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.

Polymyxin B1 in the Escherichia coli inner membrane: A complex story of protein and lipopolysaccharide-mediated insertion.

The rise in multi-drug resistant Gram-negative bacterial infections has led to an increased need for "last-resort" antibiotics such as polymyxins. However, the emergence of polymyxin-resistant strains threatens to bring about a post-antibiotic era. Thus, there is a need to develop new polymyxin-based antibiotics, but a lack of knowledge of the mechanism of action of polymyxins hinders such efforts. It has recently been suggested that polymyxins induce cell lysis of the Gram-negative bacterial inner membrane (IM) by targeting trace amounts of lipopolysaccharide (LPS) localized there. We use multiscale molecular dynamics (MD), including long-timescale coarse-grained (CG) and all-atom (AA) simulations, to investigate the interactions of polymyxin B1 (PMB1) with bacterial IM models containing phospholipids (PLs), small quantities of LPS, and IM proteins. LPS was observed to (transiently) phase separate from PLs at multiple LPS concentrations, and associate with proteins in the IM. PMB1 spontaneously inserted into the IM and localized at the LPS-PL interface, where it cross-linked lipid headgroups via hydrogen bonds, sampling a wide range of interfacial environments. In the presence of membrane proteins, a small number of PMB1 molecules formed interactions with them, in a manner that was modulated by local LPS molecules. Electroporation-driven translocation of PMB1 via water-filled pores was favored at the protein-PL interface, supporting the 'destabilizing' role proteins may have within the IM. Overall, this in-depth characterization of PMB1 modes of interaction reveals how small amounts of mislocalized LPS may play a role in pre-lytic targeting and provides insights that may facilitate rational improvement of polymyxin-based antibiotics.

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.

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.

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.

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.

Impact of N-Terminal Domain Conformation and Domain Interactions on RfaH Fold Switching.

RfaH is a two-domain metamorphic protein involved in transcription regulation and translation initiation. To carry out its dual functions, RfaH relies on two coupled structural changes: Domain dissociation and fold switching. In the free state, the C-terminal domain (CTD) of RfaH adopts an all-α fold and is tightly associated with the N-terminal domain (NTD). Upon binding to RNA polymerase (RNAP), the domains dissociate and the CTD transforms into an all-ß fold while the NTD remains largely, but not entirely, unchanged. We test the idea that a change in the conformation of an extended ß-hairpin (ß3-ß4) located on the NTD, helps trigger domain dissociation. To this end, we use homology modeling to construct a structure, H1, which is similar to free RfaH but with a remodeled ß3-ß4 hairpin. We then use an all-atom physics-based model enhanced with a dual basin structure-based potential to simulate domain separation driven by the thermal unfolding of the CTD with NTD in a fixed, folded conformation. We apply our model to both free RfaH and H1. For H1 we find, in line with our hypothesis, that the CTD exhibits lower stability and the domains dissociate at a lower temperature T, as compared to free RfaH. We do not, however, observe complete refolding to the all-ß state in these simulations, suggesting that a change in ß3-ß4 orientation aids in, but is not sufficient for, domain dissociation. In addition, we study the reverse fold switch in which RfaH returns from a domain-open all-ß state to its domain-closed all-α state. We observe a T-dependent transition rate; fold switching is slow at low T, where the CTD tends to be kinetically trapped in its all-ß state, and at high-T, where the all-α state becomes unstable. Consequently, our simulations suggest an optimal T at which fold switching is most rapid. At this T, the stabilities of both folds are reduced. Overall, our study suggests that both inter-domain interactions and conformational changes within NTD may be important for the proper functioning of RfaH.

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.

Unraveling the molecular basis for effective regulation of integrin α5ß1 for enhanced therapeutic interventions.

Cell attachment to the extracellular matrix significantly impacts the integrity of tissues and human health. The integrin α5ß1 is a heterodimer of α5 and ß1 subunits and has been identified as a crucial modulator in several human carcinomas. Integrin α5ß1 significantly regulates cell proliferation, angiogenesis, inflammation, tumor metastasis, and invasion. This regulatory role of integrin α5ß1 in tumor metastasis makes it an appealing target for cancer therapy. The majority of the drugs targeting integrin α5ß1 are limited only to clinical trials. In our study, we have performed 94287 compounds screening to determine potential drugs against α5ß1 integrin. We have used ATN-161 as a reference and employed combined bioinformatic methodologies, including molecular modelling, virtual screening, MM-GBSA, cell-line cytotoxicity prediction, ADMET, Density Functional Theory (DFT), Non-covalent Interactions (NCI) and molecular simulation, to identify putative integrin α5ß1 inhibitors. We found Taxifolin, PD133053, and Acebutolol that possess inhibitory activity against α5ß1 integrin and could act as effective drug for the cancer treatment. Taxifolin, PD133053, and Acebutolol exhibited excellent binding to the druggable pocket of integrin α5ß1, and also maintained a unique binding mechanism with extra hydrophobic contacts at molecular level. Overall, our study gives new pharmacological candidates that may act as a potential drug against integrin α5ß1.

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.

A study on loading multiple epitopes with a single peptide.

Epitopes, the basic functional units of antigens, hold great significance in the field of immunology. However, the structure and composition of epitopes and their interactions with antibodies remain unclear, which limits in-depth studies on epitopes and the development of subunit vaccines. In a previous study on the localization of anti-influenza HA monoclonal antibodies (mAbs), three strains with different characteristics reacted with the same peptide. In this study, by conventional immunological assays, computer homology modeling, and molecular docking simulations, we found that (1) the peptide could bind to three strains of mAbs with different reaction characteristics utilizing different combinations of immunodominant groups. (2) By computer molecular docking and simulation methods, the immunodominant groups on the two peptides could be combined into a multi-epitope peptide bound to six strains of mAbs. We established a method for multi-epitope peptide recombination from these immunodominant groups. (3) The immune effect of the recombinant multi-epitope peptide was better than that of a single peptide. Our findings facilitate the understanding of the composition of antigen epitopes and provide a theoretical and experimental basis for developing polyvalent vaccines and understanding immune responses at the molecular level.

Assessing Solid Catalysts with Ionic Liquid Layers (SCILL) from Molecular Dynamics Simulations: On the Role of Local Charge Polarization.

Recent developments in molecular mechanics modelling of metal catalyst surfaces with interfaces to complex ad-layers or bulk liquids enable the study of 10 nm scale systems by molecular dynamics simulations of up to microseconds. Therein, electronic polarization as otherwise benchmarked by quantum calculations is mimicked via atom-centered partial charges that are adjusted dynamically to account for changes in local environment. Apart from thermal fluctuations, this encompasses molecule association and dissociation processes as well as externally applied voltage. Here, we elaborate the concept of employing the charge equilibration method to the molecular dynamics simulation of solid catalysts, namely metal surfaces and substrate-supported metal nanoparticles. This showcases the association of reactants and their interplay with local charge polarization upon co-adsorption of ionic liquids or application of external voltage - thus paving the way to understanding complex interfaces in (electro-)catalysis from molecular dynamics simulation.

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.