The 50 most-cited articles in The Journal of Physical Chemistry B, 2023

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.

By averaging over atomic details, coarse-grained (CG) models provide profound computational and conceptual advantages for studying soft materials. In particular, bottom-up approaches develop CG models based upon information obtained from atomically detailed models. At least in principle, a bottom-up model can reproduce all the properties of an atomically detailed model that are observable at the resolution of the CG model. Historically, bottom-up approaches have accurately modeled the structure of liquids, polymers, and other amorphous soft materials, but have provided lower structural fidelity for more complex biomolecular systems. Moreover, they have also been plagued by unpredictable transferability and a poor description of thermodynamic properties. Fortunately, recent studies have reported dramatic advances in addressing these prior limitations. This Perspective reviews this remarkable progress, while focusing on its foundation in the basic theory of coarse-graining. In particular, we describe recent insights and advances for treating the CG mapping, for modeling many-body…

High Resolution Image Download MS PowerPoint Slide D 2 O is commonly used as a solvent instead of H 2 O in spectroscopic studies of proteins, in particular, in infrared and nuclear-magnetic-resonance spectroscopy. D 2 O is chemically equivalent to H 2 O, and the differences, particularly in hydrogen-bond strength, are often ignored. However, replacing solvent water with D 2 O can affect not only the kinetics but also the structure and stability of biomolecules. Recent experiments have shown that even the mesoscopic structures and the elastic properties of biomolecular assemblies, such as amyloids and protein networks, can be very different in D 2 O and H 2 O. We discuss these findings, which probably are just the tip of the iceberg, and which seem to call for obtaining a better understanding of the H 2 O/D 2 O-isotope effect on water–water and water–protein interactions. Such improved understanding may change the differences between H 2 O and D 2 O as biomolecular solvents from an elephant in the room to an opportunity for protein research.

The design of novel cancer drug nanocarriers is critical in the framework of cancer therapeutics. Nanomaterials are gaining increased interest as cancer drug delivery systems. Self-assembling peptides constitute an emerging novel class of highly attractive nanomaterials with highly promising applications in drug delivery, as they can be used to facilitate drug release and/or stability while reducing side effects. Here, we provide a perspective on peptide self-assembled nanocarriers for cancer drug delivery and highlight the aspects of metal coordination, structure stabilization, and cyclization, as well as minimalism. We review particular challenges in nanomedicine design criteria and, finally, provide future perspectives on addressing a portion of the challenges via self-assembling peptide systems. We consider that the intrinsic advantages of such systems, along with the increasing progress in computational and experimental approaches for their study and design, could possibly lead to novel classes of single or multicomponent systems incorporating such materials for cancer drug…

The OPLS all-atom force field was updated and applied to modeling unsaturated hydrocarbons, alcohols, and ethers. Testing has included gas-phase conformational energetics, properties of pure liquids, and free energies of hydration. Monte Carlo statistical mechanics (MC) calculations were used to model 60 liquids. In addition, a robust, automated procedure was devised to compute the free energies of hydration with high precision via free-energy perturbation (FEP) calculations using double annihilation. Testing has included larger molecules than in the past, and parameters are reported for the first time for some less common groups including alkynes, allenes, dienes, and acetals. The average errors in comparison with experimental data for the computed properties of the pure liquids were improved with the modified force field (OPLS/2020). For liquid densities and heats of vaporization, the average unsigned errors are 0.01 g/cm 3 and 0.2 kcal/mol. The average error and signed error for free energies of hydration are both 1.2 kcal/mol. As noted before, this reflects a systematic…

Biomolecular condensates are important contributors to the internal organization of the cell material. While initially described as liquid-like droplets, the term biomolecular condensates is now used to describe a diversity of condensed phase assemblies with material properties extending from low to high viscous liquids, gels, and even glasses. Because the material properties of condensates are determined by the intrinsic behavior of their molecules, characterizing such properties is integral to rationalizing the molecular mechanisms that dictate their functions and roles in health and disease. Here, we apply and compare three distinct computational methods to measure the viscoelasticity of biomolecular condensates in molecular simulations. These methods are the Green-Kubo (GK) relation, the oscillatory shear (OS) technique, and the bead tracking (BT) method. We find that, although all of these methods provide consistent results for the viscosity of the condensates, the GK and OS techniques outperform the BT method in terms of computational efficiency and statistical uncertainty. We…

Studies of biological membrane heterogeneity particularly benefit from the use of the environment-sensitive fluorescent probe Laurdan, for which shifts in the emission, produced by any stimulus (e.g., fluidity variations), are ascribed to alterations in hydration near the fluorophore. Ironically, no direct measure of the influence of the membrane hydration level on Laurdan spectra has been available. To address this, we investigated the fluorescence spectrum of Laurdan embedded in solid-supported lipid bilayers as a function of hydration and compared it with the effect of cholesterol─a major membrane fluidity regulator. The effects are illusively similar, and hence the results obtained with this probe should be interpreted with caution. The dominant phenomenon governing the changes in the spectrum is the hindrance of the lipid internal dynamics. Furthermore, we unveiled the intriguing mechanism of dehydration-induced redistribution of cholesterol between domains in the phase-separated membrane, which reflects yet another regulatory function of cholesterol.

