Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes.

Nanoelectrochemical devices have become a promising candidate technology across various applications, including sensing and energy storage, and provide new platforms for studying fundamental properties of electrode/electrolyte interfaces. In this work, we employ constant-potential molecular dynamics simulations to investigate the impedance of gold-aqueous electrolyte nanocapacitors, exploiting a recently introduced fluctuation-dissipation relation. In particular, we relate the frequency-dependent impedance of these nanocapacitors to the complex conductivity of the bulk electrolyte in different regimes, and use this connection to design simple but accurate equivalent circuit models. We show that the electrode/electrolyte interfacial contribution is essentially capacitive and that the electrolyte response is bulk-like even when the interelectrode distance is only a few nanometers, provided that the latter is sufficiently large compared to the Debye screening length. We extensively compare our simulation results with spectroscopy experiments and predictions from analytical theories. In contrast to experiments, direct access in simulations to the ionic and solvent contributions to the polarization allows us to highlight their significant and persistent anticorrelation and to investigate the microscopic origin of the timescales observed in the impedance spectrum. This work opens avenues for the molecular interpretation of impedance measurements, and offers valuable contributions for future developments of accurate coarse-grained representations of confined electrolytes.

Dynamical Reweighting for Biased Rare Event Simulations.

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

RevGraphVAMP: A protein molecular simulation analysis model combining graph convolutional neural networks and physical constraints.

Molecular dynamics simulation is a crucial research domain within the life sciences, focusing on comprehending the mechanisms of biomolecular interactions at atomic scales. Protein simulation, as a critical subfield, often utilizes MD for implementation, with trajectory data play a pivotal role in drug discovery. The advancement of high-performance computing and deep learning technology becomes popular and critical to predict protein properties from vast trajectory data, posing challenges regarding data features extraction from the complicated simulation data and dimensionality reduction. Simultaneously, it is essential to provide a meaningful explanation of the biological mechanism behind dimensionality. To tackle this challenge, we propose a new unsupervised model named RevGraphVAMP to intelligently analyze the simulation trajectory. This model is based on the variational approach for Markov processes (VAMP) and integrates graph convolutional neural networks and physical constraint optimization to enhance the learning performance. Additionally, we introduce attention mechanism to assess the importance of key interaction region, facilitating the interpretation of molecular mechanism. In comparison to other VAMPNets models, our model showcases competitive performance, improved accuracy in state transition prediction, as demonstrated through its application to two public datasets and the Shank3-Rap1 complex, which is associated with autism spectrum disorder. Moreover, it enhanced dimensionality reduction discrimination across different substates and provides interpretable results for protein structural characterization.

Many-body effects in the X-ray absorption spectra of liquid water.

SignificanceIn X-ray absorption spectroscopy, an electron-hole excitation probes the local atomic environment. The interpretation of the spectra requires challenging theoretical calculations, particularly in a system like liquid water, where quantum many-body effects and molecular disorder play an important role. Recent advances in theory and simulation make possible new calculations that are in good agreement with experiment, without recourse to commonly adopted approximations. Based on these calculations, the three features observed in the experimental spectra are unambiguously attributed to excitonic effects with different characteristic correlation lengths, which are distinctively affected by perturbations of the underlying H-bond structure induced by temperature changes and/or by isotopic substitution. The emerging picture of the water structure is fully consistent with the conventional tetrahedral model.

Direct free energy evaluation of classical and quantum many-body systems via field-theoretic simulation.

Free energy evaluation in molecular simulations of both classical and quantum systems is computationally intensive and requires sophisticated algorithms. This is because free energy depends on the volume of accessible phase space, a quantity that is inextricably linked to the integration measure in a coordinate representation of a many-body problem. In contrast, the same problem expressed as a field theory (auxiliary field or coherent states) isolates the particle number as a simple parameter in the Hamiltonian or action functional and enables the identification of a chemical potential field operator. We show that this feature leads a "direct" method of free energy evaluation, in which a particle model is converted to a field theory and appropriate field operators are averaged using a field-theoretic simulation conducted with complex Langevin sampling. These averages provide an immediate estimate of the Helmholtz free energy in the canonical ensemble and the entropy in the microcanonical ensemble. The method is illustrated for a classical polymer solution, a block copolymer melt exhibiting liquid crystalline and solid mesophases, and a quantum fluid of interacting bosons.

