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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗
DOE OSTI2022

Design and evaluation of novel analogs of 2-amino-4-boronobutanoic acid (ABBA) as inhibitors of human gamma-glutamyl transpeptidase

Inhibitors of gamma-glutamyl transpeptidase (GGT1, aka gamma-glutamyl transferase) are needed for the treatment of cancer, cardiovascular illness and other diseases. Compounds that inhibit GGT1 have been evaluated in the clinic, but no inhibitor has successfully demonstrated specific and systemic GGT1 inhibition. All have severe side effects. L-2-amino-4-boronobutanoic acid (l-ABBA), a glutamate analog, is the most potent GGT1 inhibitor in vitro. In this study, we have solved the crystal structure of human GGT1 (hGGT1) with ABBA bound in the active site. The structure was interrogated to identify interactions between the enzyme and the inhibitor. Based on these data, a series of novel ABBA analogs were designed and synthesized. Their inhibitory activity against the hydrolysis and transpeptidation activities of hGGT1 were determined. The lead compounds were crystalized with hGGT1 and the structures solved. The kinetic data and structures of the complexes provide new insights into the critical role of protein structure dynamics in developing compounds for inhibition of hGGT1.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Structural and compositional complexities of hierarchical self-assembly: A hypergraph approach

Programmable self-assembly enables the construction of complex molecular, supramolecular, and crystalline architectures from well-designed building blocks. In this work, we introduce a hypergraph-based formalism, Blocks & Bonds (B&B), which generalizes classical chemical graph theory by incorporating directed and multicolored interactions, internal symmetries, and hierarchical organization. Within this framework, we develop the Structure Code (SC), a compact and versatile language for describing self-assembled architectures. We define a Kolmogorov-style structural complexity as the total information content of SC, obtained through its tokenization and Shannon information assignment. Complementing this encoding-based measure, we introduce a much simpler quantity, the compositional complexity, which depends only on the number and cumulative usage of block and bond types in the construction set. A central result of this work is a strong empirical correlation between the token-based structural complexity and the compositional complexity across all examined systems. Owing to this agreement, the compositional complexity emerges as the most practical and broadly applicable measure: it is easy to compute, requires no explicit encoding, and yet closely tracks the actual information content of structurally diverse architectures. Applications to molecular systems (ethylene glycol and glucose), DNA-origami lattices, and crystalline assemblies show that B&B hypergraphs provide a unified, scalable, and information-efficient representation of structural organization, naturally capturing symmetry, modularity, and stereochemistry. This framework establishes a quantitative foundation for complexity-aware classification and inverse design of programmable matter.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Protein Assembly by Design

Proteins are nature’s primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Furthermore, our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

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

Crystallographic Mapping and Tuning of Water Adsorption in Metal–Organic Frameworks Featuring Distinct Open Metal Sites

Crucial steps toward designing water sorption materials and fine-tuning their properties for specific applications include precise identification of adsorption sites and establishment of rigorous molecular-level insight into the water adsorption process. We report stepwise crystallographic mapping and DFT computations of adsorbed water molecules in ALP-MOF-1, a metal-organic framework decorated with distinct open metal sites and carbonyl functional groups that serve as water anchoring sites for seeding the nucleation of a complex water network. Identification of an unusual water adsorption step in ALP-MOF-1 motivated the tuning of metal ion composition to carefully adjust water uptake. These studies provide direct evidence that the identity of the open metal sites in MOFs can dramatically affect water adsorption behavior between 0 and ~20% RH and that multiple proximal water anchoring sites along the MOF skeleton facilitate water uptake steps which could be potentially useful for applications requiring rapid and energetically facile water sorption.

