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At least 163 records · Page 9

Helical Organic and Inorganic Polymers

Despite being a staple of synthetic plastics and biomolecules, helical polymers are scarcely studied with Gaussian-basis-set ab initio electron-correlated methods on an equal footing with molecules. This article introduces an ab initio second-order many-body Green’s-function [MBGF(2)] method with nondiagonal, frequency-dependent Dyson self-energy for infinite helical polymers using screw-axis-symmetry-adapted Gaussian-spherical-harmonics basis functions. Together with the Gaussian-basis-set density-functional theory for energies, analytical atomic forces, translational-period force, and helical-angle force, it can compute correlated energy, quasiparticle energy bands, structures, and vibrational frequencies of an infinite helical polymer, which smoothly converge at the corresponding oligomer results. These methods can handle incommensurable structures, which have an infinite translational period and are hard to characterize by any other method, just as efficiently as commensurable structures. We apply them to polyethylene (2/1 helix), polyacetylene (Peierls’ system), and polytetrafluoroethylene (13/6 helix) to establish the quantitative accuracy of MBGF(2)/cc-pVDZ in simulating their (angle-resolved) ultraviolet photoelectron spectra, and of B3LYP/cc-pVDZ or 6-31G** in reproducing their structures, infrared and Raman band positions, phonon dispersions, and (coherent and incoherent) inelastic neutron scattering spectra. We then predict the same properties for infinitely catenated chains of nitrogen or oxygen and discuss their possible metastable existence under ambient conditions. They include planar zigzag polyazene (N2)x (Peierls’ system), 11/3-helical isotactic polyazane (NH)x, 9/4-helical isotactic polyfluoroazane (NF)x, and 7/2-helical polyoxane (O)x as potential high-energy-density materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Dynamical and Quantum Mechanical Exploration of the Site-Specific Dynamics of Cy3 Dimers Internally Linked to dsDNA

Performing spectroscopic measurements on biomolecules labeled with fluorescent probes is a powerful approach to locating the molecular behavior and dynamics of large systems at specific sites within their local environments. The indocarbocyanine dye Cy3 has emerged as one of the most commonly used chromophores. The incorporation of Cy3 dimers into DNA enhances experimental resolution owing to the spectral characteristics influenced by the geometric orientation of excitonically coupled monomeric units. Various theoretical models and simulations have been utilized to aid in the interpretation of the experimental spectra. In this study, we employ all-atom molecular dynamics simulations to study the structural dynamics of Cy3 dimers internally linked to the dsDNA backbone. We used quantum mechanical calculations to derive insights from both the linear absorption spectra and the circular dichroism data. Furthermore, we explore potential limitations within a commonly used force field for cyanine dyes. The molecular dynamics simulations suggest the presence of four possible Cy3 dimeric populations. The spectral simulations on the four populations show one of them to agree better with the experimental signatures, suggesting it to be the dominant population. Furthermore, the relative orientation of Cy3 in this population compares very well with previous predictions from the Holstein–Frenkel Hamiltonian model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

Selective Adsorption of Thiol-Containing Molecules on Copper Sulfide Surfaces via Molecule–Surface Disulfide Bridges

Recent results in the fields of nanoenhanced agriculture and expanding interest in prebiotic chemistry have placed increased emphasis on understanding the chemically selective interaction of small molecules with the surfaces of metal sulfides. Here, we present an integrated experimental and computational study of the interaction of thiol-containing molecules with copper sulfide (covellite) surfaces in aqueous media. In situ Fourier-transform infrared (FTIR) measurements and ex situ X-ray photoelectron spectroscopy (XPS) measurements show that molecules bearing free thiol groups, including glutathione and cysteine, bind strongly to CuS (covellite) nanoparticles and to CuS (001) single crystals, while control studies show that similar molecules lacking the free thiol group exhibit much less binding. Additional experiments show that these thiol-containing molecules interact transiently with CuO nanoparticle surfaces but are readily removed by rinsing. The FTIR and XPS experiments demonstrate that adsorption of molecular thiols to CuS surfaces occurs in a chemically selective manner. Further experimental studies and density functional calculations show that the preferred mode of binding is through the surface S atoms, forming a Solid–S–S–Molecule disulfide linkage. While the role of disulfide linkages in controlling structure and function of proteins and other biomolecules is widely known, the formation of surface disulfide linkages as a motif for covalent molecular binding at surfaces has not been established previously.