Nonisothermal nucleation in the gas phase is driven by cool subcritical clusters.

Nucleation of clusters from the gas phase is a widely encountered phenomenon, yet rather little is understood about the underlying out-of-equilibrium dynamics of this process. The classical view of nucleation assumes isothermal conditions where the nucleating clusters are in thermal equilibrium with their surroundings. However, in all first-order phase transitions, latent heat is released, potentially heating the clusters and suppressing the nucleation. The question of how the released energy affects cluster temperatures during nucleation as well as the growth rate remains controversial. To investigate the nonisothermal dynamics and energetics of homogeneous nucleation, we have performed molecular dynamics simulations of a supersaturated vapor in the presence of thermalizing carrier gas. The results obtained from these simulations are compared against kinetic modeling of isothermal nucleation and classical nonisothermal theory. For the studied systems, we find that nucleation rates are suppressed by two orders of magnitude at most, despite substantial release of latent heat. Our analyses further reveal that while the temperatures of the entire cluster size populations are elevated, the temperatures of the specific clusters driving the nucleation flux evolve from cold to hot when growing from subcritical to supercritical sizes and resolve the apparent contradictions regarding cluster temperatures. Our findings provide unprecedented insight into realistic nucleation events and allow us to directly assess earlier theoretical considerations of nonisothermal nucleation.

Repurposing FDA-approved drugs to target malaria through inhibition of dihydrofolate reductase in the folate biosynthesis pathway: A prospective approach.

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme that regulates the biosynthesis of tetrahydrofolate among various species of Plasmodium parasite. It is a validated target of the antifolate drug pyrimethamine (Pyr) in Plasmodium falciparum (Pf), but its clinical efficacy has been hampered due to the emergence of drug resistance. This has made the attempt to screen Food & Drug Administration-approved drugs against wild- and mutant PfDHFR by employing an in-silico pipeline to identify potent candidates. The current study has followed a virtual screening approach for identifying potential DHFR inhibitors from DrugBank database, based on a structure similarity search of candidates, followed by absorption, distribution, metabolism, and excretion estimation. The screened drugs were subjected to various parameters like docking, molecular mechanics with generalized born and surface area solvation calculations, and molecular simulations. We have thus identified two potential drug candidates, duloxetine and guanethidine, which can be repurposed to be tested for their efficacy against wild type and drug resistant falciparum malaria.

Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning.

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

Enhanced Interfacial Electron Transfer in Photocatalyst-Natural Enzyme Coupled Artificial Photosynthesis System: Tuning Strategies and Molecular Simulations.

Laccase is capable of catalyzing a vast array of reactions, but its low redox potential limits its potential applications. The use of photocatalytic materials offers a solution to this problem by converting absorbed visible light into electrons to facilitate enzyme catalysis. Herein, MIL-53(Fe) and NH2-MIL-53(Fe) serve as both light absorbers and enzyme immobilization carriers, and laccase is employed for solar-driven chemical conversion. Electron spin resonance spectroscopy results confirm that visible light irradiation causes rapid transfer of photogenerated electrons from MOF excitation to T1 Cu(II) of laccase, significantly increasing the degradation rate constant of tetracycline (TC) from 0.0062 to 0.0127 min-1. Conversely, there is only minimal or no electron transfer between MOF and laccase in the physical mixture state. Theoretical calculations demonstrate that the immobilization of laccase's active site and its covalent binding to the metal-organic framework surface augment the coupled system's activity, reducing the active site accessible from 27.8 to 18.1 Å. The constructed photo-enzyme coupled system successfully combines enzyme catalysis' selectivity with photocatalysis's high reactivity, providing a promising solution for solar energy use.

Electrostatic Repulsion Facilitated Ion Transport in Covalent-Organic Framework Membranes.

Covalent-organic framework (COF) membranes are increasingly used for many potential applications including ion separation, fuel cells, and ion batteries. It is of central importance to fundamentally and quantitatively understand ion transport in COF membranes. In this study, a series of COF membranes is designed with different densities and arrangements of functional groups and subsequently utilize molecular simulation to provide microscopic insights into ion transport in these membranes. The membrane with a single-sided layer exhibits the highest chloride ion (Cl-) conductivity of 77.2 mS cm-1 at 30 °C. Replacing the single-sided layer with a double-sided layer or changing layer arrangement leads to a decrease in Cl- conductivity up to 33% or 53%, respectively. It is revealed that the electrostatic repulsion between ions serves as a driving force to facilitate ion transport and the positions of functional groups determine the direction of electrostatic repulsion. Furthermore, the ordered pores generate concentrated ions and allow rapid ion transport. This study offers bottom-up inspiration on the design of new COF membranes with moderate density and proper arrangement of functional groups to achieve high ion conductivity.