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

Semi-empirical quantum optics for mid-infrared molecular nanophotonics

Nanoscale infrared (IR) resonators with sub-diffraction limited mode volumes and open geometries have emerged as new platforms for implementing cavity quantum electrodynamics at room temperature. The use of IR nanoantennas and tip nanoprobes to study strong light–matter coupling of molecular vibrations with the vacuum field can be exploited for IR quantum control with nanometer spatial and femtosecond temporal resolution. In order to advance the development of molecule-based quantum nanophotonics in the mid-IR, we propose a generally applicable semi-empirical methodology based on quantum optics to describe light–matter interaction in systems driven by mid-IR femtosecond laser pulses. The theory is shown to reproduce recent experiments on the acceleration of the vibrational relaxation rate in infrared nanostructures. It also provides physical insights on the implementation of coherent phase rotations of the near-field using broadband nanotips. We then apply the quantum framework to develop general tip-design rules for the experimental manipulation of vibrational strong coupling and Fano interference effects in open infrared resonators. We finally propose the possibility of transferring the natural anharmonicity of molecular vibrational levels to the resonator near-field in the weak coupling regime to implement intensity-dependent phase shifts of the coupled system response with strong pulses and develop a vibrational chirping model to understand the effect. The semi-empirical quantum theory is equivalent to first-principles techniques based on Maxwell’s equations, but its lower computational cost suggests its use as a rapid design tool for the development of strongly coupled infrared nanophotonic hardware for applications ranging from quantum control of materials to quantum information processing.

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

Accelerated optimization of pure metal and ligand compositions for light-driven hydrogen production

Photocatalytic hydrogen production is a promising alternative to traditional hydrogen production. To implement photocatalytic hydrogen production the development of efficient, sustainable, and stable catalysts is necessary, and overcoming the current challenges surrounding high dimensional search spaces requires both computational and experimental efforts. Utilizing photo driven processes, stable colloidal metal catalysts can be formed in situ for efficient hydrogen production from water. When considering colloidal catalysts, stability is typically a concern solved through the addition of supports or ligands. In this work, poly(ethylene glycol) methyl ether thiol acts as a stabilizing ligand eliminating the need for catalyst supports while providing stable and active nanoparticle catalysts for more than 45 hours of reaction time and illumination. These systems utilize molecular photosensitizers, water reduction catalysts, stabilizing ligands, water, a sacrificial reductant, and organic solvents, posing new challenges pertaining to the optimization of multi-variable systems. Design of experiments (DOE) is applied to accelerate the understanding of variable interactions and is used as a tool to rapidly optimize the compositions of Au, Cu, Ni, and Fe containing systems. Through a collaboration leveraging computation and experimentation (both high throughput and characterizations), optimized performance peaks were obtained for each of these metals alongside distinct mapping of expected activity associated with photosensitizer, metal, and ligand concentration variations. With the highly digitized workflow, this study allowed for comparative generalizations to be made regarding photo driven hydrogen production for all four metals.

08 HYDROGEN↗
DOE OSTI2023

Predicting partner fitness based on spatial structuring in a light-driven microbial community

Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology ( e . g ., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Simplifying the Chemical Design of Nonfused-Ring Electron Acceptors─Lessons Learned from Thienothiophene and Benzodithiophene Cores

Nonfused-ring electron acceptors (NFREA)s have been proposed as alternatives to fused-ring acceptors in organic photovoltaics (OPV)s. The simpler molecular design of NFREAs results in a reduced synthetic complexity, potentially lowering manufacturing costs, and easier access to desired optoelectronic properties by structural modifications. However, they have not seen the same rise in popularity as fused nonfullerene acceptors (NFA)s due to their lower performances in devices. In this work, we explore structure–property relationships of three NFREA molecules based on thieno[3,2-b]thiophene (TT) and benzo[1,2-b:4,5-b′]dithiophene (BDT) cores and malononitrile functionalized-isatin end group acceptors. We describe their synthetic routes, computational analysis, and photophysical and electronic properties. Here, we investigated the effect of changing the core from TT to BDT on electronic properties of the molecules─a result of raising/lowering of the frontier molecular orbital (FMO) levels. We also explored the effect of branched vs nonbranched alkyl groups on the morphological and blend-capabilities in bulk heterojunction (BHJ) OPV devices. These effects were then reflected in the overall device performances, primarily due to favorable FMO energy alignment between the NFREA and polymer. To investigate the behavior of the excited states of the NFREAs within the active layer of the devices, we performed time-resolved microwave conductivity and transient absorption experiments, which confirmed that the TT molecules exhibited very low conductance while the BDT molecule showed moderate photoconductance. Our combined theoretical, synthetic, device, and charge carrier dynamics studies of these materials reveal the central role that structure–property relationships play in future molecular designs of NFREAs that can perform as well as their fused counterparts.

