The Journal of Physical Chemistry B最新文献

Ceramide transfer protein CERT is the mediator of nonvesicular transfer of ceramide from the ER to Golgi. In CERT, START is the domain responsible for the binding and transport of ceramide. A wealth of structural data has revealed a helix-grip fold surrounding a large hydrophobic cavity holding the ceramide. Yet, little is known about the mechanisms by which START releases the ceramide through the polar region and into the packed environment of cellular membranes. As such events do not lend themselves easily to experimental investigations, we used multiple unbiased microsecond-long molecular simulations. We propose a membrane-assisted mechanism in which the membrane acts as an allosteric effector initiating the release of ceramide and where the passage of the ceramide acyl chains is facilitated by the intercalation of a single phosphatidylcholine lipid in the cavity, practically greasing the ceramide way out. We verify using free energy calculation and experimental lipidomics data that CERT forms stable complexes with phosphatidylcholine lipids, in addition to ceramide, thus providing validation for the proposed mechanism.

Coiled-coil protein origami (CCPO) is a modular strategy for the de novo design of polypeptide nanostructures. It represents a type of modular design based on pairwise-interacting coiled-coil (CC) units with a single-chain protein programmed to fold into a polyhedral cage. However, the mechanisms underlying the self-assembly of the protein tetrahedron are still not fully understood. In the present study, 18 CCPO cages with three different topologies were modeled in silico. Then, molecular dynamics simulations and CC parameters were calculated to characterize the dynamic properties of protein tetrahedral cages at both the local and global levels. Furthermore, a deformed CC unit was redesigned, and the stability of the new cage was significantly improved.

We present software infrastructure for the design and testing of new quantum mechanical/molecular mechanical and machine-learning potential (QM/MM−ΔMLP) force fields for a wide range of applications. The software integrates Amber’s molecular dynamics simulation capabilities with fast, approximate quantum models in the xtb package and machine-learning potential corrections in DeePMD-kit. The xtb package implements the recently developed density-functional tight-binding QM models with multipolar electrostatics and density-dependent dispersion (GFN2-xTB), and the interface with Amber enables their use in periodic boundary QM/MM simulations with linear-scaling QM/MM particle-mesh Ewald electrostatics. The accuracy of the semiempirical models is enhanced by including machine-learning correction potentials (ΔMLPs) enabled through an interface with the DeePMD-kit software. The goal of this paper is to present and validate the implementation of this software infrastructure in molecular dynamics and free energy simulations. The utility of the new infrastructure is demonstrated in proof-of-concept example applications. The software elements presented here are open source and freely available. Their interface provides a powerful enabling technology for the design of new QM/MM−ΔMLP models for studying a wide range of problems, including biomolecular reactivity and protein–ligand binding.

The characterization of cryptic pockets has been elusive, despite substantial efforts. Computational modeling approaches, such as molecular dynamics (MD) simulations, can provide atomic-level details of binding site motions and binding pathways. However, the time scale that MD can achieve at a reasonable cost often limits its application for cryptic pocket identification. Enhanced sampling techniques can improve the efficiency of MD simulations by focused sampling of important regions of the protein, but prior knowledge of the simulated system is required to define the appropriate coordinates. In the case of a novel, unknown cryptic pocket, such information is not available, limiting the application of enhanced sampling techniques for cryptic pocket identification. In this work, we explore the ability of SiteMap and Site Finder, widely used commercial packages for pocket identification, to detect focus points on the protein and further apply other advanced computational methods. The information gained from this analysis enables the use of computational modeling, including enhanced MD sampling techniques, to explore potential cryptic binding pockets suggested by SiteMap and Site Finder. Here, we examined SiteMap and Site Finder results on 136 known cryptic pockets from a combination of the PocketMiner dataset (a recently curated set of cryptic pockets), the Cryptosite Set (a classic set of cryptic pockets), and Natural killer group 2D (NKG2D, a protein target where a cryptic pocket is confirmed). Our findings demonstrate the application of existing, well-studied tools in efficiently mapping potential regions harboring cryptic pockets.

The existence of liquid carbon as an intermediate phase preceding the formation of novel carbon materials has been a point of contention for several decades. Experimental observation of such a liquid state requires nonthermal melting of solid carbon materials at various laser fluences and pulse properties. Reflectivity experiments performed in the mid-1980s reached opposing conclusions regarding the metallic or insulating properties of the purported liquid state. Time-resolved X-ray absorption studies showed shortening of C–C bonds and increasing diffraction densities, thought to evidence a liquid or glassy carbon state, respectively. Nevertheless, none of these experiments provided information on the electronic structure of the proposed liquid state. Herein, we report the results of time-resolved resonant inelastic X-ray scattering (RIXS) and time-resolved X-ray emission spectroscopy (XES) studies on amorphous carbon (a-C) and ultrananocrystalline diamond (UNCD) as a function of delay time between the irradiating pulse and X-ray probe. For both a-C and UNCD, we attribute decreases in RIXS or XES signals to transition blocking, relaxation, and finally, ablation. Increased signal at 20 ps following the irradiation of the UNCD is attributed to the probable formation of nanoscale structures in the ablation plume. Differences in the amount of signal observed between a-C and UNCD are explained by the difference in sample thickness and, specifically, incomplete melting of the UNCD film. Comparisons to spectral simulations based on MD trajectories at extreme conditions indicate that the carbon state in our experiments is crystalline. Normal mode analysis confirmed that symmetrical bending or stretching of the C–C bonds in the diamond lattice results in XES spectra with small intensity differences. Overall, we observed no evidence of melting to a liquid state, as determined by the lack of changes in the spectral properties for up to 100 ps delays following the melting pulses.

