The role of flow in the self-assembly of dragline spider silk proteins.

Hydrodynamic flow in the spider duct induces conformational changes in dragline spider silk proteins (spidroins) and drives their assembly, but the underlying physical mechanisms are still elusive. Here we address this challenging multiscale problem with a complementary strategy of atomistic and coarse-grained molecular dynamics simulations with uniform flow. The conformational changes at the molecular level were analyzed for single-tethered spider silk peptides. Uniform flow leads to coiled-to-stretch transitions and pushes alanine residues into ß sheet and poly-proline II conformations. Coarse-grained simulations of the assembly process of multiple semi-flexible block copolymers using multi-particle collision dynamics reveal that the spidroins aggregate faster but into low-order assemblies when they are less extended. At medium-to-large peptide extensions (50%-80%), assembly slows down and becomes reversible with frequent association and dissociation events, whereas spidroin alignment increases and alanine repeats form ordered regions. Our work highlights the role of flow in guiding silk self-assembly into tough fibers by enhancing alignment and kinetic reversibility, a mechanism likely relevant also for other proteins whose function depends on hydrodynamic flow.

Understanding the performance of graphdiyne membrane for the separation of nitrate ions from aqueous solution at the atomistic scale.

A molecular dynamics simulation study is conducted to investigate the capability of the pristine graphdiyne nanosheet for nitrate ion separation from water. The removal of nitrate ion contaminants from water is of critical importance as it represents an environmental hazard. The graphdiyne is a carbon-based membrane with pore density of 2.4 × 1018 pores/m2 and incircle radius of 2.8 Å. We show that the efficient water flow is accurately controlled through fine regulation of the exerted hydrostatic pressure. The high water permeability of 6.19 L.Day-1cm-2MPa-1 with 100% nitrate ions rejection suggests that the graphdiyne can perform as a suitable membrane for nitrate separation. The potential of mean force analysis of the single water molecule and nitrate ion indicated the free energy barriers for nitrate of about 4 times higher than that of water molecules. The results reveal the weak interaction of the water molecules and the membrane which aid to high water flux.

Efficient Removal of Heavy Metals from Aqueous Solutions through Functionalized γ-Graphyne-1 Membranes under External Uniform Electric Fields: Insights from Molecular Dynamics Simulations.

Carbon-based nanosheet membranes with functionalized pores have great potential as water treatment membranes. In this study, the separation of Hg2+ and Cu2+ as heavy metal ions from aqueous solutions using a functionalized γ-graphyne-1 nanosheet membrane is investigated by molecular dynamics simulations. The simulation systems consist of a γ-graphyne-1 nanosheet with -COOH or -NH2 functional groups on the edge of pores placed in an aqueous solution containing CuCl2 and HgCl2. An external electric field is applied as a driving force across the membrane for the separation of heavy metal ions using these functionalized pores. The ion-membrane and water molecule-membrane interaction energies, the radial distribution function of cations, the retention time and permeation of ions through the membrane, the density profile of water and ions, and the hydrogen bond in the system are investigated, and these results reveal that the performance of -NH2-functionalized γ-graphyne-1 is better than that of -COOH-functionalized γ-graphyne-1 in the separation of Cu2+, while the Hg2+ cations encounter a high energy barrier as they pass through the membrane, especially in the -COOH-functionalized pore, due to their larger ionic radius and the smaller pore size of this membrane.

Selecting XFEL single-particle snapshots by geometric machine learning.

A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of individual molecules, so-called single particles. Here, we present a method that allows for efficient identification of single particles in very large XFEL datasets, operates at low signal levels, and is tolerant to background. This method uses supervised Geometric Machine Learning (GML) to extract low-dimensional feature vectors from a training dataset, fuse test datasets into the feature space of training datasets, and separate the data into binary distributions of "single particles" and "non-single particles." As a proof of principle, we tested simulated and experimental datasets of the Coliphage PR772 virus. We created a training dataset and classified three types of test datasets: First, a noise-free simulated test dataset, which gave near perfect separation. Second, simulated test datasets that were modified to reflect different levels of photon counts and background noise. These modified datasets were used to quantify the predictive limits of our approach. Third, an experimental dataset collected at the Stanford Linear Accelerator Center. The single-particle identification for this experimental dataset was compared with previously published results and it was found that GML covers a wide photon-count range, outperforming other single-particle identification methods. Moreover, a major advantage of GML is its ability to retrieve single particles in the presence of structural variability.

Organic Filling Mitigates Flaw-Sensitivity of Nanoscale Aragonite.