The "bottom-up" approach to coarse-graining, for building accurate and efficient computational models to simulate large-scale and complex phenomena and processes, is an important approach in computational chemistry, biophysics, and materials science. As one example, the Multiscale Coarse-Graining (MS-CG) approach to developing CG models can be rigorously derived using statistical mechanics applied to fine-grained, i.e., all-atom simulation data for a given system. Under a number of circumstances, a systematic procedure, such as MS-CG modeling, is particularly valuable. Here, we present the development of the OpenMSCG software, a modularized open-source software that provides a collection of successful and widely applied bottom-up CG methods, including Boltzmann Inversion (BI), Force-Matching (FM), Ultra-Coarse-Graining (UCG), Relative Entropy Minimization (REM), Essential Dynamics Coarse-Graining (EDCG), and Heterogeneous Elastic Network Modeling (HeteroENM). OpenMSCG is a high-performance and comprehensive toolset that can be used to derive CG models from large-scale fine-grained…

Molecular dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively long time scales of these processes. Many enhanced sampling approaches have emerged to tackle this problem, including biased sampling and path-sampling methods. In this Perspective, we focus on adaptive sampling algorithms. These techniques differ from other approaches because the thermodynamic ensemble is preserved and the sampling is enhanced solely by restarting MD trajectories at particularly chosen seeds rather than introducing biasing forces. We begin our treatment with an overview of theoretically transparent methods, where we discuss principles and guidelines for adaptive sampling. Then, we present a brief summary of select methods that have been applied to realistic systems in the past. Finally, we discuss recent advances in adaptive sampling methodology powered by deep learning techniques, as well as their shortcomings.

Abstract Natural gas hydrate, a potential energy resource, is attracting worldwide attention. In this study, we propose a new method of hydrate dissociation which uses seawater and electrostatic fields (SE method) cooperatively. The hydrate molecular dissociation mechanism of gas hydrate is a key issue in studying the kinetic properties of gas hydrate using the SE method. Therefore, molecular dynamics simulations were used to investigate the thermodynamic properties and structural changes of methane hydrate (MH) in multiple kinds of salt solutions under an electrostatic field. The results show that the electric field can drive cations into the MH phase to form a series of random semiopen cages, which are essentially temporary and metastable. The variation in free energy indicates that it is more difficult for divalent cations to enter the hydrate phase than monovalent cations, meaning that the hydrate structures formed with divalent cations are more unstable. Then, the ion current occurred in the hydrate phase (called ion migration in this study), which greatly accelerated hydrate…

This Perspective presents a review of our work and that of others in the highly controversial topic of the coupling of protein dynamics to reaction in enzymes. We have been involved in studying this topic for many years. Thus, this perspective will naturally present our own views, but it also is designed to present an overview of the variety of viewpoints of this topic, both experimental and theoretical. This is obviously a large and contentious topic.

Abstract Cellular crowding plays a key role in regulating the enzymatic reactivity in physiological conditions, which is challenging to realize in the dilute phase. Enzymes drive a wide range of complex metabolic reactions with high efficiency and selectivity under extremely heterogeneous and crowded cellular environments. However, the molecular interpretation behind the enhanced enzymatic reactivity under a crowded milieu is poorly understood. Herein, using horseradish peroxidase (HRP) and glucose oxidase (GOx) cascade pair, we demonstrate for the first time that macromolecular crowding induces liquid-liquid phase separation (LLPS) via the formation of liquid-like condensates/droplets and thereby increases the intrinsic catalytic efficiencies of HRP and GOx. Both these enzymes undergo crowding induced homotypic LLPS via enthalpically driven multivalent electrostatic as well as hydrophobic interactions. Using a set of kinetic and microscopic experiments, we show that precise synchronization of spontaneous LLPS and enzymatic transformations is key to realize the enhanced enzymatic…

Water is considered integral for the stabilization and function of proteins, which has recently attracted significant attention. However, the microscopic aspects of water ranging up to the second hydration shell, including strongly and weakly bound water at the sub-nanometer scale, are not yet well understood. Here, we combined terahertz spectroscopy, thermal measurements, and infrared spectroscopy to clarify how the strongly and weakly bound hydration water changes upon protein denaturation. With denaturation, that is, the exposure of hydrophobic groups in water and entanglement of hydrophilic groups, the number of strongly bound hydration water decreased, while the number of weakly bound hydration water increased. Even though the constraint of water due to hydrophobic hydration is weak, it extends to the second hydration shell as it is caused by the strengthening of hydrogen bonds between water molecules, which is likely the key microscopic mechanism for the destabilization of the native state due to hydration.