Berubicin, a chemotherapy medication belonging to the class of anthracyclines, is simulated in double-stranded DNA sequences and cyclodextrins in an aqueous environment via full-atom molecular dynamics simulations on the time scale of microseconds. The drug is studied in both the neutral and protonated states so as to better comprehend the role of its charge in the formed complexes. The noncovalent berubicin–DNA and berubicin–cyclodextrin complexes are investigated in detail, paying special attention to their thermodynamic description by employing the double decoupling method, the solvent balance method, the weighted solvent accessible surface model, and the linear interaction energy method. A novel approach for extracting the desolvation thermodynamics of the binding process is also presented. Both the binding and desolvation Gibbs energies are decomposed into entropic and enthalpic contributions so as to elucidate the nature of complexation and its driving forces. Selected structural and geometrical properties of all the complexes, which are all stable, are analyzed. Both cyclodextrins under consideration are widely utilized for drug delivery purposes, and a comparative investigation between their bound states with berubicin is carried out.

AOT reverse micelles are a common and convenient model system for studying the effects of nanoconfinement on aqueous solutions. The reverse micelle shape is important to understanding how the constituent components come together to form the coherent whole and the unique properties observed there. The shape of reverse micelles impacts the amount of interface present and the distance of the solute from the interface and is therefore vital to understanding interfacial properties and the behavior of solutes in the polar core. In this work, we use previously introduced measures of shape, the coordinate-pair eccentricity (CPE) and convexity, and apply them to a series of simulations of AOT reverse micelles. We simulate the most commonly used force field for AOT reverse micelles, the CHARMM force field, but we also adapt the OPLS force field for use with AOT, the first work to do so, in addition to using both 3- and 4-site water models. Altogether, these simulations are designed to examine the impact of the force field on the shape of the reverse micelles in detail. We also study the time autocorrelation of shape, the water rotational anisotropy decay, and how the CPE changes between the water pool and AOT tail groups. We find that although the force field changes the shape noticeably, AOT reverse micelles are always amorphous particles. The shape of the micelles changes on the order of 10 ns. The water rotational dynamics observed match the experiment and demonstrate slower dynamics relative to bulk water, suggesting a two-population model that fits a core/shell hypothesis. Taken together, our results indicate that it is likely not possible to create a perfect force field that can reproduce every aspect of the AOT reverse micelle accurately. However, the magnitude of the differences between simulations appears relatively small, suggesting that any reasonably derived force field should provide an acceptable model for most work on AOT reverse micelles.

The enzymatic biosensors’ response can be monitored based on the results of nonlinear differential equations. The nonlinear reaction-diffusion equations proposed for this enzyme-based electrochemical biosensor include a nonlinear term associated with Michaelis–Menten kinetics. Herein, the system of nonlinear reaction-diffusion equations is solved using a modified homotopy perturbation method. For all values of the rate constants, the approximate analytical expressions for the concentration profiles, current, sensitivity, and gradient of biosensor have been determined. Performance factors of an enzymatic electrochemical biosensor, such as response time, sensitivity, accuracy, and resistance, are discussed. The analytical results and numerically simulated outcomes using Matlab software have been compared.

The bending modulus of a lipid bilayer quantifies its mechanical resistance to curvature. It is typically understood in terms of thickness; e.g., thicker bilayers are usually stiffer. Here, we describe an additional and powerful molecular determinant of stiffness─the variance in the distribution of curvature sensitivity of lipids and lipid conformations. Zwitterionic choline and ethanolamine headgroups of glycerophospholipids dynamically explore inter- and intraspecies interactions, leading to transient clustering. We demonstrate that these clusters couple strongly to negative curvature, exciting undulatory membrane modes and reducing the apparent bending modulus. Three force fields (Martini 2, Martini 3, and all-atom CHARMM C36) each show the effect to a different extent, with the coarse-grained Martini models showing the most clustering and thus the most softening. The theory is a guide to understanding the stiffness of biological membranes with their complex composition, as well as how choices of force field parameterization are translated into mechanical stiffness.

The dynamics of the conjugated polymers poly(9,9-dioctylfluorene) (PF8) and poly(9,9-didodecylfluorene) (PF12), differing by the length of their side chains, is investigated in the amorphous phase using the temperature-dependent quasielastic neutron scattering (QENS) technique. The neutron spectroscopy measurements are synergistically underpinned by molecular dynamics (MD) simulations. The probe is focused on the picosecond time scale, where the structural dynamics of both PF8 and PF12 would mainly be dominated by the motions of their side chains. The measurements highlighted temperature-induced dynamics, reflected in the broadening of the QENS spectra upon heating. The MD simulations reproduced well the observations; hence, the neutron measurements validate the MD force fields, the adopted amorphous model structures, and the numerical procedure. As the QENS spectra are dominated by the signal from the hydrogens on the backbones and side chains of PF8 and PF12, extensive analysis of the MD simulations allowed the following: (i) tagging these hydrogens, (ii) estimating their contributions to the self-part of the van Hove functions and hence to the QENS spectra, and (iii) determining the activation energies of the different motions involving the tagged hydrogens. PF12 is found to exhibit QENS spectra broader than those of PF8, indicating a more pronounced motion of the didodecyl chains of PF12 as compared to dioctyl chains of PF8. This is in agreement with the outcome of our MD analysis: (i) confirming a lower glass transition temperature of PF12 compared to PF8, (ii) showing PF12 having a lower density than PF8, and (iii) highlighting lower activation energies of the motions of PF12 in comparison with PF8. This study helped to gain insights into the temperature-induced side-chain dynamics of the PF8 and PF12 conjugated polymers, influencing their stability, which could potentially impact, on the practical side, the performance of the associated optoelectronic active layer.