Engineering at nanoscale holds the promise of tuning materials with extraordinary properties. However, macroscopic approaches commonly used to predict mechanical properties do not fully apply at nanoscale level. A controversial feature is the presence of nanoflaws in aragonite nacre, as it is expected that flaws would weaken the material, whereas nacre still shows high toughness and rupture strength. Here, we performed molecular dynamics and finite element simulations emulating flaws found in aragonite nacre. Our simulations reveal two regimes for fracture: nacre remains flaw-insensitive only for flaws smaller than 1.2 nm depth, or flaws of a few atoms, whereas larger flaws follow a Griffith-like trend resembling macroscopic fracture. We tested an alternative mechanism for flaw-insensitivity in nacre, and investigated the mechanical effect of organic filling to mitigate fracture. We found that a single nacre protein, perlucin, decreases the stress concentration at the fracture point, producing enhancements of up to 15% in rupture strength. Our study reveals a more comprehensive understanding of mechanical stability at the nanoscale and offers new routes toward hybrid nanomaterials.

Sustaining dry surfaces under water.

Rough surfaces immersed under water remain practically dry if the liquid-solid contact is on roughness peaks, while the roughness valleys are filled with gas. Mechanisms that prevent water from invading the valleys are well studied. However, to remain practically dry under water, additional mechanisms need consideration. This is because trapped gas (e.g. air) in the roughness valleys can dissolve into the water pool, leading to invasion. Additionally, water vapor can also occupy the roughness valleys of immersed surfaces. If water vapor condenses, that too leads to invasion. These effects have not been investigated, and are critically important to maintain surfaces dry under water. In this work, we identify the critical roughness scale, below which it is possible to sustain the vapor phase of water and/or trapped gases in roughness valleys - thus keeping the immersed surface dry. Theoretical predictions are consistent with molecular dynamics simulations and experiments.

Structure and response to flow of the glycocalyx layer.

The glycocalyx is a sugar-rich layer located at the luminal part of the endothelial cells. It is involved in key metabolic processes and its malfunction is related to several diseases. To understand the function of the glycocalyx, a molecular level characterization is necessary. In this article, we present large-scale molecular-dynamics simulations that provide a comprehensive description of the structure and dynamics of the glycocalyx. We introduce the most detailed, to-date, all-atom glycocalyx model, composed of lipid bilayer, proteoglycan dimers, and heparan sulfate chains with realistic sequences. Our results reveal the folding of proteoglycan ectodomain and the extended conformation of heparan sulfate chains. Furthermore, we study the glycocalyx response under shear flow and its role as a flypaper for binding fibroblast growth factors (FGFs), which are involved in diverse functions related to cellular differentiation, including angiogenesis, morphogenesis, and wound healing. The simulations show that the glycocalyx increases the effective concentration of FGFs, leading to FGF oligomerization, and acts as a lever to transfer mechanical stimulus into the cytoplasmic side of endothelial cells.

Barriers to superfast water transport in carbon nanotube membranes.

Carbon nanotube (CNT) membranes hold the promise of extraordinary fast water transport for applications such as energy efficient filtration and molecular level drug delivery. However, experiments and computations have reported flow rate enhancements over continuum hydrodynamics that contradict each other by orders of magnitude. We perform large scale molecular dynamics simulations emulating for the first time the micrometer thick CNTs membranes used in experiments. We find transport enhancement rates that are length dependent due to entrance and exit losses but asymptote to 2 orders of magnitude over the continuum predictions. These rates are far below those reported experimentally. The results suggest that the reported superfast water transport rates cannot be attributed to interactions of water with pristine CNTs alone.

Electrically induced conformational change of peptides on metallic nanosurfaces.

Surface immobilized biomolecular probes are used in many areas of biomedical research, such as genomics, proteomics, immunology, and pathology. Although the structural conformations of small DNA and peptide molecules in free solution are well studied both theoretically and experimentally, the conformation of small biomolecules bound on surfaces, especially under the influence of external electric fields, is poorly understood. Using a combination of molecular dynamics simulation and surface-enhanced Raman spectroscopy, we study the external electric field-induced conformational change of dodecapeptide probes tethered to a nanostructured metallic surface. Surface-tethered peptides with and without phosphorylated tyrosine residues are compared to show that peptide conformational change under electric field is sensitive to biochemical modification. Our study proposes a highly sensitive in vitro nanoscale electro-optical detection and manipulation method for biomolecule conformation and charge at bio-nano interfaces.

