Energetic Analysis Research Articles

A DFT Study of Band-Gap Tuning in 2D Black Phosphorus via Li+, Na+, Mg2+, and Ca2+ Ions

Black phosphorus (BP) and its two-dimensional derivative (2D-BP) have garnered significant attention as promising anode materials for electrochemical energy storage devices, including next-generation fast-charging batteries. However, the interactions between BP and light metal ions, as well as how these interactions influence BP’s electronic properties, remain poorly understood. Here, we employed density functional theory (DFT) to investigate the effects of monovalent (Li+ and Na+) and divalent (Mg2+ and Ca2+) ions on the valence electronic structure of 2D-BP. Molecular orbital analysis revealed that the adsorption of divalent cations can significantly reduce the band gap, suggesting an enhancement in charge transfer rates. In contrast, the adsorption of monovalent cations had minimal impact on the band gap, suggesting the preservation of 2D-BP’s intrinsic electrical properties. Energetic and charge analyses indicated that the extent of charge transfer primarily governs the ability of ions to modulate 2D-BP’s electronic structure, especially under high-pressure conditions where ions are in close proximity to the 2D-BP surface. Moreover, charge polarization calculations revealed that, compared with monovalent cations, divalent cations induced greater polarization, disrupting the symmetry of the pristine 2D-BP and further influencing its electronic characteristics. These findings provide a molecular-level understanding of how ion interactions influence 2D-BP’s electronic properties during ion-intercalation processes, where ions are in close proximity to the 2D-BP surface. Moreover, the calculated diffusion barrier results revealed the potential of 2D-BP as an effective anode material for lithium-ion, sodium-ion, and magnesium-ion batteries, though its performance may be limited for calcium-ion batteries. By extending our understanding of interactions between ions and 2D-BP, this work contributes to the design of efficient and reliable energy storage technologies, particularly for the next-generation fast-charging batteries.

Energetic, exergetic, and exergoeconomic analyses of beer wort production processes

Energy efficiency strategies in industrial breweries examine the inefficiency of thermal systems from a thermodynamic perspective. However, understanding the costs of inefficiencies in systems, including non-thermodynamic costs, requires exergoeconomics. This study examined wort production in a standard Tier-1 brewery from the tripod of energy, exergy, and exergoeconomics analyses to assess the performance of brewing sections and to pinpoint components that contributed the most to exergy destruction and product cost rate. The energy analyses for the production system showed that the total specific energy for processing 10.05 tons of brew grains to 346.98 hL high-gravity wort was (86 ± 1) MJ/hL at an operational energy efficiency of 30.35%. The exergetic analyses showed that the cumulative exergetic destruction was 3.2737 MW, with the brewhouse section contributing 89.25% of the system’s inefficiencies. Also, the analyses showed that the wort kettle (42.7911%), mash tun (10.8086%), preheater (10.0683%), whirlpool (8.3522%), and adjunct kettle (6.2705%) are the top five components with the highest rates of cumulative exergy destruction. The exergoeconomic analyses revealed that the cost rate of processing chilled wort was estimated to be 0.0681 USD/s per overall exergetic efficiency of 6.61%. The five most significant components are the wort kettle (53.70%), whirlpool (16.42%), mash filter (10.44%), mash tun (6.875%), and adjunct kettle (3.31%) based on the relative total cost increases for the production processes. Additionally, wet steam throttling resulted in a 2.51% increase in exergetic efficiency, a 1.60% drop in exergetic destruction rate, and a decrease in cost rates to 0.0675 USD/s.

Molecular and energetic analysis of the interaction and specificity of Maximin 3 with lipid membranes: In vitro and in silico assessments.

In this study, the interaction of antimicrobial peptide Maximin 3 (Max3) with three different lipid bilayer models was investigated to gain insight into its mechanism of action and membrane specificity. Bilayer perturbation assays using liposome calcein leakage dose-response curves revealed that Max3 is a selective membrane-active peptide. Dynamic light scattering recordings suggest that the peptide incorporates into the liposomal structure without producing a detergent effect. Langmuir monolayer compression assays confirmed the membrane inserting capacity of the peptide. Attenuated total reflection-Fourier transform infrared spectroscopy showed that the fingerprint signals of lipid phospholipid hydrophilic head groups and hydrophobic acyl chains are altered due to Max3-membrane interaction. On the other hand, all-atom molecular dynamics simulations (MDS) of the initial interaction with the membrane surface corroborated peptide-membrane selectivity. Peptide transmembrane MDS shed light on how the peptide differentially modifies lipid bilayer properties. Molecular mechanics Poisson-Boltzmann surface area calculations revealed a specific electrostatic interaction fingerprint of the peptide for each membrane model with which they were tested. The data generated from the in silico approach could account for some of the differences observed experimentally in the activity and selectivity of Max3.