The prediction of thermophysical properties at extreme conditions is an important application of molecular simulations. The quality of these predictions primarily depends on the quality of the employed force field. In this work, a systematic comparison of classical transferable force fields for the prediction of different thermophysical properties of alkanes at extreme conditions, as they are encountered in tribological applications, was carried out using molecular dynamics simulations. Nine transferable force fields from three different classes were considered (all-atom, united-atom, and coarse-grained force fields). Three linear alkanes ( n -decane, n -icosane, and n -triacontane) and two branched alkanes (1-decene trimer and squalane) were studied. Simulations were carried out in a pressure range between 0.1 and 400 MPa at 373.15 K. For each state point, density, viscosity, and self-diffusion coefficient were sampled, and the results were compared to experimental data. The Potoff force field yielded the best results.

High Resolution Image Download MS PowerPoint Slide Lipid nanoparticles (LNPs) containing ionizable aminolipids are among the leading platforms for the successful delivery of nucleic-acid-based therapeutics, including messenger RNA (mRNA). The two recently FDA-approved COVID-19 vaccines developed by Moderna and Pfizer/BioNTech belong to this category. Ionizable aminolipids, cholesterol, and DSPC lipids are among the key components of such formulations, crucially modulating physicochemical properties of these formulations and, consequently, the potency of these therapeutics. Despite the importance of these components, the distribution of these molecules in LNPs containing mRNA is not clear. In this study, we used all-atom molecular dynamics (MD) simulations to investigate the distribution and effects of the Lipid-5 (apparent p K a of the lipid nanoparticle = 6.56), a rationally designed and previously reported ionizable aminolipid by Moderna, on lipid bilayers [ Mol. Ther. 2018, 26, 1509–1519]. The simulations were conducted with half of the aminolipids charged and half neutral…

Purple phototrophic bacteria are ancient anoxygenic phototrophs and attractive research tools because they capture light energy in the near-infrared (NIR) region of the spectrum and transform it into chemical energy by way of uphill energy transfers. The heart of this reaction occurs in light-harvesting 1-reaction center (LH1-RC) complexes, which are the simplest model systems for understanding basic photosynthetic reactions within type-II (quinone-utilizing) reaction centers. In this Perspective, we highlight structure-function relationships concerning unresolved fundamental processes in purple bacterial photosynthesis, including the diversified light-harvesting capacity of LH1-associated BChl molecules, energies necessary for photoelectric conversion in the RC special pairs, and quinone transport mechanisms. Based on recent progress in the spectroscopic and structural analysis of LH1-RC complexes from a variety of purple phototrophs, we discuss several key factors for understanding how purple bacteria resource light energy in the inherently energy-poor NIR region of the…

High Resolution Image Download MS PowerPoint Slide Protein stability is important in many areas of life sciences. Thermal protein unfolding is investigated extensively with various spectroscopic techniques. The extraction of thermodynamic properties from these measurements requires the application of models. Differential scanning calorimetry (DSC) is less common, but is unique as it measures directly a thermodynamic property, that is, the heat capacity C p ( T ). The analysis of C p ( T ) is usually performed with the chemical equilibrium two-state model. This is not necessary and leads to incorrect thermodynamic consequences. Here we demonstrate a straightforward model-independent evaluation of heat capacity experiments in terms of protein unfolding enthalpy Δ H ( T ), entropy Δ S ( T ), and free energy Δ G ( T )). This now allows the comparison of the experimental thermodynamic data with the predictions of different models. We critically examined the standard chemical equilibrium two-state model, which predicts a positive free energy for the native protein, and diverges distinctly…

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

This Perspective article focuses on recent simulation work on the dynamics of aqueous electrolytes. It is well-established that full-charge, nonpolarizable models for water and ions generally predict solution dynamics that are too slow in comparison to experiments. Models with reduced (scaled) charges do better for solution diffusivities and viscosities but encounter issues describing other dynamic phenomena such as nucleation rates of crystals from solution. Polarizable models show promise, especially when appropriately parametrized, but may still miss important physical effects such as charge transfer. First-principles calculations are starting to emerge for these properties that are in principle able to capture polarization, charge transfer, and chemical transformations in solution. While direct ab initio simulations are still too slow for simulations of large systems over long time scales, machine-learning models trained on appropriate first-principles data show significant promise for accurate and transferable modeling of electrolyte solution dynamics.