36 MATERIALS SCIENCE↗

Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies

The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. In this work, we present an efficient computational strategy that combines machine learning (ML)-based models and high-fidelity ensemble docking studies to enable rapid screening of possible therapeutic ligands. Targeting the binding affinity of molecules for either the isolated SARS-CoV-2 S-protein at its host receptor region or the S-protein:human ACE2 interface complex, we screen ligands from drug and biomolecule data sets that can potentially limit and/or disrupt the host-virus interactions. Top scoring one hundred eighty-seven ligands (with 75 approved by the Food and Drug Administration) are further validated by all atom docking studies. Important molecular descriptors ( 2 χ n , topological surface area, and ring count) and promising chemical fragments (oxolane, hydroxy, and imidazole) are identified to guide future experiments. Overall, this work expands our knowledge of small-molecule treatment against COVID-19 and provides a general screening pathway (combining quick ML models with expensive high-fidelity simulations) for targeting several chemical/biochemical problems.

60 APPLIED LIFE SCIENCES↗

Immobilization of Cyanines in DNA Produces Systematic Increases in Fluorescence Intensity

Cyanines are useful fluorophores for a myriad of biological labeling applications, but their interactions with biomolecules are unpredictable. Cyanine fluorescence intensity can be highly variable due to complex photoisomerization kinetics, which are exceedingly sensitive to the surrounding environment. This introduces large errors in Förster resonance energy transfer (FRET)-based experiments where fluorescence intensity is the output parameter. However, this environmental sensitivity is a strength from a biological sensing point of view if specific relationships between biomolecular structure and cyanine photophysics can be identified. We describe a set of DNA structures that modulate cyanine fluorescence intensity through the insertion of adenine or thymine bases. These structures simultaneously provide photophysical predictability and tunability. We characterize these structures using steady-state fluorescence measurements, fluorescence correlation spectroscopy (FCS), and time-resolved photoluminescence (TRPL). Here, we find that the photoisomerization rate decreases over an order of magnitude across the adenine series, which is consistent with increasing immobilization of the cyanine moiety by the surrounding DNA structure.

59 BASIC BIOLOGICAL SCIENCES↗

Low-Temperature Gas-Phase Formation of Methanimine (CH 2 NH; X 1 A')–the Simplest Imine–under Single-Collision Conditions

The D1-methanimine molecule (CHDNH; X 1 A') – the simplest (deuterated) imine – has been prepared through the elementary reaction of the D1-methylidyne (CD; X 2 Π) with ammonia (NH 3 ; X 1 A 1 ) under single collision conditions. As a highly reactive species with a carbon-nitrogen double bond and a key building block of biomolecules like amino acids and nucleobases, methanimine is of particular significance in coupling the nitrogen and carbon chemistries in the interstellar medium and in hydrocarbon-rich atmospheres of planets and their moons. However, the underlying formation mechanisms of methanimine in these extreme environments are still elusive. Here, the directed, low-temperature gas-phase formation of D1-methanimine will deepen our fundamental understanding of low-temperature molecular growths processes via carbon-nitrogen bond coupling. Considering the recent detection of the interstellar D1-methylidyne radical, the investigation of the CD–NH 3 system also suggests a promising pathway for future astronomical observations of D1-methanimine as a molecular tracer of gas phase deuterium-enrichment in deep space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determination of Thiol Protonation States by Sulfur X-ray Spectroscopy in Biological Systems

Cysteine is one of the most functionally diverse of the proteinogenic amino acids, owing to its reactive thiol side chain that can undergo deprotonation to form a strongly nucleophilic thiolate. However, few techniques can directly interrogate sulfur charge and covalency in cysteine, particularly in proteins. X-ray spectroscopies provide an element specific probe of sulfur. We demonstrate the sensitivity of S Kβ and Kα X-ray emission spectroscopy (XES) to cysteine ionization and compare it to S K-edge X-ray absorption spectroscopy (XAS) in the physiologically relevant biomolecules l-cysteine and N-acetyl-l-cysteine at room temperature in solution phase. Kβ XES and K-edge XAS are most sensitive to chemical changes at the cysteine thiol and can be used to evaluate the composition of thiol/thiolate mixtures. Furthermore, these results provide a foundation for assessing the pK a of functionally significant cysteine residues in proteins and open the door to time-resolved studies of cysteine-dependent enzymes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗

