Circular valorization of Hypericum perforatum biomass into CuO-lignin and CuO-cellulose bionanocomposites for mitigating copper nanotoxicity in plants.

We present a circular biomass valorisation strategy for the synthesis of CuO-based nanocomposites (NCs) using Hypericum perforatum L. In this approach, H. perforatum serves a dual purpose: its phytochemicals are used to synthesize CuO nanoparticles (NPs), while the remaining biomass is used to extract lignin and cellulose.

Recognizing amino acid sidechains in a medium-resolution cryo-electron density map.

Building an accurate atomic structure model of a protein into a cryo-electron microscopy (cryo-EM) map at worse than 3 Å resolution is difficult. To facilitate this task, we devised a method for assigning the amino acid residue sequence to the backbone fragments traced in an input cryo-EM map (EMSequenceFinder). EMSequenceFinder relies on a Bayesian scoring function for ranking 20 standard amino acid residue types at a given backbone position, based on the fit to a density map, map resolution, and secondary structure propensity.

Recognizing amino acid sidechains in a medium resolution cryo-electron density map.

Building an accurate atomic structure model of a protein into a cryo-electron microscopy (cryo-EM) map at worse than 3 Å resolution is difficult. To facilitate this task, we devised a method for assigning the amino acid residue sequence to the backbone fragments traced in an input cryo-EM map (). relies on a Bayesian scoring function for ranking 20 standard amino acid residue types at a given backbone position, based on the fit to a density map, map resolution, and secondary structure propensity.

Machine learning approach toward quantum error mitigation for accurate molecular energetics.

Despite significant efforts, the realization of the hybrid quantum-classical algorithms has predominantly been confined to proof-of-principles, mainly due to the hardware noise. With fault-tolerant implementation being a long-term goal, going beyond small molecules with existing error mitigation (EM) techniques with current noisy intermediate scale quantum devices has been a challenge. That being said, statistical learning methods are promising approaches to learning the noise and its subsequent mitigation.

Chiral Self-Assembly of Biphenyl-Cored Carbohydrate Bolaamphiphiles and Molecular Dynamic Simulation-Derived Mechanistic Insights.

The presence of multiple chiral centers and constitutions in carbohydrates opens up a facile access to uncover supramolecular chirality properties in self-assembled carbohydrate bolaamphiphiles. In this work, bolaamphiphiles are presented that present monosaccharide moieties at the termini of an internal p,p'-biphenyl core segment. The core segment exhibits a planar twisting, which promotes chiral self-assembly of the bolaamphiphiles.

Many-body approach to projective solution of generalized operators: Formulation and application to quantum computing.

In this paper, we propose a novel many-body approach for determining the amplitudes of generalized operators in a projection-based formalism. To implicitly account for the effects of higher-order excitations, we begin with the well-established double-exponential coupled-cluster (CC) ansatz, parametrized by both one- and two-body excitation operators, complemented by a set of vacuum-annihilating two-body generalized operators with effective excitation rank of one. A systematic formalism is developed that effectively bypasses the constraints due to the vacuum-annihilation property of the generalized operators toward a set of closed-form residual equations for their optimization.

Bioinspired design of DNA in aqueous ionic liquid media for sustainable packaging of horseradish peroxidase under biotic stress.

We show that a combination of DNA and ionic liquid significantly increases the stability and activity of HRP and achieves a 4.8-fold higher peroxidase activity than PBS buffer. Also, HRP retains 84% of its activity in IL+DNA compared to 24% in PBS against trypsin digestion.

Toward a resource-optimized dynamic quantum algorithm via non-iterative auxiliary subspace corrections.

Recent quantum algorithms pertaining to electronic structure theory primarily focus on the threshold-based dynamic construction of ansatz by selectively including important many-body operators. These methods can be made systematically more accurate by tuning the threshold to include a greater number of operators into the ansatz. However, such improvements come at the cost of rapid proliferation of the circuit depth, especially for highly correlated molecular systems.

Physical Mechanisms of Improved Performance of Scaffolded Zinc-Silver Battery Cathodes.

Nanostructuring can greatly improve the electrode stability of rechargeable battery systems, such as Zn-Ag. In this report, we investigate the physical mechanisms by which nanostructuring alters structural properties of nanomaterials and thereby influences the structural stability of electrodes. We specifically consider the effects of Au-based nanoscaffolds on Ag.

Unveiling Dissolution Kinetics of CuO Nanofertilizer Using Bio-Based Ionic Liquids Envisaging Controlled Use Efficiency for Sustainable Agriculture.