RNA-based therapies have shown promise in a wide range of applications, from cancer therapy, treatment of inherited diseases to vaccination. Encapsulation of RNA into ionizable lipid (IL) containing lipid nanoparticles (LNPs) has enabled its safe and targeted delivery. We present here the simulations of the self-assembly process of pH-sensitive RNA-carrying LNPs and their internal morphology. At low pH, the simulations confirm a lipid core encapsulating RNA in the hexagonal phase. Our all-atom and coarse-grained simulations show that an RNA molecule inside an LNP is protected from interactions with ions by being enveloped in the charged ILs. At neutral pH, representing the environment after LNP administration into human tissues, LNPs expelled most of the encapsulated RNA and water and formed separate bulk IL-rich and ordered the helper-lipid-rich phase. Helper lipids arranged themselves to be in contact with RNA or water. The presented models provide atomistic understanding of the LNP structure and open a way to investigate them in silico, varying the LNP composition or interacting…

Abstract Interaction strength and localization are critical parameters controlling the single-chain and condensed-state properties of intrinsically disordered proteins (IDPs). Here, we decipher these relationships using coarse-grained heteropolymers comprised of hydrophobic (H) and polar (P) monomers as model IDPs. We systematically vary the fraction of P monomers X P and employ two distinct particle-based models that include either strong localized attractions between only H–H pairs (HP model) or weak distributed attractions between both H–H and H–P pairs (HP+ model). To compare different sequences and models, we first carefully tune the attraction strength for all sequences to match the single-chain radius of gyration. Interestingly, we find that this procedure produces similar conformational ensembles, nonbonded potential energies, and chain-level dynamics for single chains of almost all sequences in both models, with some deviations for the HP model at large X P . However, we observe a surprisingly rich phase behavior for the sequences in both models that deviates from the…

A systematic description of microscopic mechanisms is necessary to understand mass transport in solid and liquid electrolytes. From Molecular Dynamics (MD) simulations, transport properties can be computed and provide a detailed view of the molecular and ionic motions. In this work, ionic conductivity and transport numbers in electrolyte systems are computed from equilibrium and nonequilibrium MD simulations. Results from the two methods are compared with experimental results, and we discuss the significance of the frame of reference when determining and comparing transport numbers. Two ways of computing ionic conductivity from equilibrium simulations are presented: the Nernst-Einstein approximation or the Onsager coefficients. The Onsager coefficients take ionic correlations into account and are found to be more suitable for concentrated electrolytes. Main features and differences between equilibrium and nonequilibrium simulations are discussed, and some potential anomalies and critical pitfalls of using nonequilibrium molecular dynamics to determine transport properties are…

Sorafenib (Sor) is a multitarget kinase inhibitor used clinically to treat hepatocellular carcinoma and renal cancer. In this study, the interaction mechanism of Sor with c-MYC G-quadruplexes (G4) was investigated at the molecular level by computer-aided means and experiments. Molecular docking results predicted the binding of Sor to the groove of G4. Molecular dynamics (MD) simulations were used to evaluate the effect of ligand binding to G4. Ultraviolet (UV), fluorescence spectroscopy, and viscosity experiments showed that the binding site was in the groove. The UV and fluorescence titration results showed that compared with traditional G4 ligands represented by compound meso -tetra ( N -methyl-4-pyridyl) porphine (TmPyP4), Sor has a lower affinity for G4. Likewise, results from fluorescence resonance energy transfer (FRET) experiments suggested that Sor could have a limited ability to stabilize G4, but it was not as prominent as that of TmPyP4. Time-resolved fluorescence spectroscopy again supported the results from steady-state fluorescence spectroscopy, indicating that a static…

Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory Random Coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of…

High Resolution Image Download MS PowerPoint Slide Coherent anti-Stokes Raman scattering (CARS) microscopy is an emerging nonlinear vibrational imaging technique that delivers label-free chemical maps of cells and tissues. In narrowband CARS, two spatiotemporally superimposed picosecond pulses, pump and Stokes, illuminate the sample to interrogate a single vibrational mode. Broadband CARS (BCARS) combines narrowband pump pulses with broadband Stokes pulses to record broad vibrational spectra. Despite recent technological advancements, BCARS microscopes still struggle to image biological samples over the entire Raman-active region (400–3100 cm –1 ). Here, we demonstrate a robust BCARS platform that answers this need. Our system is based on a femtosecond ytterbium laser at a 1035 nm wavelength and a 2 MHz repetition rate, which delivers high-energy pulses used to produce broadband Stokes pulses by white-light continuum generation in a bulk YAG crystal. Combining such pulses, pre-compressed to sub-20 fs duration, with narrowband pump pulses, we generate a CARS signal with a high (<9 cm…

Machine learning (ML) is having an increasing impact on the physical sciences, engineering, and technology and its integration into molecular simulation frameworks holds great potential to expand their scope of applicability to complex materials and facilitate fundamental knowledge and reliable property predictions, contributing to the development of efficient materials design routes. The application of ML in materials informatics in general, and polymer informatics in particular, has led to interesting results, however great untapped potential lies in the integration of ML techniques into the multiscale molecular simulation methods for the study of macromolecular systems, specifically in the context of Coarse Grained (CG) simulations. In this Perspective, we aim at presenting the pioneering recent research efforts in this direction and discussing how these new ML-based techniques can contribute to critical aspects of the development of multiscale molecular simulation methods for bulk complex chemical systems, especially polymers. Prerequisites for the implementation of such…

