The molecular mechanics force field Slipids developed in a series of works by Jämbeck and Lyubartsev (J. Phys. Chem. B 2012, 116, 3164–3179; J. Chem. Theory Comput. 2012, 8, 2938–2948) generally ...provides a good description of various lipid bilayer systems. However, it was also found that order parameters of C–H bonds in the glycerol moiety of the phosphatidylcholine headgroup deviate significantly from NMR results. In this work, the dihedral force field parameters have been reparameterized in order to improve the agreement with experiment. For this purpose, we have computed energies for a large amount of lipid headgroup conformations using density functional theory on the B3P86/cc-pvqz level and optimized dihedral angle parameters simultaneously to provide the best fit to the quantum chemical energies. The new parameter set was validated for three lipid bilayer systems against a number of experimental properties including order parameters, area per lipid, scattering form factors, bilayer thickness, area compressibility and lateral diffusion coefficients. In addition, the order parameter dependence on cholesterol content in the POPC bilayer was investigated. It is shown that the new force field significantly improves agreement with the experimental order parameters for the lipid headgroup while keeping good agreement with other experimentally measured properties.
Piezoelectric semiconductors can be polarized and used in mechanoredox systems and photoredox catalysis. Conventional non-piezoelectric semiconductors have limitations when it comes to charge carrier ...recombination and slow transport rates in catalytic reactions, which can be overcome by piezoelectric polarization processes in piezoelectric semiconductors. Heterostructures based on semiconducting piezoelectrics often offer enhanced catalytic reactivities that are related to their mechanical, piezoelectric, optical, and electronic characteristics. We review how to use such heterostructures to convert mechanical energy into chemical energy, and how the related piezoelectric polarization tunes the band structures and provides advantages in piezophotocatalysis over regular photocatalysis. We discuss fundamental concepts of piezoelectricity, piezoelectric potential, and examine different piezoelectric heterostructures for piezo- and piezophotocatalysis. A review of dynamic investigations of piezo- and piezophotocatalytic processes is presented. The complementary developments in the understanding of the piezotronic and piezophototronic effects are described, which include the induced charge-transfer mechanisms for piezo- and piezophotocatalytic reactions that can occur with piezoelectric heterostructures. Finally, we derive design principles and suggest future research directions in the emerging field of piezo- and piezophotocatalysis employing semiconductive heterostructures.
Because piezoelectric semiconductors have mechanical, piezoelectric, optical, and electronic properties, the formation of piezoelectric polarization leads to piezotronic and piezophototronic effects, which can be used to tune their surface and bulk charge-transfer processes. With piezoelectric heterostructures the charge transport is enhanced and results in high efficiency piezo- and piezophotocatalytic performances, as compared with single components. Display omitted
•Review advances in using heterostructures to convert mechanical energy into chemical energy.•Dynamic investigations of piezo- and piezophotocatalytic processes are reviewed.•Complementary developments in the understanding of the piezotronic and piezophototronic effects are described.•Suggest possible future research directions for piezo- and piezophotocatalysis with semiconductive heterostructures.
Cholesterol is an essential component of all animal cell membranes and plays an important role in maintaining the membrane structure and physical-chemical properties necessary for correct cell ...functioning. The presence of cholesterol is believed to be responsible for domain formation (lipid rafts) due to different interactions of cholesterol with saturated and unsaturated lipids. In order to get detailed atomistic insight into the behaviour of cholesterol in bilayers composed of lipids with varying degrees of unsaturation, we have carried out a series of molecular dynamics simulations of saturated and polyunsaturated lipid bilayers with different contents of cholesterol, as well as well-tempered metadynamics simulations with a single cholesterol molecule in these bilayers. From these simulations we have determined distributions of cholesterol across the bilayer, its orientational properties, free energy profiles, and specific interactions of molecular groups able to form hydrogen bonds. Both molecular dynamics and metadynamics simulations showed that the most unsaturated bilayer with 22:6 fatty acid chains shows behaviour which is most different from other lipids. In this bilayer, cholesterol is relatively often found in a "flipped" configuration with the hydroxyl group oriented towards the membrane middle plane. This bilayer has also the highest (least negative) binding free energy among liquid phase bilayers, and the lowest reorientation barrier. Furthermore, cholesterol molecules in this bilayer are often found to form head-to-tail contacts which may lead to specific clustering behaviour. Overall, our simulations support ideas that there can be a subtle interconnection between the contents of highly unsaturated fatty acids and cholesterol, deficiency or excess of each of them is related to many human afflictions and diseases.