Effective remediation of toxic metal ions (Cd(II), Pb(II), Hg(II), and Ba(II)) using mesoporous glauconite-based iron silicate nanorods: Experimental and theoretical studies

Glauconite minerals underwent an advanced exfoliation and scrolling process, yielding novel iron silicate nanorods (GRs) with increased surface area, reactivity, and improved physicochemical properties. These structures were introduced as superior adsorbents for the highly efficient adsorption of various toxic metal ions, such as Cd(II), Pb(II), Hg(II), and Ba(II). The GRs exhibited maximum adsorption capacities of 283 mg/g for Cd(II), 247 mg/g for Pb(II), 132.3 mg/g for Hg(II), and 165.2 mg/g for Ba(II). The adsorption properties of the GRs during the adsorption of these four metal ions were elucidated through traditional (Langmuir model) and advanced (monolayer model of single energy site) isotherm analyses. Advanced isotherm modeling revealed that the GR surface was saturated with numerous effective adsorption sites, with densities of 125 mg/g for Cd(II), 68.8 mg/g for Pb(II), 40.9 mg/g for Hg(II), and 57.9 mg/g for Ba(II). Moreover, each site could accommodate approximately four ions of the studied metals, which are vertically oriented and participate in multi-ionic adsorption reactions. Energetic analyses, whether based on classical models (Gaussian energy <8 kJ/mol) or advanced models (adsorption energy <40 kJ/mol), indicated that the adsorption processes are governed by physical mechanisms, including electrostatic attractions, van der Waals forces, and hydrogen bonding. Furthermore, thermodynamic assessments confirmed that the adsorption of these ions occurs through exothermic and spontaneous reactions.

Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme–ligand complexes

Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with time-consuming molecular dynamics simulations, but much faster. The optimized and validated pipeline was applied to annotate more than 17,000 cognate enzyme–ligand complexes. Analysis of ligand un/binding energetics indicates that the top priority tunnel has the most favourable energies in 75% of cases. Moreover, energy profiles of cognate ligands revealed that a simple geometry analysis can correctly identify tunnel bottlenecks only in 50% of cases. Our study provides essential information for the interpretation of results from tunnel calculation and energy profiling in mechanistic enzymology and protein engineering. We formulated several simple rules allowing identification of biochemically relevant tunnels based on the binding pockets, tunnel geometry, and ligand transport energy profiles.Scientific contributionsThe pipeline introduced in this work allows for the detailed analysis of a large set of protein–ligand complexes, focusing on transport pathways. We are introducing a novel predictor for determining the relevance of binding pockets for tunnel calculation. For the first time in the field, we present a high-throughput energetic analysis of ligand binding and unbinding, showing that approximate methods for these simulations can identify additional mutagenesis hotspots in enzymes compared to purely geometrical methods. The predictor is included in the supplementary material and can also be accessed at https://github.com/Faranehhad/Large-Scale-Pocket-Tunnel-Annotation.git. The tunnel data calculated in this study has been made publicly available as part of the ChannelsDB 2.0 database, accessible at https://channelsdb2.biodata.ceitec.cz/.

Chemical-bonding and lattice-deformation mechanisms unifying the stability and diffusion trends of hydrogen in TiN and AlN polymorphs