Cryo-electron microscopy (cryo-EM) has recently become a leading method for obtaining high-resolution structures of biological macromolecules. However, cryo-EM is limited to biomolecular samples with low conformational heterogeneity, where most conformations can be well-sampled at various projection angles. While cryo-EM provides single-molecule data for heterogeneous molecules, most existing reconstruction tools cannot retrieve the ensemble distribution of possible molecular conformations from these data. To overcome these limitations, we build on a previous Bayesian approach and develop an ensemble refinement framework that estimates the ensemble density from a set of cryo-EM particle images by reweighting a prior conformational ensemble, e.g., from molecular dynamics simulations or structure prediction tools. Our work provides a general approach to recovering the equilibrium probability density of the biomolecule directly in conformational space from single-molecule data. To validate the framework, we study the extraction of state populations and free energies for a simple toy…

The underlying recognition mechanisms of alkali metal ions by crown ethers in aqueous solutions are yet to be fully understood at the molecular level. We report direct experimental and theoretical evidence for the structure and recognition sequence of alkali metal ions (Li +, Na +, K +, Rb +, and Cs + ) by 18-crown-6 in aqueous solutions by wide-angle X-ray scattering combined with an empirical potential structure refinement modeling and ab initio molecular dynamics simulation. Li +, Na +, and K + are located in the negative potential cavity of 18-crown-6, with Li + and Na + deviating from the centroid of 18-crown-6 by 0.95 and 0.35 Å, respectively. Rb + and Cs + lie outside the 18-crown-6 ring and deviate from the centroid of 18-crown-6 by 0.05 and 1.35 Å, respectively. The formation of the 18-crown-6/alkali metal ion complexes is dominated by electrostatic attraction between the cations and the oxygen atoms (Oc) of 18-crown-6. Li +, Na +, K +, and Rb + form the H 2 O···18-crown-6/cation···H 2 O “sandwich” hydrates, while water molecules only hydrate with Cs + of the 18-crown-6/Cs…

Ion exchange membranes (IEMs) are frequently used in water treatment and electrochemical applications, with their ion separation properties largely governed by equilibrium ion partitioning between a membrane and contiguous solution. Despite an expansive literature on IEMs, the influence of electrolyte association (i.e., ion pairing) on ion sorption remains relatively unexplored. In this study, salt sorption in two commercial cation exchange membranes equilibrated with 0.01–1.0 M MgSO 4 and Na 2 SO 4 is investigated experimentally and theoretically. Association measurements of salt solutions using conductometric experiments and the Stokes–Einstein approximation show significant concentrations of ion pairs in MgSO 4 and Na 2 SO 4 relative to those in simple electrolytes (i.e., NaCl), which is consistent with prior studies of sulfate salts. The Manning/Donnan model, developed and validated for halide salts in previous studies, substantially underpredicts sulfate sorption measurements, presumably due to ion pairing effects not accounted for in this established theory. These findings…

The structures of equimolar mixtures of the commonly used polar aprotic solvents dimethylformamide (DMF) and dimethylacetamide (DMAc) in dimethyl sulfoxide (DMSO) have been investigated via neutron diffraction augmented by extensive hydrogen/deuterium isotopic substitution. Detailed 3-dimensional structural models of these solutions have been derived from the neutron data via Empirical Potential Structure Refinement (EPSR). The intermolecular center-of-mass (CoM) distributions show that the first coordination shell of the amides comprises ∼13-14 neighbors, of which approximately half are DMSO. In spite of this near ideal coordination shell mixing, the changes to the amide-amide structure are found to be relatively subtle when compared to the pure liquids. Analysis of specific intermolecular atom-atom correlations allows quantitative interpretation of the competition between weak interactions in the solution. We find a hierarchy of formic and methyl C-H···O hydrogen bonds forms the dominant local motifs, with peak positions in the range of 2.5-3.0 Å. We also observe a rich variety of…

Water (H 2 O) is of great societal importance, and there has been a significant amount of research on its fundamental properties and related physical phenomena. Deuterium dioxide (D 2 O), known as heavy water, also draws much interest as an important medium for medical imaging, nuclear reactors, etc. Although many experimental studies on the fundamental properties of H 2 O and D 2 O have been conducted, they have been primarily limited to understanding the differences between H 2 O and D 2 O in the bulk state. In this paper, using path integral molecular dynamics simulations, the structural and dynamical properties of H 2 O and D 2 O in bulk and under nanoscale confinement in a (14,0) carbon nanotube are studied. We find that in bulk, structural properties such as bond angle and bond length of D 2 O are slightly smaller than those of H 2 O while D 2 O is slightly more structured than H 2 O. The dipole moment of D 2 O tends to be 4% higher than that of H 2 O, and the hydrogen bonding of D 2 O is also stronger than that of H 2 O. Under nanoscale confinement in a (14,0) carbon…