Cross-reaction mediated by distinct key amino acid combinations in the complementary-determining region (CDR) of a monoclonal antibody.

In immunology, cross-reaction between antigens and antibodies are commonly observed. Prior research has shown that various monoclonal antibodies (mAbs) can recognize a broad spectrum of epitopes related to influenza viruses. However, existing theories on cross-reactions fall short in explaining the phenomena observed. This study explored the interaction characteristics of H1-74 mAb with three peptides: two natural peptides, LVLWGIHHP and LPFQNI, derived from the hemagglutinin (HA) antigen of the H1N1 influenza virus, and one synthetic peptide, WPFQNY. Our findings indicate that the complementarity-determining region (CDR) of H1-74 mAb comprised five antigen-binding sites, containing eight key amino acid residues from the light chain variable region and 16 from the heavy chain variable region. These critical residues formed distinct hydrophobic or hydrophilic clusters and functional groups within the binding sites, facilitating interaction with antigen epitopes through hydrogen bonding, salt bridge formation, and π-π stacking. The study revealed that the formation of the antibody molecule led to the creation of binding groups and small units in the CDR, allowing the antibody to attach to a variety of antigen epitopes through diverse combinations of these small units and functional groups. This unique ability of the antibody to bind with antigen epitopes provides a new molecular basis for explaining the phenomenon of antibody cross-reaction.

Efficient Assessment of 'Instantaneous pK' Values from Molecular Dynamics Simulations.

We present a molecular simulation approach to studying the role of local and momentary molecular environment for potential acid-base reactions. For this, we combine thermodynamic considerations on the pK of ionic species with rapid sampling of energy changes related to (de)protonation. Using dispersed carbonate ions in water as a reference, our approach aims at the fast assessment of the momentary protonation energy, and thus the 'instantaneous pK', of calcium-carbonate ion aggregates. The latter include transient complexes that are elusive to long sampling runs. This motivated the elaboration of approximate, yet particularly fast assessable sampling strategies. Along this line, we were able to characterize instantaneous pK values at a statistical accuracy of 0.4 pK units within sampling runs of only 10 ps duration, whereas statistical errors reduce to 0.1 pK units in 75 ps sampling runs, respectively. This readily enabled the required time resolution for the characterization of [Cax (CO3 )y ]2(x-y) aggregates with x=1,2 and y=1,2,3, respectively. In turn, the analysis of the pH-dependent nature of calcite-water interfaces and dynamically ordered liquid-like oxyanion polymers (dollop) domains is outlined at 10 ps resolution.

Discovery of 3-oxo-1,2,3,4-tetrahydropyrido[1,2-a]pyrazin derivatives as SARS-CoV-2 main protease inhibitors through virtual screening and biological evaluation.

The COVID-19 caused by SARS-CoV-2 has led to a global pandemic that continues to impact societies and economies worldwide. The main protease (Mpro) plays a crucial role in SARS-CoV-2 replication and is an attractive target for anti-SARS-CoV-2 drug discovery. Herein, we report a series of 3-oxo-1,2,3,4-tetrahydropyrido[1,2-a]pyrazin derivatives as non-peptidomimetic inhibitors targeting SARS-CoV-2 Mpro through structure-based virtual screening and biological evaluation. Further similarity search and structure-activity relationship study led to the identification of compound M56-S2 with the enzymatic IC50 value of 4.0 µM. Moreover, the molecular simulation and predicted ADMET properties, indicated that non-peptidomimetic inhibitor M56-S2 might serve as a useful starting point for the further discovery of highly potent inhibitors targeting SARS-CoV-2 Mpro.

Design and synthesis 1H-Pyrrolo[2,3-b]pyridine derivatives as FLT3 inhibitors for the treatment of Acute myeloid Leukemia.