Aggregation of amyloid beta (Aβ) peptides in neuronal membranes is a known promoter of Alzheimer's disease. To gain insight into the molecular details of Aβ peptide aggregation and its effect on ...model neuronal membranes, we carried out molecular dynamics simulations of the Aβ(25-35) fragment of the amyloid precursor protein in phospholipid bilayers composed of either fully saturated or highly unsaturated lipids, in the presence or absence of cholesterol. It was found that the peptide does not penetrate through any of the considered membranes, but can reside in the headgroup region and upper part of the lipid tails showing a clear preference to a polyunsaturated cholesterol-free membrane. Due to the ordering and condensing effect upon addition of cholesterol, membranes become more rigid facilitating peptide aggregation on the surface. Except for the case of the cholesterol-free saturated lipid bilayer, the peptides have a small effect on the membrane structure and ordering. It was also found that the most "active" amino-acid for peptide-lipid and peptide-cholesterol interaction is methionine-35, followed by asparagine-27 and serine-26, which form hydrogen bonds between peptides and polar atoms of lipid headgroups. These amino acids are also primarily responsible for peptide aggregation. This work will be relevant for designing strategies to develop drugs to combat Alzheimer's disease.
Molecular dynamics simulations of Aβ(25-35) peptides in phospholipid bilayers are carried out to investigate the effect of polyunsaturated lipids and cholesterol on aggregation of the peptides.
Understanding interactions of inorganic nanoparticles with biomolecules is important in many biotechnology, nanomedicine, and toxicological research, however, the size of typical nanoparticles makes ...their direct modeling by atomistic simulations unfeasible. Here, we present a bottom‐up coarse‐graining approach for modeling titanium dioxide (TiO 2) nanomaterials in contact with phospholipids that uses the inverse Monte Carlo method to optimize the effective interactions from the structural data obtained in small‐scale all‐atom simulations of TiO 2 surfaces with lipids in aqueous solution. The resulting coarse‐grained models are able to accurately reproduce the structural details of lipid adsorption on different titania surfaces without the use of an explicit solvent, enabling significant computational resource savings and favorable scaling. Our coarse‐grained simulations show that small spherical TiO 2 nanoparticles (r=2 nm) can only be partially wrapped by a lipid bilayer with phosphoethanolamine headgroups, however, the lipid adsorption increases with the radius of the nanoparticle. The current approach can be used to study the effect of the size and shape of TiO 2 nanoparticles on their interactions with cell membrane lipids, which can be a determining factor in membrane wrapping as well as the recently discovered phenomenon of nanoquarantining, which involves the formation of layered nanomaterial–lipid structures.
Understanding interactions of inorganic nanoparticles with biomolecules is important in many biotechnology, nanomedicine, and toxicological research, however, the size of typical nanoparticles makes ...their direct modeling by atomistic simulations unfeasible. Here, we present a bottom‐up coarse‐graining approach for modeling titanium dioxide (TiO 2) nanomaterials in contact with phospholipids that uses the inverse Monte Carlo method to optimize the effective interactions from the structural data obtained in small‐scale all‐atom simulations of TiO 2 surfaces with lipids in aqueous solution. The resulting coarse‐grained models are able to accurately reproduce the structural details of lipid adsorption on different titania surfaces without the use of an explicit solvent, enabling significant computational resource savings and favorable scaling. Our coarse‐grained simulations show that small spherical TiO 2 nanoparticles (r=2 nm) can only be partially wrapped by a lipid bilayer with phosphoethanolamine headgroups, however, the lipid adsorption increases with the radius of the nanoparticle. The current approach can be used to study the effect of the size and shape of TiO 2 nanoparticles on their interactions with cell membrane lipids, which can be a determining factor in membrane wrapping as well as the recently discovered phenomenon of nanoquarantining, which involves the formation of layered nanomaterial–lipid structures.