The continuous development of hydrogen-permeation barriers (HPB) based on metal nitrides highly desires a generic unification of the key thermodynamic and kinetic mechanisms therein. This work employs first-principles calculations to study the stability and diffusion trends of H impurity in the rock-salt, wurtzite, and sphalerite phases of the prototypical TiN and AlN. The formation energies (Ef) of H at various interstitial and vacant sites in these nitrides are calculated, and the underlying chemical-bonding and lattice-deformation mechanisms are self-consistently revealed by the systematic structual, energetic, and electronic-structure analyses. This leads to the discovery of a generic volcanic trend of Ef in terms of the electron number on H (QH), which well portrays how the covalent-ionic H–N and H–metal bondings determine its stability in different atomistic environments. Then, the kinetic properties (e.g., potential barriers, diffusion coefficients, and isotope effects) of interstitial H in these nitrides are calculated, where the volcanic Ef–QH relationship is applied to better understand the joint contributions of chemical bonding and lattice deformation. Finally, the revealed mechanisms and volcanic Ef–QH relationship are generalized to successfully describe the behaviors of H in some important grain boundaries of c-TiN and c-AlN, including the Σ3{112}〈110〉 twin frequently observed in c-TiN and the Σ5{210}〈001〉 twin prototypical to many rock-salt materials. The widely varying hydrogen permeabilities measured in experiment on many nitride coatings are successfully explained, inspiring more useful chemical principles to guide the design of HPB coatings facing harsh environments with long-term reliability.

Austenite-martensite interfacial patterns and energy dissipation of phase transformation in Ni-Mn-Ga single crystal

The martensitic phase transformation occurs in Shape Memory Alloys (SMA) via the nucleation/propagation of the Austenite-Martensite interface (A-M interface), which is a transition region (domain) between the two coexisting phases. For providing compatibility, the transition region consists of various martensitic twin structures (laminates), forming different interfacial patterns, such as parallel laminates and branching laminates. Due to the energy accumulation in the interfacial structures (e.g., elastic mismatch and twin-boundary surface energy), the interfacial patterns should be relevant to the driving force (energy dissipation) and the associated kinetics of the phase transformation. In this paper, we adopt a special thermal loading, small-temperature-gradient “heating-cooling-reheating”, to control the A-M interface's forward and reverse propagation to generate different interfacial patterns in a Ni-Mn-Ga single crystal SMA with the observation on the twin structures (by optical microscope and SEM) and the InfraRed measurement on the temperature hysteresis of the interface propagation (for characterizing the thermal driving force). Simple energetic analysis indicates that the thermal driving force (energy dissipation) is directly related to the stored energy in the interfacial structure, particularly the large mismatch elastic energy near the habit plane. This study not only provides the details of the various interfacial patterns and their dependence on the loading path, but also indicates the driving force and the associated mechanism about the pattern evolution to understand the phase transformation process.

Adjustments to Climate Perturbations—Mechanisms, Implications, Observational Constraints

AbstractSince the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global‐mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015, https://doi.org/10.1175/bams‐d‐13‐00167.1), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change.

Comparative First-Principles Study of the Y2Ti2O7/Matrix Interface in ODS Alloys

Oxide-dispersion-strengthened (ODS) alloys generally exhibit extraordinary service performance under severe conditions through the formation of ultrafine nano oxides. Y2Ti2O7 has been characterized as the major strengthening oxide in Fe-based ODS alloys. First-principles energetic analyses were performed to investigate the structural, elastic and interface properties of Y2Ti2O7 in either Fe-based or Ni-based ODS alloys. Y2Ti2O7 has comparable elastic constants to bcc-Fe and fcc-Ni and similar elastic deformation compatibility in Y2Ti2O7-strengthened Fe-based and Ni-based ODS alloys is therefore expected. The Ni/oxide interface has generally better thermostability than Fe/oxide across the whole range of the concerned oxygen chemical potential. Further interface bonding and adhesion calculations revealed that Y2Ti2O7 can enhance the bonding strength of Ni/Y2Ti2O7 through d-d orbital interaction between the interfacial YTi layer and Ni layer, while the interface bonding between the Fe layer and YTi layer is weakened compared to the metal matrix. First-principles calculations suggest that Y2Ti2O7 can be a candidate for strengthening nano-oxides in either Fe-based or Ni-based ODS alloys with well-behaved mechanical properties for fourth-generation fission reactors and further experimental validations are encouraged.