Acute myeloid leukemia (AML) is the most common type of blood cancer and has been strongly correlated with the overexpression of Fms-like tyrosine kinase 3 (FLT3), a member of the class III receptor tyrosine kinase family. With the emergence of FLT3 internal tandem duplication alteration (ITD) and tyrosine kinase domain (TKD) mutations, the development of FLT3 small molecule inhibitors has become an effective medicinal chemistry strategy for AML. Herein, we have designed and synthesized two series of 1H-pyrrolo[2,3-b]pyridine derivatives CM1-CM24, as FLT3 inhibitors based on F14, which we previously reported, that can target the hydrophobic FLT3 back pocket. Among these derivates, CM5 showed significant inhibition of FLT3 and FLT3-ITD, with inhibitory percentages of 57.72 % and 53.77 % respectively at the concentration of 1 µΜ. Furthermore, CM5 demonstrated potent inhibition against FLT3-dependent human AML cell lines MOLM-13 and MV4-11 (both harboring FLT3-ITD mutant), with IC50 values of 0.75 µM and 0.64 µM respectively. In our cellular mechanistic studies, CM5 also effectively induces apoptosis by arresting cell cycle progression in the G0/G1 phase. In addition, the amide and urea linker function were discussed in detail based on computational simulations studies. CM5 will serve as a novel lead compound for further structural modification and development of FLT3 inhibitors specifically targeting AML with FLT3-ITD mutations.

N-Doping CQDs as an Efficient Fluorescence Probe Based on Dynamic Quenching for Determination of Copper Ions and Alcohol Sensing in Baijiu.

To address an accurate detection of heavy metal ions in Baijiu production, a nitrogen-doping carbon quantum dots (N-CQDs) was prepared by hydrothermal method from citric acid and urea. The as-prepared N-CQDs had an average particle size of 2.74 nm, and a large number of functional groups (amino, carbonyl group, etc.) attached on its surface, which obtained a 9.6% of quantum yield (QY) with relatively high and stable fluorescence performance. As a fluorescent sensor, the fluorescence of N-CQDs at 380 nm excitation wavelength could be quenched quantitatively by adding Cu2+, due to the dynamic quenching of electron transfer caused by the binding of amine groups and Cu2+, which showed excellent sensitivity and selectivity to Cu2+ in the range of 0.5-5 µM with a detection limit (LOD) of 0.032 µM. In addition, the N-CQDs as well as could be applied to quantitative determine alcohol content in the range of 10-80 V/V% depending on the fluorescence enhancement. Upon the experiment, the fluorescent mechanism was studied by Molecular dynamics (MD) simulations, which demonstrated that solvent effect played an influential role on sensing alcohol content in Baijiu. Overall, the work provided a theoretically guide for the design of fluorescence sensors to monitor heavy metal ion in liquid drinks and sense alcohol content.

Amino acids-based deep eutectic solvents as additives for improved enantioseparation in capillary electrophoresis.

In this study, several amino acids deep eutectic solvents were prepared using L-valine and L-leucine as hydrogen bond acceptors, and L-lactic acid and glycerol as hydrogen bond donors. These amino acids' deep eutectic solvents were first used as buffer additives to construct several synergistic systems along with maltodextrin in capillary electrophoresis for the enantioseparations of four racemic drugs. Compared with single maltodextrin system, the separations of model drugs in the synergistic systems were significantly improved. Some key parameters affecting chiral separation such as maltodextrin concentration, deep eutectic solvent concentration, buffer pH, and applied voltage were optimized. In order to further understand the specific mechanism of the amino acids deep eutectic solvents in improving chiral separation, we first calculated the binding constants of maltodextrin with enantiomers using the capillary electrophoresis method in the two separation modes, respectively. We also used molecular simulation to calculate the binding free energy of maltodextrin with enantiomers. It is the first time that amino acids deep eutectic solvents were used for enantioseparation in capillary electrophoresis, which will greatly promote the development of deep eutectic solvents in the field of chiral separation.

Molecular simulation on the interaction between trehalose and asymmetric lipid bilayer mimicking the membrane of human red blood cells.