Effective, low-cost adsorbents are needed to remove perfluoroalkyl and polyfluoroalkyl substances (PFAS) from water sources. Carbon-based materials are promising PFAS adsorbents. Here, we explore the potential of graphite oxide (GO) and its derivatives as PFAS adsorbents by studying the adsorption of perfluorooctanoic acid (PFOA), a model PFAS molecule, on GO surfaces with O/C ratios up to 16.7% using molecular dynamics simulations. An adsorption free energy of approximately -30 kJ/mol (or -310 meV) is obtained for pristine graphene in pure water, and adsorbed PFOA molecules diffuse rapidly. As the O/C ratio increases, hydrophobic interactions' contribution to PFOA adsorption diminishes, but that by electrostatic interactions becomes important. Overall, adsorption is weakened, but favorable adsorption still occurs at an O/C ratio of 16.7%. The in-plane diffusion coefficient of adsorbed PFOA molecules decreases by more than 45 times as the O/C ratio increases to 8.3% but increases significantly when the O/C ratio increases further to 16.7%. Adding salt improves the adsorption owing…

Amyloid aggregation describes the aberrant self-assembly of peptides into ordered fibrils characterized by cross-β spine cores and is associated with many neurodegenerative diseases and Type 2 diabetes. Oligomers, populated during the early stage of aggregation, are found to be more cytotoxic than mature fibrils. Recently, many amyloidogenic peptides have been reported to undergo liquid-liquid phase separation (LLPS)─a biological process important for the compartmentalization of biomolecules in living cells─prior to fibril formation. Understanding the relationship between LLPS and amyloid aggregation, especially the formation of oligomers, is essential for uncovering disease mechanisms and mitigating amyloid toxicity. In this Perspective, available theories and models of amyloid aggregation and LLPS are first briefly reviewed. By drawing analogies to gas, liquid, and solid phases in thermodynamics, a phase diagram of protein monomer, droplet, and fibril states separated by coexistence lines can be inferred. Due to the high free energy barrier of fibrillization kinetically delaying…

Fluorescence microscopy techniques have been widely adopted in biology for their ability to visualize the structure and dynamics of a wide range of cellular and subcellular processes. The specificity and sensitivity that these techniques afford have made them primary tools in the characterization of protein localizations within cells. Many of the fluorescence microscopy techniques require cells to be fixed via chemical or alternative methods before being imaged. However, some fixation methods have been found to induce the redistribution of particular proteins in the cell, resulting in artifacts in the characterization of protein localizations and functions under physiological conditions. Here, we review the ability of commonly used cell fixation methods to faithfully preserve the localizations of proteins that bind to chromatin, undergo liquid-liquid phase separation (LLPS), and are involved in the formation of various membrane-bound organelles. We also review the mechanisms underlying various fixation artifacts and discuss potential alternative fixation methods to minimize the…

High Resolution Image Download MS PowerPoint Slide Recent claims of the spontaneous H 2 O 2 formation at the air–water interface of water microdroplets have sparked debates on its feasibility. New results from different research groups have provided more insight into these claims, but conclusive proofs are still far from realized. In this Perspective, thermodynamic viewpoints, potential experiments, and theoretical approaches are presented as references for future studies. We suggest that future work should seek for H 2 byproduct as indirect evidence to confirm the feasibility of this phenomenon. Examining potential energy surfaces for H 2 O 2 formation reaction when moving from the bulk to the interface under the influence of the local electric fields is also critical to establish this phenomenon.

The cause of Alzheimer's disease is related to aggregates such as oligomers and amyloid fibrils consisting of amyloid-β (Aβ) peptides. Molecular dynamics (MD) simulation studies have been conducted to understand the molecular mechanism of the formation and disruption of Aβ aggregates. In this Perspective, the MD simulation studies are classified into four categories, focusing on the target systems: aggregation of Aβ peptides in bulk solution, Aβ aggregation at the interface, aggregation inhibitor against Aβ peptides, and nonequilibrium MD simulation of Aβ aggregates. MD simulation studies in these categories are first reviewed. Future perspectives in each category are then presented. Finally, the overall perspective is presented on how MD simulations of Aβ aggregates can be utilized for developing Alzheimer's disease treatment.

Semicrystalline polymer materials are commonly strong yet tough after processed through fiber spinning, film stretching (or blowing), and plastic molding (or foaming), which are fundamentally related with strain-induced crystallization. This paper provides a personal perspective on thermodynamics and kinetics aspects of strain-induced polymer crystallization, mainly based on the author's recent research experience. The thermodynamic studies include homopolymers, random copolymers, solution polymers, and blend polymers. The kinetic studies cover three sequential crystallization stages, i.e., crystal nucleation, crystal growth, and postgrowth. The thermodynamic driving forces join with the kinetic barriers to determine the crystal nucleation mechanisms and the structure evolution at the molecular level, which yield unique polymer crystal morphologies from lamellar crystals to shish-kebab crystals and eventually fibril crystals. The resulting semicrystalline structures were discussed with their implications for the mechanical properties of products. Some future studies were briefly…