The need for sustainable agriculture amid a growing population and challenging climatic conditions is hindered by the environmental repercussions of widespread fertilizer use, resulting in the accumulation of metal ions and the loss of micronutrients. The present study provides an approach to improve the efficiency of nanofertilizers by controlling the release of copper (Cu) ions from copper oxide (CuO) nanofertilizers through bioionic liquids based on plant growth regulators (PGR-ILs). A 7-day study was conducted to understand the kinetics of Cu ion release in aqueous solution of five different PGR-ILs, with choline ascorbate ([Cho][Asc]) or choline salicylate ([Cho][Sal]) leading to 200- to 700-fold higher dissolution of Cu ions in comparison to choline indole-3-acetate ([Cho][IAA]), choline indole-3-butyrate ([Cho][IBA]), and choline gibberellate ([Cho][GA]).

Do nanoparticles delivered to roots affect plant secondary metabolism? A comprehensive analysis in float seedling cultures of Hypericum perforatum L.

Since nanoparticles (NPs) released into the environment from household or industrial wastes and applied directly on plants as agrochemicals can accumulate in the rhizosphere, it is imperative to understand how these NPs affect plant secondary metabolism upon their contact with the roots of intact plants. Here, the effects of Pd, Au, ZnO and FeO NPs on secondary metabolism were comprehensively investigated in Hypericum perforatum L float seedlings by analyzing 41 major secondary metabolites using ultra-performance liquid chromatography coupled with photodiode array, fluorescence detector and high-resolution mass spectrometry (UPLC-PDA-FLR-HRMS). The results showed that exposure of H.

Noise-independent route toward the genesis of a COMPACT ansatz for molecular energetics: A dynamic approach.

Recent advances in quantum information and quantum science have inspired the development of various compact, dynamically structured ansätze that are expected to be realizable in Noisy Intermediate-Scale Quantum (NISQ) devices. However, such ansätze construction strategies hitherto developed involve considerable measurements, and thus, they deviate significantly in the NISQ platform from their ideal structures. Therefore, it is imperative that the usage of quantum resources be minimized while retaining the expressivity and dynamical structure of the ansatz that can adapt itself depending on the degree of correlation.

Do Ionic Liquids Exhibit the Required Characteristics to Dissolve, Extract, Stabilize, and Purify Proteins? Past-Present-Future Assessment.

Proteins are highly labile molecules, thus requiring the presence of appropriate solvents and excipients in their liquid milieu to keep their stability and biological activity. In this field, ionic liquids (ILs) have gained momentum in the past years, with a relevant number of works reporting their successful use to dissolve, stabilize, extract, and purify proteins. Different approaches in protein-IL systems have been reported, namely, proteins dissolved in () neat ILs, () ILs as co-solvents, () ILs as adjuvants, () ILs as surfactants, () ILs as phase-forming components of aqueous biphasic systems, and () IL-polymer-protein/peptide conjugates.

Suitability of Adenosine Derivatives in Improving the Activity and Stability of Cytochrome c under Stress: Insights into the Effect of Phosphate Groups.

It is well known that adenosine and its phosphate derivatives play a crucial role in biological phenomena such as apoptosis and cell signaling and act as the energy currency of the cell. Although their interactions with various proteins and enzymes have been described, the focus of this work is to demonstrate the effect of the phosphate group on the activity and stability of the native heme metalloprotein cytochrome c (Cyt c), which is important from both biological and industrial aspects. In situ and in silico characterizations are used to correlate the relationship between the binding affinity of adenosine and its phosphate groups with unfolding behavior, corresponding peroxidase activities, and stability factors.

Non-Native Site-Selective Enzyme Catalysis.

The ability to site-selectively modify equivalent functional groups in a molecule has the potential to streamline syntheses and increase product yields by lowering step counts. Enzymes catalyze site-selective transformations throughout primary and secondary metabolism, but leveraging this capability for non-native substrates and reactions requires a detailed understanding of the potential and limitations of enzyme catalysis and how these bounds can be extended by protein engineering. In this review, we discuss representative examples of site-selective enzyme catalysis involving functional group manipulation and C-H bond functionalization.

Development of a compact Ansatz via operator commutativity screening: Digital quantum simulation of molecular systems.

Recent advancements in quantum information and quantum technology have stimulated a good deal of interest in the development of quantum algorithms toward the determination of the energetics and properties of many-fermionic systems. While the variational quantum eigensolver is the most optimal algorithm in the noisy intermediate scale quantum era, it is imperative to develop compact Ansätze with low-depth quantum circuits that are physically realizable in quantum devices. Within the unitary coupled cluster framework, we develop a disentangled Ansatz construction protocol that can dynamically tailor an optimal Ansatz using the one- and two-body cluster operators and a selection of rank-two scatterers.

Expanding the Reactivity of Flavin Dependent Halogenases Toward Olefins via Enantioselective Intramolecular Haloetherification and Chemoenzymatic Oxidative Rearrangements.