Trehalose is widely acknowledged for its ability to stabilize plasma membranes during dehydration. However, the exact mechanism by which trehalose interacts with lipid bilayers remains presently unclear. In this study, we conducted atomistic molecular dynamic simulations on asymmetric model bilayers that mimic the membrane of human red blood cells at various trehalose and water contents. We considered three different hydration levels mimicking the full hydration to desiccation scenarios. Results indicate that the asymmetric distribution of lipids did not significantly influence the computed structural characteristics at full and low hydration. At dehydration, however, the order parameter obtained from the symmetric bilayer is significantly higher compared to those obtained from asymmetric ones. Analysis of hydrogen bonds revealed that the protective ability of trehalose is well described by the water replacement hypothesis at full and low hydration, while at dehydration other interaction mechanisms associated with trehalose exclusion from the bilayer may involve. In addition, we found that trehalose exclusion is not attributed to sugar saturation but rather to the reduction in hydration levels. It can be concluded that the protective effect of trehalose is not only related to the hydration level of the bilayer, but also closely tied to the asymmetric distribution of lipids within each leaflet.

Riboflavin-targeted polymers improve tolerance of paclitaxel while maintaining therapeutic efficacy.

Active targeting can enhance precision and efficacy of drug delivery systems (DDS) against cancers. Riboflavin (RF) is a promising ligand for active targeting due to its biocompatibility and high riboflavin-receptor expression in cancers. In this study, RF-targeted 4-arm polyethylene glycol (PEG) stars conjugated with Paclitaxel (PTX), named PEG PTX RF, were evaluated as a targeted DDS. In vitro, PEG PTX RF exhibited higher toxicity against tumor cells compared to the non-targeted counterpart (PEG PTX), while free PTX displayed the highest acute toxicity. In vivo, all treatments were similarly effective, but PEG PTX RF-treated tumors showed fewer proliferating cells, pointing to sustained therapy effects. Moreover, PTX-treated animals' body and liver weights were significantly reduced, whereas both remained stable in PEG PTX and PEG PTX RF-treated animals. Overall, our targeted and non-targeted DDS reduced PTX's adverse effects, with RF targeting promoted drug uptake in cancer cells for sustained therapeutic effect.

Affinity of small-molecule solutes to hydrophobic, hydrophilic, and chemically patterned interfaces in aqueous solution.

Performance of membranes for water purification is highly influenced by the interactions of solvated species with membrane surfaces, including surface adsorption of solutes upon fouling. Current efforts toward fouling-resistant membranes often pursue surface hydrophilization, frequently motivated by macroscopic measures of hydrophilicity, because hydrophobicity is thought to increase solute-surface affinity. While this heuristic has driven diverse membrane functionalization strategies, here we build on advances in the theory of hydrophobicity to critically examine the relevance of macroscopic characterizations of solute-surface affinity. Specifically, we use molecular simulations to quantify the affinities to model hydroxyl- and methyl-functionalized surfaces of small, chemically diverse, charge-neutral solutes represented in produced water. We show that surface affinities correlate poorly with two conventional measures of solute hydrophobicity, gas-phase water solubility and oil-water partitioning. Moreover, we find that all solutes show attraction to the hydrophobic surface and most to the hydrophilic one, in contrast to macroscopically based hydrophobicity heuristics. We explain these results by decomposing affinities into direct solute interaction energies (which dominate on hydroxyl surfaces) and water restructuring penalties (which dominate on methyl surfaces). Finally, we use an inverse design algorithm to show how heterogeneous surfaces, with multiple functional groups, can be patterned to manipulate solute affinity and selectivity. These findings, importantly based on a range of solute and surface chemistries, illustrate that conventional macroscopic hydrophobicity metrics can fail to predict solute-surface affinity, and that molecular-scale surface chemical patterning significantly influences affinity-suggesting design opportunities for water purification membranes and other engineered interfaces involving aqueous solute-surface interactions.

Diffusion of a disordered protein on its folded ligand.

Intrinsically disordered proteins often form dynamic complexes with their ligands. Yet, the speed and amplitude of these motions are hidden in classical binding kinetics. Here, we directly measure the dynamics in an exceptionally mobile, high-affinity complex. We show that the disordered tail of the cell adhesion protein E-cadherin dynamically samples a large surface area of the protooncogene ß-catenin. Single-molecule experiments and molecular simulations resolve these motions with high resolution in space and time. Contacts break and form within hundreds of microseconds without a dissociation of the complex. The energy landscape of this complex is rugged with many small barriers (3 to 4 kBT) and reconciles specificity, high affinity, and extreme disorder. A few persistent contacts provide specificity, whereas unspecific interactions boost affinity.