fe-O 2 intermediates implicated in these processes is challenged by their highly transient nature. To that end, we have developed a ligand platform featuring phosphinimide donors intended to stabilize oxidized, high-spin iron complexes. O 2 exposure of single crystals of a three-coordinate Fe(II) complex of this framework allowed for in crystallo trapping of a terminally bound Fe-O 2 complex suitable for XRD characterization. Spectroscopic and computational studies of this species support a high-spin Fe(III) center antiferromagnetically coupled to a superoxide ligand, similar to that proposed for numerous nonheme iron oxygenases. In addition to the apparent stability of this synthetic Fe-O 2 complex, its ability to engage in a range of stoichiometric and catalytic oxidation processes demonstrates that this iron-phosphinimide system is primed for development in modeling oxidizing bioinorganic intermediates and green oxidation chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging Exchange Kinetics for the Synthesis of Atomically Precise Porous Catalysts

Metal-organic frameworks (MOFs) have attracted significant attention as porous catalyst platforms due to the synthetic modularity of these materials and the diversity of lattice-confined catalytic active sites that are readily embedded within periodic crystalline frameworks. MOFs offer platforms to heterogenize molecular catalysts, stabilize novel coordination motifs, and leverage confinement effects in catalysis. Crystallinity allows diffraction-based methods to be employed in the characterization of these catalysts. Access to crystalline MOFs typically requires reversible construction of the metal-ligand (M-L) bonds that connect the SBUs, which provides a mechanism to anneal defects during crystallization. While the required M-L bond reversibility is often promoted by synthesis at elevated temperature, access to crystalline materials based on either transition metals with characteristic slow exchange kinetics or highly basic donor ligands remains a synthetic challenge. Here in this paper, we highlight synthetic strategies that leverage M-L exchange kinetics to access MOFs based on kinetically inert ions and extensions of these strategies to the assembly of atomically precise multimetallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure-based development of a subtype-selective orexin 1 receptor antagonist

Orexin receptors belong to the superfamily of G-protein–coupled receptors (GPCRs) which represent the largest class of drug targets in humans. Despite the recent progress in structural biology, the development of subtype-selective orexin receptor and GPCR ligands in general remains challenging, due to the high sequence similarity among individual receptor subtypes. However, subtype-selective molecules are key to discerning the individual contributions of receptor subtypes to (patho-)physiology. Starting from the clinically used, non–subtype-selective orexin receptor antagonist suvorexant, we demonstrate how docking, crystallography, medicinal chemistry, and in vitro pharmacology can be combined to exploit single amino acid sequence differences for the discovery of subtype-selective probes. Such compounds will help to better understand orexin receptor pharmacology and develop promising drug candidates.

59 BASIC BIOLOGICAL SCIENCES↗

Toll-like Receptor Ligands Enhance Vaccine Efficacy against a Virulent Newcastle Disease Virus Challenge in Chickens

To enhance the efficacy of the current Newcastle disease vaccine, we have selected potential adjuvants that target well-characterized pattern recognition receptors: the toll-like receptors (TLRs). Imiquimod is a small-molecule activator of TLR7, which is a sensor of dsDNA. ODN-1826 is a mimetic of CpG DNA and ligates TLR21 (a chicken homologue of TLR9 in mammals). The activation of TLRs leads to antiviral responses, including the induction of type I interferons (IFNs). In this study, birds were vaccinated intranasally with a live LaSota strain with or without imiquimod or ODN-1826 (50 µg/bird). Two weeks after vaccination, the birds were challenged with a virulent Newcastle disease virus (chicken/CA/212676/2002). Both adjuvants (imiquimod or ODN-1826) induced higher and more uniform antibody titers among vaccinated birds compared with the live vaccine-alone group. In addition, adjuvanted vaccines demonstrated greater protective efficacy in terms of the reduction in virus-shedding titer and the number of birds shedding the challenge virus at 2 and 4 days post-challenge. A differential expression of antiviral and immune-related genes was observed among groups from tissues (Harderian gland, trachea, cecal tonsil, and spleen) collected 1 and 3 days after treatment. These results demonstrate the potential of TLR-targeted adjuvants as mucosal vaccine enhancers and warrant a further characterization of immune correlates and optimization for efficacy.

59 BASIC BIOLOGICAL SCIENCES↗