Computational methods have become an important tool in studying the mechanisms of nanomaterial exposure. However, while the simulations of nanoparticles interacting with biomatter at atomic resolution are exceptionally detailed, computing power becomes a bottleneck with the increasing size of simulated systems. Here we present a coarse‐grained model of TiO 2 nanomaterials in contact with cell membrane phospholipids, which is significantly faster yet captures the structural detail from atomistic simulations with the help of the inverse Monte Carlo method.
Zinc oxide nanostructures are used in an ever increasing line of applications in technology and biomedical fields. This requires a detailed understanding of the phenomena that occur at the surface ...particularly in aqueous environments and in contact with biomolecules. In this work, we used ab initio molecular dynamics (AIMD) simulations to determine structural details of ZnO surfaces in water and to develop a general and transferable classical force field for hydrated ZnO surfaces. AIMD simulations show that water molecules dissociate near unmodified ZnO surfaces, forming hydroxyl groups at about 65% of the surface Zn atoms and protonating 3-coordinated surface oxygen atoms, while the rest of the surface Zn atoms bind molecularly adsorbed waters. Several force field atom types for ZnO surface atoms were identified by analysis of the specific connectivities of atoms. The analysis of the electron density was then used to determine partial charges and Lennard-Jones parameters for the identified force field atom types. The obtained force field was validated by comparison with AIMD results and with available experimental data on adsorption and immersion enthalpies, as well as adsorption free energies of several amino acids in methanol. The developed force field can be used for modeling of ZnO in aqueous and other fluid environments and in interaction with biomolecules.
Adsorption free energies of 32 small biomolecules (amino acids side chains, fragments of lipids, and sugar molecules) on 33 different nanomaterials, computed by the molecular dynamics - metadynamics ...methodology, have been analyzed using statistical machine learning approaches. Multiple unsupervised learning algorithms (principal component analysis, agglomerative clustering, and K-means) as well as supervised linear and nonlinear regression algorithms (linear regression, AdaBoost ensemble learning, artificial neural network) have been applied. As a result, a small set of biomolecules has been identified, knowledge of adsorption free energies of which to a specific nanomaterial can be used to predict, within the developed machine learning model, adsorption free energies of other biomolecules. Furthermore, the methodology of grouping of nanomaterials according to their interactions with biomolecules has been presented.
An all-atomistic force field (FF) has been developed for fully saturated phospholipids. The parametrization has been largely based on high-level ab initio calculations in order to keep the empirical ...input to a minimum. Parameters for the lipid chains have been developed based on knowledge about bulk alkane liquids, for which thermodynamic and dynamic data are excellently reproduced. The FFs ability to simulate lipid bilayers in the liquid crystalline phase in a tensionless ensemble was tested in simulations of three lipids: 1,2-diauroyl-sn-glycero-3-phospocholine (DLPC), 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1,2-dipalmitoyl-sn-glycero-3-phospcholine (DPPC). Computed areas and volumes per lipid, and three different kinds of bilayer thicknesses, have been investigated. Most importantly NMR order parameters and scattering form factors agree in an excellent manner with experimental data under a range of temperatures. Further, the compatibility with the AMBER FF for biomolecules as well as the ability to simulate bilayers in gel phase was demonstrated. Overall, the FF presented here provides the important balance between the hydrophilic and hydrophobic forces present in lipid bilayers and therefore can be used for more complicated studies of realistic biological membranes with protein insertions.
We propose a method of bottom-up coarse-graining, in which interactions within a coarse-grained model are determined by an artificial neural network trained on structural data obtained from multiple ...atomistic simulations. The method uses ideas of the inverse Monte Carlo approach, relating changes in the neural network weights with changes in average structural properties, such as radial distribution functions. As a proof of concept, we demonstrate the method on a system interacting by a Lennard–Jones potential modeled by a simple linear network and a single-site coarse-grained model of methanol–water solutions. In the latter case, we implement a nonlinear neural network with intermediate layers trained by atomistic simulations carried out at different methanol concentrations. We show that such a network acts as a transferable potential at the coarse-grained resolution for a wide range of methanol concentrations, including those not included in the training set.
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