Ionic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship between the IL structure and properties has been the subject of many research studies. Recently, special attention has been paid to machine learning tools, especially multilayer perceptron and convolutional neural networks, among many other algorithms in the field of artificial neural networks. For the latter, graph neural networks (GNNs) seem to be a powerful cheminformatic tool yet not well enough studied for dual molecular systems such as ILs. In this work, the usage of GNNs in structure-property studies is critically evaluated for predicting the density, viscosity, and surface tension of ILs. The problem of data availability and integrity is discussed to…

Machine learning has recently entered into the mainstream of coarse-grained (CG) molecular modeling and simulation. While a variety of methods for incorporating deep learning into these models exist, many of them involve training neural networks to act directly as the CG force field. This has several benefits of which the most significant is accuracy. Neural networks can inherently incorporate multibody effects during the calculation of CG forces, and a well-trained neural network force field outperforms pairwise basis sets generated from essentially any methodology. However, this comes at a significant cost. First, these models are typically slower than pairwise force fields, even when accounting for specialized hardware, which accelerates the training and integration of such networks. The second and the focus of this paper is the need for a considerable amount of data to train such force fields. It is common to use 10s of microseconds of molecular dynamics data to train a single CG model, which approaches the point of eliminating the CG model's usefulness in the first place. As we…

High Resolution Image Download MS PowerPoint Slide Ionic liquid viscosity is one of the most important properties to consider for practical applications. Yet, the connection between local structure and viscosity remains an open question. This article explores the structural origin of differences in the viscosity and viscoelastic relaxation across several ionic liquids, including cations with alkyl, ether, and thioether tails, of the imidazolium and pyrrolidinium families coupled with the NTf 2 – anion. In all cases, for the systems studied here, we find that pyrrolidinium-based ions are “harder” than their imidazolium-based counterparts. We make a connection between the chemical concept of hardness vs softness and specific structural and structural dynamic quantities that can be derived from scattering experiments and simulations.

In this study, the effect of non-covalent interaction in the tapinarof-EtOH systems is evaluated, particularly the hydrogen-bonding interaction using density functional theory in a gas phase. From the optimization results and the binding energy calculated thereafter, it is concluded that interaction in the employed system occurs between the O-H groups on tapinarof and the oxygen atom of EtOH molecules existing in the vicinity of the O-H group. These interactions were concluded to be those of the weak hydrogen bonds by carrying out the reduced gradient approach and QTAIM analysis, which are basically electron-density-based topological analyses. The charge localization between the donor-acceptor moieties was analyzed using the NBO analysis. Using the LED analysis, the binding energy between the tapinarof and EtOH was partitioned into different energy terms centered on a domain-based local pair natural orbital coupled cluster method. Thus, the electronic environment of the tapinarof-EtOH systems is evaluated.

A variety of anticancer and antibacterial drugs target DNA as one of their primary intracellular targets. Understanding ligand–DNA interactions and developing new, promising bioactive molecules for clinical use are greatly aided by elucidating the interaction between small molecules and natural polymeric DNAs. Small molecules′ ability to attach to and inhibit DNA replication and transcription provides more information on how drugs impact the expression of genes. Yohimbine has been broadly studied in pharmacological properties, while its binding mode to DNA has not been explicated so far. In this study, an attempt was made to explore the interaction between Yohimbine (YH) and calf thymus (CT-DNA) by using varying thermodynamics and in silico approaches. Minor hypochromic and bathochromic shifts of fluorescence intensity were observed, suggesting the binding of YH to CT-DNA. The Scatchard plot analysis using the McGhee–von Hipple method revealed noncooperative binding and affinities in the range of 10 5 M –1 . The binding stoichiometry value is 2:1 (2 molecules of YH were span by 1…

De novo lipogenesis (DNL) is a critical metabolic process that provides the majority of lipids for adipocyte and liver tissue. In cancer, obesity, type II diabetes, and nonalcoholic fatty liver disease DNL becomes dysregulated. A deeper understanding of the rates and of subcellular organization of DNL is necessary for identifying how this dysregulation occurs and varies across individuals and diseases. However, DNL is difficult to study inside the cell because labeling lipids and their precursors is not trivial. Existing techniques either can only measure parts of DNL, like glucose uptake, or do not provide spatiotemporal resolution. Here, we track DNL in space and time as isotopically labeled glucose is converted to lipids in adipocytes using optical photothermal infrared microscopy (OPTIR). OPTIR provides submicron resolution infrared imaging of the glucose metabolism in both living and fixed cells while also reporting on the identity of lipids and other biomolecules. We show significant incorporation of the labeled carbons into triglycerides in lipid droplets over the course of…

