Different from earlier experiments where a one dimensional (1D) atomic SOC of pseudo-spin-1/2 is synthesized with Raman laser fields, the scheme we demonstrate employs a gradient magnetic field (GMF) and ground-state atoms, thus is immune to atomic spontaneous emission. The strength of SOC we realize can be tuned by changing the modulation amplitude of the GMF, and the effect of the SOC is confirmed through the studies of: 1) the collective dipole oscillation of an atomic condensate in a harmonic trap after the synthesized SOC is abruptly turned on; and 2) the minimum energy state at a finite adiabatically adjusted momentum when SOC strength is slowly ramped up. The condensate coherence is found to remain very good after driven by modulating GMFs. Our scheme presents an alternative means for studying interacting many-body systems with synthesized SOC.We report the observation of synthesized spin-orbit coupling (SOC) for ultracold spin-1  Spin-orbit coupling (SOC), as is often referred to in condensed matter physics, couples the spin of a particle to its orbital degrees of freedom. It is believed that SOC constitutes an important ingredient for quantum simulation with ultracold atoms123571011121314151617181115222324262728293032333435363738394041The Raman scheme, pioneered by the Spielman group2444et al.et al.485354To overcome the restrictions due to atomic spontaneous emission and to enhance tunability, one can seek out spin-dependent interactions between atoms and magnetic fields to synthesize SOC, as was proposed by Xu 87Rb atomic Bose-Einstein condensate (BEC) synthesized by modulating a one dimensional (1D) GMF48kso we report corresponds to a spin-dependent momentum shift ∝ mFkso to the single-particle dispersion curves for spin component mF, which gives rise to the three crossing dispersion curves for the three spin components of spin-1 atoms. The synthesized SOC is confirmed through the following two observations: first, we measure the excitation of the collective dipole mode of a condensate in a harmonic trap after abruptly turning on the SOC; and second, we achieve the adiabatic loading of condensed atoms into the minimum energy state at shifted momentum when SOC is gradually turned on by slowly ramping up the amplitude of the modulating GMF.This article reports our observation of a tunable SOC with equal Rashba and Dresselhaus contributions in a spin-1 F atom (with mass m). Here, μB is the Bohr magneton, gF is the Lande g-factor and Fx,y,z denotes the x-, y-, and z-component of spin vector F. Although the net impulse over one period is zero, the accumulated distance an atom moves depends on its spin state, which implies the atom acquires a spin dependent group velocity. Thus atomic spin and its center-of-mass motion  is coupled by GMF pulses. The origin for the synthesized 1D SOC can be understood more straightforwardly when we consider the extreme case where each period contains a pair of two opposite GMF pulses of impulse ±kso capping the ends of free evolution over time T. These two pulses enact a unitary transformation, which displaces the canonical momentum by a spin-dependent quantity, i.e., Heff is given by  of the bias field used for selecting the 1D GMF from a 3D quadrupole magnetic field (see c1 and c2 terms on the rhs of q can be further tuned to zero or negative by an off-resonant dressing microwave fieldωmod = 2π/T is far greater than the trap frequency.where ield see . The c1 87Rb BEC of 1.2 × 105 atoms in state π) 4 MHz and (2π) 2.34 kHz, respectively (see ωmod for the GMF is (2π) 1.0 kHz unless stated otherwise. To generate a SOC strength kso = 1 kL = 8.0554 μm−1, where kL = 2πλL is the one photon recoil momentum at a laser wavelength λL = 780 nm, the required peak magnetic field gradient μm to minimize short-term magnetic field fluctuation during modulation  as kz = c1ksomF for the state c1ksomF. According to the adiabatic theorem, if the ramp of kso is slow enough, atoms will follow the ramp and stay at the shifted minimum. In this set of experiments, atoms are prepared at the initial spin state of  π/2 pulse to the state T. The modulation amplitude is then ramped up to a final value within 200 ms. After turning off the optical trap, we measure the momentum for each spin component. We find good agreement with theoretical predictions as shown in kso is ramped up from 0 to 4.9 μm−1 in 100 ms and then back to 0 in another 100 ms. We find atomic center-of-mass momentum returns to 0 without noticeable heating. We also check the dependence of c1 