Analysis of Heat Exchanger for Single-Phase Cooling Applications using Micro-channels of Copper Material

The design of a microchannel heat exchanger can be achieved using various approaches. The design includes various materials, such as ceramics, silicon, metals, and polymers, that are used to make microchannels, depending on their specific requirements. Polymers such as silicon, glass, and other polymeric materials are utilized on metallic substrates. The current study includes microchannels fabricated from metallic copper. Further, the design solutions do not consider the implications of the second law of thermodynamics. Hence, performing an energetic analysis of microchannels is imperative to design and assess thermodynamic systems that use them efficiently. One technique to improve a thermodynamic system's efficiency is using a well-designed microchannel heat exchanger with excellent energetic performance. This can be achieved by creating a thermodynamic system that eliminates energetic losses and limits only unavoidable losses. The use of high-conductivity material like copper also achieves this. To identify possible reasons for exergy loss and perhaps address them, a thorough energetic analysis of an existing heat exchanger is necessary. A microchannel heat exchanger with 19 microchannels in a flat tube is considered for this study. The study finds the energetic losses, which are useful for the thermal design of the heat exchanger.

On the mechanism and energetics of electrochemical alloy formation between mercury and platinum for mercury removal from aqueous solutions

Mercury pollution is an acute global concern threatening the health of humans and wildlife. Thus, there is a need for new and improved techniques to reduce emissions and remove toxic mercury from aqueous environments. Electrochemical alloy formation, specifically between mercury ions in aqueous solution and a platinum electrode, emerges as a promising solution. Through analysis of reaction mechanisms and energetics related to the formation and dissolution of the PtHg4 alloy, this study aims to deepen our understanding of the underlying processes of effective electrochemical mercury removal. Potentiodynamic measurements indicate rapid alloy formation at a clean platinum surface, proceeding with only trace amounts of metallic mercury on the surface. However, once the electrode surface has sufficient mercury coverage with an alloy thickness of around 1.5 nm, clear evidence of metallic mercury on the surface is observed. Furthermore, the amount of absorbed mercury on the cathode increases linearly in time. The onset potential for the alloy formation is experimentally determined using electrochemical quartz crystal microbalance with dissipation monitoring to be approximately 0.64 V vs. SHE, and the alloy dissolution (oxidation) onset potential is found to be approximately 0.98 V vs. SHE, at a mercury ion concentration of 10 mg/L. Density functional theory calculations are used to provide a theoretical value for the reversible potential from a thermodynamics perspective, yielding a value of 0.78 V vs. SHE at a mercury ion concentration of 10 mg/L. This value is in excellent agreement with the experimental results, suggesting an overpotential of about 0.14 and 0.20 V for the alloy formation and oxidation, respectively. These findings provide important information on the reaction mechanisms and overpotentials of the PtHg4 alloy formation and dissolution, which are key factors for development of large-scale mercury removal based on this technique, as well as fundamental understanding of the electrochemical alloy formation between mercury ions and platinum.

Design, Synthesis, and Biological Evaluation of Darunavir Analogs as HIV-1 Protease Inhibitors.

Darunavir, a frontline treatment for HIV infection, faces limitations due to emerging multidrug resistant (MDR) HIV strains, necessitating the development of analogs with improved activity. In this study, a combinatorial in silico approach was used to initially design a series of HIV-1 PI analogs with modifications at key sites, P1' and P2', to enhance interactions with HIV-1 PR. Fifteen analogs with promising binding scores were selected for synthesis and evaluated for the HIV-1 PR inhibition activity. The variation of P2' substitution was found to be effective, as seen in 5aa (1.54 nM), 5ad (0.71 nM), 5ac (0.31 nM), 5ae (0.28 nM), and 5af (1.12 nM), featuring halogen, aliphatic, and alkoxy functionalities on the phenyl sulfoxide motif exhibited superior inhibition against HIV-1 PR compared to DRV, with minimal cytotoxicity observed in Vero and 293T cell lines. Moreover, computational studies demonstrated the potential of selected analogs to inhibit various HIV-1 PR mutations, including I54M and I84V. Further structural dynamics and energetic analyses confirmed the stability and binding affinity of promising analogs, particularly 5ae, which showed strong interactions with key residues in HIV-1 PR. Overall, this study underscores the importance of flexible moieties and interaction enhancement at the S2' subsite of HIV-1 PR in developing effective DRV analogs to combat HIV and other global health issues.