Computational microscopy of the role of protonable surface residues in nanoprecipitation oscillations.

A novel phenomenon has recently been reported in polymeric nanopores. This phenomenon, so-called nanoprecipitation, is characterized by the transient formation of precipitates in the nanopore lumen, producing a sequence of low and high conductance states in the ionic current through the pore. By means of all-atom molecular dynamics simulations, we studied nanoprecipitation for polyethylene terephthalate nanopore immersed in electrolytic solution containing calcium phosphate, covering a total simulation time of 1.24 micros. Our results suggest that protonable surface residues at the nanopore surface, namely carboxyl groups, trigger the formation of precipitates that strongly adhere to the surface, blocking the pore and producing the low conductance state. On the basis of the simulations, we propose a mechanism for the formation of the high conductance state; the mechanism involves detachment of the precipitate from the surface due to reprotonation of carboxyl groups and subsequent translocation of the precipitate out of the pore.

Ionic Current Rectification Through Silica Nanopores.

Nanopores immersed in electrolytic solution and under the influence of an electric field can produce ionic current rectification, where ionic currents are higher for one voltage polarity than for the opposite polarity, resulting in an asymmetric current-voltage (I-V) curve. This behavior has been observed in polymer and silicon-based nanopores as well as in theoretically studied continuum models. By means of atomic level molecular dynamics (MD) simulations, we have performed a systematic investigation of KCl conductance in silica nanopores with a total simulation time of 680 ns. We found that ion-binding spots at the silica surfaces, such as dangling atoms, have effects on the ion concentration and electrostatic potential inside the nanopore, producing asymmetric I-V curves. Conversely, silica surfaces without ion-binding spots produce symmetric I-V curves.

Molecular control of ionic conduction in polymer nanopores.

Polymeric nanopores show unique transport properties and have attracted a great deal of scientific interest as a test system to study ionic and molecular transport at the nanoscale. By means of all-atom molecular dynamics, we simulated the ion dynamics inside polymeric polyethylene terephthalate nanopores. For this purpose, we established a protocol to assemble atomic models of polymeric material into which we sculpted a nanopore model with the key features of experimental devices, namely a conical geometry and a negative surface charge density. Molecular dynamics simulations of ion currents through the pore show that the protonation state of the carboxyl group of exposed residues have a considerable effect on ion selectivity, by affecting ionic densities and electrostatic potentials inside the nanopores. The role of high concentrations of Ca2+ ions was investigated in detail.

Water-silica force field for simulating nanodevices.

Amorphous silica is an inorganic material that is central for many nanotechnology applications, such as nanoelectronics, microfluidics, and nanopore sensors. To use molecular dynamics (MD) simulations to study the behavior of biomolecules interacting with silica, we developed a force field for amorphous silica surfaces based on their macroscopic wetting properties that is compatible with the CHARMM force field and TIP3P water model. The contact angle of a water droplet on a silica surface served as a criterion to tune the intermolecular interactions. The resulting force field was used to study the permeation of water through silica nanopores, illustrating the influence of the surface topography and the intermolecular parameters on permeation kinetics. We find that minute modeling of the amorphous surface is critical for MD studies, since the particular arrangement of surface atoms controls sensitively electrostatic interactions between silica and water.

Dynamic influences on a high-affinity, high-specificity interaction involving the C-terminal SH3 domain of p67phox.

An analysis of the backbone dynamics of the C-terminal Src homology 3 (SH3) domain of p67(phox), p67(phox)SH3(C), in complex with a 32-residue high-affinity (K(d) = 24 nM) peptide, Pf, from the C-terminal region of p47(phox) is presented. This paper represents the first detailed analysis of the backbone dynamics and the ligand-induced changes therein of a high-affinity, high-specificity interaction involving an SH3 domain. The dynamic features are compared with those in the high-affinity, highly specific interaction between the SH3 domain of C-terminal Src kinase (Csk-SH3) and a proline-rich peptide from proline-enriched phosphatase (PEP). Both systems share common dynamic features especially in the canonical PxxP motif recognition surface where slow micro- to millisecond time scale dynamics persist on complex formation especially in several residues that are implicated in ligand recognition and in stabilizing the SH3 fold. These residues are highly conserved in SH3 domains. Ile505, which lies outside the PxxP recognition motif on p67(phox)SH3(C) and is key in conferring high specificity to the p67(phox)SH3(C)/Pf interaction, becomes more disordered upon complex formation. This behavior is similar to that seen in the residues that constitute the specificity surface in Csk-SH3.