Molecular Picture of the Transient Nature of Lipid Rafts

In biological membranes, lipid rafts are now thought to be transient and nanoscopic. However, the mechanism responsible for these nanoscopic assemblies remains poorly understood, even in the case of model membranes. Therefore, it has proven extremely challenging to probe the physicochemical properties of lipid rafts at the molecular level. Here, we use all-atom molecular dynamics (MD) simulations and inelastic X-ray scattering (IXS), an intrinsically nanoscale technique, to directly probe the energy transfer and collective short-wavelength dynamics (phonons) of biologically relevant model membranes. We show that the nanoscale propagation of stress in lipid rafts takes place in the form of collective motions made up of longitudinal (compression waves) and transverse (shear waves) molecular vibrations. Importantly, we provide a molecular picture for the so-called van der Waals mediated "force from lipid" [Anishkin, A. et al. Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 7898], a key parameter for the ionic channel mechano-transduction and the mechanism for the lipid transfer of molecular level stress [Aponte-Santamaría, C. et al. J. Am. Chem. Soc. 2017, 139, 13588]. Specifically, we describe how lipid rafts are formed and maintained through the propagation of molecular stress, lipid raft rattling dynamics, and a relaxation process. Eventually, the rafts dissipate through the self-diffusion of lipids making up the rafts. We also show that the molecular stress and viscoelastic properties of transient lipid rafts can be modulated through the use of hydrophobic biomolecules such as melatonin and tryptophan. Overall, the herein proposed mechanism describing the molecular interactions for the formation and dissolution of lipid rafts may offer insights as to how lipid rafts enable biological function.

36 MATERIALS SCIENCE↗

Understanding the Structure and Dynamics of Complex Biomembrane Interactions by Neutron Scattering Techniques

The membrane is one of the key structural materials of biology at the cellular level. Composed predominantly of a bilayer of lipids with embedded and bound proteins, it defines the boundaries of the cell and many organelles essential to life and therefore is involved in almost all biological processes. Membrane-specific interactions, such as drug binding to a membrane receptor or the interactions of an antimicrobial compound with the lipid matrix of a pathogen membrane, are of interest across the scientific disciplines. Herein we present a review, aimed at nonexperts, of the major neutron scattering techniques used in membrane studies: small-angle neutron scattering, neutron membrane diffraction, neutron reflectometry, quasielastic neutron scattering, and neutron spin echo. Neutron scattering techniques are well suited to studying biological membranes. The nondestructive nature of cold neutrons means that samples can be measured for long periods without fear of beam damage from ultraviolet, electron, or X-ray radiation, and neutron beams are highly penetrating, thus offering flexibility in samples and sample environments. Most important is the strong difference in neutron scattering lengths between the two most abundant forms of hydrogen, protium and deuterium. Changing the relative amounts of protium/deuterium in a sample allows the production of a series of neutron scattering data sets, enabling the observation of differing components within complex membrane architectures. This approach can be as simple as using the naturally occurring neutron contrast between different biomolecules to study components in a complex by changing the solution H 2 O/D 2 O ratio or as complex as selectively labeling individual components with hydrogen isotopes. This review presents an overview of each experimental technique with the neutron instrument configuration, related sample preparation and sample environment, and data analysis, highlighted by a special emphasis on using prominent neutron contrast to understand structure and dynamics. This review gives researchers a practical introduction to the often enigmatic suite of neutron beamlines, thereby lowering the barrier to taking advantage of these large-facility techniques to achieve new understandings of membranes and their interactions with other molecules.

59 BASIC BIOLOGICAL SCIENCES↗

Induced Chirality in QDs Using Thermoresponsive Elastin-like Polypeptides

Circular dichroism (CD) spectroscopy has emerged as a potent tool for probing chiral small-molecule ligand exchange on natively achiral quantum dots (QDs). In this study, we report a novel approach to identifying QD–biomolecule interactions by inducing chirality in CdS QDs using thermoresponsive elastin-like polypeptides (ELPs) engineered with C-terminal cysteine residues. Our method is based on a versatile two-step ligand exchange process starting from monodisperse oleate-capped QDs in nonpolar media and proceeding through an easily accessed achiral glycine-capped QD intermediate. Successful conjugation of the ELPs onto the QDs is confirmed by the diagnostic CD response corresponding to the QD electronic transitions in the visible range. The resulting ELP:CdS conjugates demonstrate thermally reversible coacervation, as observed through dynamic light scattering, small-angle X-ray scattering, and electron microscopy. Furthermore, this research provides a foundation for using induced chirality in QD electronic transitions to probe QD conjugation to complex peptides and proteins, opening pathways for designing dynamic, stimuli-responsive hybrid nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protein-Enabled Size-Selective Defect-Sealing of Atomically Thin 2D Membranes for Dialysis and Nanoscale Separations