Energetic and economic analysis of a novel concentrating solar air heater using linear Fresnel collector for industrial process heat

Industrial processes share a relevant portion of global energy consumption. A large variety of high energy-demanding industrial processes need hot air in the medium temperature range, provided by natural gas combustion or by electricity. Hot air is used as a medium in a large variety of processes such as drying, curing, and thermal treatments of several products and materials. Heat can be provided by solar thermal technologies aimed at the sustainable industry. Non-concentrating flat plate type solar collectors can directly heat air up to 100 °C while higher temperatures can be achieved using linear concentrating technology. In this study an innovative system using linear Fresnel collectors directly provides hot air for the industry up to 350 °C, avoiding the need for liquid heat transfer fluids. Accordingly, the installation is simplified, and lower installation and maintenance requirements are expected compared to other solar technologies. The present studies provide an energetic and economic analysis of the concentrating solar air heater, considering a medium-scale benchmark as a reference case in representative European locations. The results indicate that the solar technology here presented can be economically competitive with conventional natural gas heating, having a huge potential for fossil fuel source replacement in hot air based industrial processes.

AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance.

The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore ACE2-binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class 1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.

Energetic and Exergetic Analyses of a Double-Pass Tubular Absorber for Application in Solar Towers

Abstract The present research integrates the concept of double-pass (DP) flows with high-temperature solar receivers to introduce an innovative design aimed at minimizing heat losses and optimizing performance. The new DP system was developed using a tubular absorber derived from billboard solar tower technology and operated with air as the heat transfer medium. Computational fluid dynamic models are developed based on an experimental campaign conducted at a solar furnace facility. The computational analyses indicated that employing the DP design instead of single-pass (SP) absorbers results in an average enhancement of energy and exergy efficiency by 35% and 225%, respectively, across all test conditions. However, this enhancement is accompanied by an average increase in pressure drop of ∼60%. The detailed exergy analysis also revealed the contribution of each term in the exergetic performance, identifying the exergy destruction between the sun and the absorber as the primary source, accounting for an average of ∼65% of the total inlet exergy for both SP and DP absorbers. Consequently, the DP presents itself as a promising alternative design for future solar tower configurations, offering improved Nu numbers up to ∼50% in air-based solar systems.

Monte Carlo QM/MM simulation studies of the Cannizzaro reaction in ionic liquids for improved biofuel production.

The conversion of biomass to 5-hydroxymethylfurfural (HMF) holds substantial promise as a renewable energy source. Notably, HMF can be transformed into 2,5-bis(hydroxymethyl)furan (BHMF), a crucial reactant in biofuel production, but requires harsh operating conditions, H2, and precious metal catalysts. A recently reported Cannizzaro reaction of HMF to BHMF, characterized by its efficiency, mild conditions, and eco-friendliness, instead employed ionic liquids (ILs) to achieve high yields. In this study, combined quantum mechanical and molecular mechanical (QM/MM) simulations in conjunction with Metropolis Monte Carlo statistical mechanics and free-energy perturbation theory utilized M06-2X/6-31+G(d), PDDG/PM3, and the OPLS-VSIL force field to uncover important solute-solvent interactions present in the HMF to BHMF reaction pathway. The Cannizzaro reaction was examined in water and in five ILs composed of the 1-butyl-3-methylimidazolium [BMIM] cation coupled to hexafluorophosphate, tetrafluoroborate, thiocyanate, chloride, and bromide. Energetic and structural analysis of the rate-determining hydride transfer between HMF and the hydride-donor anion HMFOH- attributed the enhanced reactivity to highly organized solvent interactions featuring (1) hydrogen bonding between the ring protons of [BMIM] and the negatively charged carbonyl oxygen atoms on the transition structure, (2) favorable electrostatic interactions between the IL anions and solute hydroxyl groups, and (3) beneficial π-π stacking interactions between [BMIM] and the two aromatic rings present in HMF and HMFOH-.

Multiferroicity in a two-dimensional vanadium dioxide

Two-dimensional (2D) multiferroic materials have attracted great interest owing to the integration of ferroelastic and ferromagnetic properties. We identify a novel 2D multiferroic vanadium dioxide (VO₂) monolayer exhibiting a monoclinic phase with a C2/m space group using density functional theory (DFT) calculations. The energetic, dynamic, thermodynamic and mechanical analyses indicate that the monolayer exhibits excellent stability and can be prepared experimentally. The arrangement of the electronic energy bands is analogous to that of a type I heterostructure. The electron doping at a concentration of 0.2 electrons per V atom results in a significant increase in the Curie temperature (TC) from 11.2 to 184 K estimated by Monte Carlo simulations, and a transition from semiconductor to half-metallicity. In addition, the VO₂ monolayer exhibits 120° ferroelastic switching with a moderate switching energy barrier of 32 meV per atom, subsequently allowing 120° rotation of the easy magnetisation axis. Our work reveals the intrinsic multiferroicity of VO₂, which may provide a guidance on the design of next-generation mechanical/spintronic devices.