High Resolution Image Download MS PowerPoint Slide Efficient CO 2 capture is indispensable for achieving a carbon-neutral society while maintaining a high quality of life. Since the discovery that ionic liquids (ILs; room-temperature molten salts) can absorb CO 2, various solvents composed of molecular ions have been studied. However, it is challenging to observe the properties of each isolated ion component to control the function of ILs as they are mixtures of ions. Finding the optimal cation–anion combination for the CO 2 absorbent from their enormous chemical space had been impossible in a practical sense. This study applied electronic structure informatics to explore ILs with high CO 2 solubility from 402,114 IL candidates. The feature variables were determined by a set of cheap quantum chemistry calculations for isolated small-ion fragments, and the importance of molecular geometries and electronic states governing molecular interactions was identified via the wrapper method. As a result, it was clearly shown that the electronic states of ionic species must have essential…

. As a first step, available force fields for describing ethylene glycol oligomers were tested on how accurately they reproduced experimental properties. They were found to all fall short on either reproducing density, a static property, or the self-diffusion coefficient, a dynamic property. Discrepancies with the experimental data increased with the increasing size of the tested ethylene glycol oligomer. From the available force fields, the optimized potential for liquid simulation (OPLS) force field was used to further investigate which adjustments to the force field would improve the agreement of simulated physical properties with experimental ones. Two parameters were identified and adjusted, the (HO)-C-C-O proper dihedral potential and the polarity of the hydroxy group. The parameter adjustments depended on the size of the ethylene glycol oligomer. Next, PEG200 was simulated with the OPLS force field with and without modifications to inspect their effects on the simulation results. The modifications to the OPLS force field significantly decreased hydrogen bonding overall and…

The formation of amyloid fibrils is a complex phenomenon that remains poorly understood at the atomic scale. Herein, we perform extended unbiased all-atom simulations in explicit solvent of a short amphipathic peptide to shed light on the three mechanisms accounting for fibril formation, namely, nucleation via primary and secondary mechanisms, and fibril growth. We find that primary nucleation takes place via the formation of an intermediate state made of two laminated β-sheets oriented perpendicular to each other. The amyloid fibril spine subsequently emerges from the rotation of these β-sheets to account for peptides that are parallel to each other and perpendicular to the main axis of the fibril. Growth of this spine, in turn, takes place via a dock-and-lock mechanism. We find that peptides dock onto the fibril tip either from bulk solution or after diffusing on the fibril surface. The latter docking pathway contributes significantly to populate the fibril tip with peptides. We also find that side chain interactions drive the motion of peptides in the lock phase during growth,…

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores…

High Resolution Image Download MS PowerPoint Slide Ion transport properties and hydrogen solubility in brine play pivotal roles in various engineering and scientific scopes including chemical, physical, geochemical, and geothermal domains. Molecular dynamics simulations were performed to obtain transport properties of NaCl in the binary H 2 O + NaCl system using different force fields. Brine density, ion diffusivity, molar conductivity, conductivity, and hydrogen solubilities were obtained as functions of temperature and salt concentration. We compared the performance of different force fields against the experimental correlation model and developed three mathematical models. The first was the modified brine density model based on the simulated brine density over a wide range of salinity levels, and the second and third analytical mathematical models were derived for the ion diffusivity and molar conductivity as a function of salinity and temperature. The results of this study illustrated that the modified brine density model not only produced the same results of the previous model…

Over the past 20 years, the most studied and debated aspect of macromolecular crowding is how it affects protein stability. Traditionally, it is explained by a delicate balance between the stabilizing entropic effect and the stabilizing or destabilizing enthalpic effect. However, this traditional crowding theory cannot explain experimental observations like (i) negative entropic effect and (ii) entropy-enthalpy compensation. Herein, we provide experimental evidence that associated water dynamics plays a crucial role in controlling protein stability in the crowded milieu for the first time. We have correlated the modulation of associated water dynamics with the overall stability and its individual components. We showed that rigid associated water would stabilize the protein through entropy but destabilize it through enthalpy. In contrast, flexible associated water destabilizes the protein through entropy but stabilizes through enthalpy. Consideration of entropic and enthalpic modulation through crowder-induced distortion of associated water successfully explains the negative entropic…

It is critical to design the solvents or additives to provide high oxidation stability of electrolyte and good solid-electrolyte interphase (SEI) in lithium secondary batteries. In this work, we used quantum chemical calculations to evaluate carbonates with various fluorinated patterns to satisfy the requirements of antioxidation, stabilize SEI films, and modify solvation structures. The thermodynamic cycle method was used to calculate the oxidation and reduction potentials of a series of fluorinated linear (dimethyl carbonate, diethyl carbonate, and methyl ethyl carbonate) and cyclic carbonates (ethylene carbonate, propylene carbonate, and 2,3-butanediol cyclic carbonate) vs Li + /Li. Both quantity and position of fluorine substitutions have a significant impact on the oxidation and reduction potentials according to correlation analyses. The instinctive causes for the potential change were the influence of the fluorinated position on the frontier orbital. We further studied lithium-ion coordinated fluorinated carbonates and found that the binding energy is mostly determined by…