Atomically thin 2D materials present the potential for advancing membrane separations via a combination of high selectivity (from molecular sieving) and high permeance (due to atomic thinness). However, the creation of a high density of precise nanopores (narrow-size-distribution) over large areas in 2D materials remains challenging, and nonselective leakage from nanopore heterogeneity adversely impacts performance. Here, we demonstrate protein-enabled size-selective defect sealing (PDS) for atomically thin graphene membranes over centimeter scale areas by leveraging the size and reactivity of permeating proteins to preferentially seal larger nanopores (≥4 nm) while preserving a significant amount of smaller nanopores (via steric hindrance). Our defect-sealed nanoporous atomically thin membranes (NATMs) show stability up to ~35 days during size-selective diffusive separations with a model dialysis biomolecule fluorescein isothiocyanate (FITC)-Ficoll 70 in phosphate buffer saline (PBS) solution as well as outperform state-of-the-art commercially available dialysis membranes (molecular-weight-cutoff ~3.5–5 kDa and ~8–10 kDa) with significantly higher permeance for smaller solutes KCl (~0.66 nm) ~5.1–6 × 10 –5 ms –1 and vitamin B12 (B12, ~1.5 nm) ~2.8–4 × 10 –6 ms –1 compared to small protein lysozyme (Lz, ~4 nm) ~4–6.4 × 10 –8 m s –1 , thereby allowing unprecedented selectivity for B12/Lz ~70 and KCl/Lz ~1280. Our work introduces proteins as nanoscale tools for size-selective defect sealing in atomically thin membranes to overcome persistent issues and advance separations for dialysis, protein desalting, small molecule separations/purification, and other bioprocesses.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Soft-Shear-Aligned Vertically Oriented Lamellar Block Copolymers for Template-Free Sub-10 nm Patterning and Hybrid Nanostructures

The template-free unidirectional alignment of lamellar block copolymers (l-BCPs) for sub-10 nm high-resolution patterning and hybrid multicomponent nanostructures is important for technological applications. Here we demonstrate a modified soft-shear directed self-assembly (SDSA) approach for aligning pristine l-BCPs and l-BCPs with incorporated polymer grafted nanoparticles (PGNPs), as well as the l-BCPs conversion to aligned gold nanowires, and hybrid of metallic gold nanowire and dielectric silica nanoparticle in the form of line-dot nanostructures. The smallest patterns have a half-pitch as small as 9.8 nm. In all cases, soft-shear is achieved using a high molecular mass polymer topcoat layer, with support on a neutral bottom layer. We also show that the hybrid line-dot nanostructures have a red-shifted plasmonic response in comparison to the neat gold nanowires. These template-free aligned BCPs and nanowires have potential use in nanopatterning applications and the line-dot nanostructures should be useful in the plasmonic sensing of biomolecules and other molecular species based on the plasmonic response of the nanowires.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser-Assisted Synthesis of Monolayer 2D MoSe 2 Crystals with Tunable Vacancy Concentrations: Implications for Gas and Biosensing

We report tuning the structural and electronic properties of atomically thin two-dimensional (2D) materials via defect and vacancy engineering is the key to enabling their potential use in various applications, including electronics, energy, and sensing devices. Vacancies are, for instance, becoming highly promising for the enhanced interaction of gases and biomolecules with 2D materials in energy and sensing applications. However, the deterministic generation of desirable vacancies with tunable concentrations remains a challenge in 2D materials due to the limitations in the current growth methods, such as the complex reaction chemistries and gas flow dynamics. Therefore, engineering defects and vacancies in 2D materials have been mainly limited to destructive top-down processes such as heating, ion bombardments, and laser postprocessing. Here, we introduce a single-step bottom-up synthesis approach for the growth of monolayer MoSe 2 crystals with tunable vacancy concentrations. This method utilizes the spatiotemporal properties and adjustable power densities of the lasers to control the vaporization dynamics of the stoichiometric MoSe 2 powders. Such a mechanism in the vaporization allows us to grow tunable stoichiometry monolayer MoSe 2–x crystals on the substrates. The localized and time-controlled (250 ms to 2 s) vaporization of the MoSe 2 powder by a CO 2 laser enables the formation of monolayer crystals with controlled vacancy concentrations ranging from ~1 to 20%. The effects of laser power, laser irradiation time, and background pressure on the tuning range and subsequent properties of the crystals are investigated and quantified using Raman and photoluminescence spectroscopy, scanning transmission electron microscopy (STEM), and time-correlated single-photon counting (TCSPC). This bottom-up synthesis is a promising approach that allows the deterministic vacancy tuning for future electronics and, in particular, gas and biosensing applications without the need for further postprocessing and potential structural disruption of the crystals.

2D materials↗

The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior

Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.

Lipids↗

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