Computational design and experimental confirmation of a disulfide-stapled YAP helixα1-trap derived from TEAD4 helical hairpin to selectively capture YAP α1-helix with potent antitumor activity.

Human Hippo signaling pathway is an evolutionarily conserved regulator network that controls organ development and has been implicated in various cancers. Transcriptional enhanced associate domain-4 (TEAD4) is the final nuclear effector of Hippo pathway, which is activated by Yes-associated protein (YAP) through binding to two separated YAP regions of α1-helix and Ω-loop. Previous efforts have all been addressed on deriving peptide inhibitors from the YAP to target TEAD4. Instead, we herein attempted to rationally design a so-called 'YAP helixα1-trap' based on the TEAD4 to target YAP by using dynamics simulation and energetics analysis as well as experimental assays at molecular and cellular levels. The trap represents a native double-stranded helical hairpin covering a specific YAP-binding site on TEAD4 surface, which is expected to form a three-helix bundle with the α1-helical region of YAP, thus competitively disrupting TEAD4-YAP interaction. The hairpin was further stapled by a disulfide bridge across its two helical arms. Circular dichroism characterized that the stapling can effectively constrain the trap into a native-like structured conformation in free state, thus largely minimizing the entropy penalty upon its binding to YAP. Affinity assays revealed that the stapling can considerably improve the trap binding potency to YAP α1-helix by up to 8.5-fold at molecular level, which also exhibited a good tumor-suppressing effect at cellular level if fused with TAT cell permeation sequence. In this respect, it is considered that the YAP helixα1-trap-mediated blockade of Hippo pathway may be a new and promising therapeutic strategy against cancers.

Predicting protein conformational motions using energetic frustration analysis and AlphaFold2

Proteins perform their biological functions through motion. Although high throughput prediction of the three-dimensional static structures of proteins has proved feasible using deep-learning-based methods, predicting the conformational motions remains a challenge. Purely data-driven machine learning methods encounter difficulty for addressing such motions because available laboratory data on conformational motions are still limited. In this work, we develop a method for generating protein allosteric motions by integrating physical energy landscape information into deep-learning-based methods. We show that local energetic frustration, which represents a quantification of the local features of the energy landscape governing protein allosteric dynamics, can be utilized to empower AlphaFold2 (AF2) to predict protein conformational motions. Starting from ground state static structures, this integrative method generates alternative structures as well as pathways of protein conformational motions, using a progressive enhancement of the energetic frustration features in the input multiple sequence alignment sequences. For a model protein adenylate kinase, we show that the generated conformational motions are consistent with available experimental and molecular dynamics simulation data. Applying the method to another two proteins KaiB and ribose-binding protein, which involve large-amplitude conformational changes, can also successfully generate the alternative conformations. We also show how to extract overall features of the AF2 energy landscape topography, which has been considered by many to be black box. Incorporating physical knowledge into deep-learning-based structure prediction algorithms provides a useful strategy to address the challenges of dynamic structure prediction of allosteric proteins.

Decoding the decline: unveiling drivers of sarcopenia.

There remains a critical need to define molecular pathways underlying sarcopenia to identify putative therapeutic targets. Research in the mechanisms of aging and sarcopenia relies heavily on preclinical rodent models. In this issue of the JCI, Kerr et al. implemented a clinically-relevant sarcopenia classification system of aged C57BL/6J mice, capturing sarcopenia prevalence across both sexes. The authors performed detailed physiological, molecular, and energetic analyses and demonstrated that mitochondrial biogenesis, oxidative capacity, and AMPK-autophagy signaling decreased as sarcopenia progressed in male mice. Sarcopenia was less prevalent in female mice with fewer alterations compared with the male-affected processes. The findings highlight factors beyond age as necessary for classifying the sarcopenic phenotype in rodent models, reveal sexual dimorphism across the trajectory of age-related declines in muscle mass and function in a commonly used rodent model, and provide insight into sex-dependent molecular alterations associated with sarcopenia progression.