14 SOLAR ENERGY↗
DOE OSTI2021

Tailoring Interfaces in Solid-State Batteries Using Interfacial Thermochemistry and Band Alignment

Solid-state lithium ion batteries have enhanced thermal stability compared to batteries using liquid electrolytes. Although their practical implementation is limited by undesired side reactions between the electrode and electrolyte, different modification strategies have been proposed to stabilize these reactive interfaces. These approaches have been primarily based upon bulk materials properties, however, which may not necessarily be representative of the chemistry at the solid/solid interface. In this work, first principles calculations and X-ray scattering experiments are used to elucidate molecular-level reactivity and develop design principles for tailored interfaces based on surface and interfacial properties. Because of its well-known instability, the interface between the Li metal anode and the lithium lanthanum titanate (LLTO) solid electrolyte is applied as a model system. Density functional theory calculations are used to describe bulk, surface, and interfacial thermochemistry of the Li/LLTO system, and interfacial reconstruction is probed using ab initio molecular dynamics. These simulations of the Li/LLTO interface demonstrate facile decomposition concomitant with reduction of Ti 4+ ions. Based on further insights from computational analysis of the surface band edge positions, La 2 O 3 is proposed as an interlayer coating and is shown to provide an energetic barrier for interfacial charge transfer and decomposition reactions from X-ray reflectivity measurements and theoretical calculations. The findings in this work suggest that design strategies based on surface and interfacial properties can be used to kinetically stabilize electrode/electrolyte interfaces in solid-state batteries.

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

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Particle Sensitivity Analysis

We propose to develop a computational sensitivity analysis capability for Monte Carlo sampling-based particle simulation relevant to Aleph, Cheetah-MC, Empire, Emphasis, ITS, SPARTA, and LAMMPS codes. These software tools model plasmas, radiation transport, low-density fluids, and molecular motion. Our report demonstrates how adjoint optimization methods can be combined with Monte Carlo sampling-based adjoint particle simulation. Our goal is to develop a sensitivity analysis to drive robust design-based optimization for Monte Carlo sampling-based particle simulation - a currently unavailable capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hierarchical assemblies of polypeptoids for rational design of advanced functional nanomaterials

Polypeptoids (poly-N-substituent glycines) are a class of highly tailorable peptidomimetic polymers. Polypeptoids have identical backbones as polypeptides (poly-C-substituent glycines), but sidechains of polypeptoids are appended to backbone nitrogen rather than α-carbon of polypeptides. As a result, peptoid backbone lacks of chirality and hydrogen bond donors. This unique structure gives polypeptoids a combined merit of both high stability as synthetic polymers and biocompatibility as biopolymers. In addition, peptoid sequences can be engineered precisely to assemble specific crystalline patterns such as spheres, fibers, ribbons, tubes, and sheets, which shows promising potentials of polypeptoids for different applications such as antimicrobials, catalysts, drug delivery, and templating inorganic materials. In this review, we summarize recent investigations into hierarchical self-assembly pathways and molecular structures of peptoid crystals that are of interest as templates for fabricating functional materials for potential biomedical, biochemical, and bioengineering applications. Furthermore, this review provides a summary of recent experimental and computational studies of polypeptoid assembly in solution and solid-liquid interfaces, current achievements in the field, and discusses future challenges and opportunities for the rational design of self-assembled polypeptoid nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The physical chemistry of solar fuels catalysis