Of the different classes of halogenases characterized to date, flavin dependent halogenases (FDHs) are most associated with site-selective halogenation of electron rich arenes and enol(ate) moieties in the biosynthesis of halogenated natural products. This capability has made them attractive biocatalysts, and extensive efforts have been devoted to both discovering and engineering these enzymes for different applications. We have established that engineered FDHs can catalyze different enantioselective halogenation processes, including halolactonization of simple alkenes with a tethered carboxylate nucleophile.

Machine learning aided dimensionality reduction toward a resource efficient projective quantum eigensolver: Formal development and pilot applications.

In recent times, a variety of hybrid quantum-classical algorithms have been developed that aim to calculate the ground state energies of molecular systems on Noisy Intermediate-Scale Quantum (NISQ) devices. Albeit the utilization of shallow depth circuits in these algorithms, the optimization of ansatz parameters necessitates a substantial number of quantum measurements, leading to prolonged runtimes on the scantly available quantum hardware. Through our work, we lay the general foundation for an interdisciplinary approach that can be used to drastically reduce the dependency of these algorithms on quantum infrastructure.

Designing protein nano-construct in ionic liquid: a boost in efficacy of cytochrome under stresses.

Herein, we present a simple approach to fabricate protein nanoconstructs by complexing cytochrome (Cyt ) with silk nanofibrils (SNF) and choline dihydrogen phosphate ionic liquid (IL). The peroxidase activity of the IL modified Cyt nanoconstruct (Cyt + SNF + IL) increased significantly (2.5 to 10-fold) over unmodified Cyt and showed enhanced catalytic activity and stability under harsh conditions, proving its potential as a suitable protein packaging strategy.

Directed Evolution of an Iron(II)- and α-Ketoglutarate-Dependent Dioxygenase for Site-Selective Azidation of Unactivated Aliphatic C-H Bonds.

Fe - and α-ketoglutarate-dependent halogenases and oxygenases can catalyze site-selective functionalization of C-H bonds via a variety of C-X bond forming reactions, but achieving high chemoselectivity for functionalization using non-native functional groups remains rare. The current study shows that directed evolution can be used to engineer variants of the dioxygenase SadX that address this challenge. Site-selective azidation of succinylated amino acids and a succinylated amine was achieved as a result of mutations throughout the SadX structure.

A Synergistic Approach towards Optimization of Coupled Cluster Amplitudes by Exploiting Dynamical Hierarchy.

The coupled cluster iteration scheme for determining the cluster amplitudes involves a set of nonlinearly coupled difference equations. In the space spanned by the amplitudes, the set of equations are analyzed as a multivariate time-discrete map where the concept of time appears in an implicit manner. With the observation that the cluster amplitudes have difference in their relaxation timescales with respect to the distributions of their magnitudes, the coupled cluster iteration dynamics are considered as a synergistic motion of coexisting slow and fast relaxing modes, manifesting a dynamical hierarchical structure.

The Single-Component Flavin Reductase/Flavin-Dependent Halogenase AetF is a Versatile Catalyst for Selective Bromination and Iodination of Arenes and Olefins.

Flavin-dependent halogenases (FDHs) natively catalyze selective halogenation of electron rich aromatic and enolate groups. Nearly all FDHs reported to date require a separate flavin reductase to supply them with FADH , which complicates biocatalysis applications. In this study, we establish that the single component flavin reductase/flavin dependent halogenase AetF catalyzes halogenation of a diverse set of substrates using a commercially available glucose dehydrogenase to drive its halogenase activity.

Directed Evolution of Flavin-Dependent Halogenases for Site- and Atroposelective Halogenation of 3-Aryl-4(3)-Quinazolinones via Kinetic or Dynamic Kinetic Resolution.

In this study, we engineer a variant of the flavin-dependent halogenase RebH that catalyzes site- and atroposelective halogenation of 3-aryl-4(3)-quinazolinones via kinetic or dynamic kinetic resolution. The required directed evolution uses a combination of random and site-saturation mutagenesis, substrate walking using two probe substrates, and a two-tiered screening approach involving the analysis of variant conversion and then enantioselectivity of improved variants. The resulting variant, 3-T, provides >99:1 e.

Presenting B-DNA as macromolecular crowding agent to improve efficacy of cytochrome c under various stresses.

Existence of numerous biomolecules results in biological fluids to be extremely crowded. Thus, Macromolecular crowding is an essential phenomenon to sustain active conformation of proteins in biological systems. Herein, double helical deoxyribonucleic acid (B-DNA) is presented for the first time as a biomacromolecular crowding system for sustainable packaging of cytochrome c (Cyt C).