The demonstration of effective light-driven electrochemical water splitting at the surface of a TiO 2 electrode in the seminal 1972 Honda–Fujishima publication spurred global research efforts to understand this effect and design advanced systems for solar H 2 generation from water as a carbon-free and sustainable fuel. In the 50+ years since that discovery, research investigating approaches toward the catalytic generation of the so-called “solar fuels,” i.e., not only H 2 from water but also CO 2 reduction products and NH 3 from N 2 , has expanded dramatically in scope and scale. The development of new experimental and computational methods and construction and commissioning of large-scale facilities have paved the way for important insights into the machinery of natural photosynthesis, leading to a greater understanding of the complexity of light-to-chemical energy conversion with an exquisite temporal and spatial resolution. Finally, these studies have provided the foundation for biologically inspired molecular and hybrid designs with the goal to promote the photochemical steps critical to solar fuels generation while avoiding unproductive or unnecessary pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗
DOE OSTI2026

Data‐Driven Engineering of Thermostable Collagen‐Mimetic Peptoid Triple Helices

Collagen-mimetic peptides (CMPs) are engineered molecules designed to replicate the triple-helical structure of natural collagen. A repeating x–y-Gly sequence is the defining motif of CMPs and is critical to their triple-helical structure and stability. Substitutions to the residues occupying the x and y positions present a means to modulate the CMP structure and properties. Peptoid residues—N-substituted glycine derivatives—present an attractive potential substitution due to their thermal stability, proteolytic resistance, biocompatibility, and diverse palette of non-natural side chains, but also tend to introduce a high degree of backbone flexibility that can diminish the stability of the triple helix. In this work, we report a computational active learning cycle comprising molecular dynamics simulation, Gaussian process regression, and Bayesian optimization to computationally identify a number of promising peptoid substitutions predicted to stabilize the desired quaternary structure through side chain interactions and produce stable peptoid-based collagen-like triple helices. To experimentally test the computational predictions, a top candidate identified by the screen was synthesized and imaged using scanning electron microscopy to resolve fibril-like bundles consistent with collagen-like triple helices. This work predicts a number of CMP peptoid substitutions capable of forming stable triple-helical structures, presents a generalizable design strategy for engineering desired peptoid structures, and opens new avenues for the design of peptoid-based biomimetic materials.

active learning↗
DOE OSTI2025

QM Investigation of Rare Earth Ion Interactions with First Hydration Shell Waters and Protein-Based Coordination Models

Here, conventional methods for extracting rare earth metals (REMs) from mined mineral ores are inefficient, expensive, and environmentally damaging. Recent discovery of lanmodulin (LanM), a protein that coordinates REMs with high-affinity and selectivity over competing ions, provides inspiration for new REM refinement methods. Here, we used quantum mechanical (QM) methods to investigate trivalent lanthanide cation (Ln 3+ ) interactions with coordination systems representing bulk solvent water and protein binding sites. Energy decomposition analysis (EDA) showed differences in the energetic components of Ln 3+ interaction with representatives of solvent (water, H 2 O) and protein binding sites (acetate, CH 3 COO – ), highlighting the importance of accurate description of electrostatics and polarization in computational modeling of REM interactions with biological and bioinspired molecules. Relative binding free energies were obtained for Ln 3+ with coordination complexes originating from binding sites in PDB structures of a lanthanum binding peptide (PDB entry 7CCO) and LanM, with explicit consideration of the first hydration shell waters, according to quasi-chemical theory (QCT). Beyond the first shell, the bulk solvent environment was represented with an implicit continuum model. Ln 3+ interactions with (H 2 O) 9 and both binding site models became more favorable, moving down the periodic series. This trend was more pronounced with the protein binding site models than with water, resulting in affinity increasing with periodic number, except for the last REM, Lu 3+ , which bound less favorably than the preceding element, Yb 3+ . Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. Conversely, the previously reported experimental data for LanM show a preference for the earlier lanthanides; this is likely due to longer-range interactions and cooperative effects, which are not represented by the reduced models. Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. In contrast to the previously reported experimental data for LanM, the peptide preferentially binds the earlier lanthanides. This difference likely arises due to longer-range interactions and cooperative effects not represented by the peptide. Further investigation of Ln 3+ interactions with whole proteins using polarizable molecular mechanics models with explicit solvent is warranted to understand the influence of longer-ranged interactions, cooperativity, and bulk solvent. Nevertheless, the present work provides new insights into Ln 3+ interactions with biomolecules and presents an effective computational platform for designing specific single-site REM binding peptides more efficiently.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