on the modulation frequency ωmod and find that c1 essentially remains a constant as long as As a second confirmation, we observe that the atom’s minimum energy state is adiabatically adjusted to a finite none-zero momentum The results of As mentioned before, one of the major heating mechanisms for the Raman scheme is photon scattering from the Raman laser. For different alkaline metal atoms, the situation varies significantly. A list of all alkaline metal atom data are shown in π) 100 Hz and the mean field interaction energy is around (2π) 200 Hz. When modulated at ωmod = (2π) 1.0 kHz, heating is found to be moderate and acceptable for the reported experiments, based on the observed condensate life time. To measure the life time, we adiabatically increase the SOC strength to prepare atoms into an equilibrium state from a initial spin state kso = 4.9 μm−1 corresponding to a recoil energy of 1.3 kHz, as shown in kso = 4.9 μm−1. The cloud radius is found to decrease with increasing modulation frequency, which confirms the expected heating suppression with increased modulation frequency. Thus enhanced performances of the GMF scheme is expected if our experiments can be carried out with atomic chip based setups, which routinely provide higher GMFs and faster modulations58As atomic spontaneous emission is absent in our experiments, the most likely heating mechanism comes from parametric processes associated with the temporal modulation. To minimize parametric heating, we modulate the GMF far away from the characteristic frequencies of our system. The typical trapping frequency is about  optical access, MOT collected from background atoms are magnetically transported 10 cm to a location 8 mm away from the inside wall of the glass cell. They are first RF evaporative cooled in a hybrid trap consisting of a magnetic quadruple trap and a crossed optical dipole trap for 5 seconds. The crossed dipole trap derives from two 1064 nm laser beams (with 1/e2 Gaussian diameter 120 μm) propagating along x- and z- directions, respectively. The magnetic quadrupole field gradient is then ramped down to transfer atoms to the crossed dipole trap. Condensation occurs after a final evaporation by ramping down the power of the crossed dipole trap in 3 seconds. At the end of the final evaporation the crossed dipole trap frequencies are 5 atoms is produced every 40 seconds. To minimize heating from the near-resonant driving of the modulating GMF, we further ramp down ωz to 2π × 31.8 Hz in 500 ms after BEC production, which reduces ωx and ωy respectively to 2π × 74.6 Hz and 2π × 67.5 Hz.Atomic z-direction is simultaneously turned on in order to maintain atoms in z-direction.Three pairs of Helmholtz coils are used to control the homogeneous bias magnetic field. While transferring atoms from the hybrid trap into the crossed dipole trap, a 0.7 Gauss bias field along π) 1.0 kHz. The radius for the gradient coils is 15 mm. The two coils are separated at an inner distance of 36 mm. Each coil consists of 12 turns of winding and produces an inductance of about 10 μH. The gradient coil size is much larger than the 120 μm beam waist of our dipole trap, which produces a homogeneous gradient field inside the crossed dipole trap. The coils are small enough to ensure fast and strong GMF modulation. The current for the gradient coils is regulated by a home made fast (10 μs rise time) and precise (100 ppm) linear bipolar current controller, whose phase compensation is carefully analysed and tuned for stable running with the inductive load. The gradient coil is mounted on a 3D low magnetic translation stage for precise alignment of the gradient coils. The center of the gradient field is aligned within 50 μm with the BEC, which is found to be crucial for minimizing short term bias field fluctuations during GMF modulation.A pair of small anti-Helmholtz coils is used to modulate the GMF with a modulation amplitude up to 100 Gauss/cm at a frequency of .


More than 100 naturally occurring modified nucleotides have been found in RNA molecules, in particular in tRNAs. We have determined molecular mechanics force field parameters compatible with the CHARMM36 all‐atom additive force field for all these modifications using the CHARMM force field parametrization strategy. Emphasis was placed on fine tuning of the partial atomic charges and torsion angle parameters. Quantum mechanics calculations on model compounds provided the initial set of target data, and extensive molecular dynamics simulations of nucleotides and oligonucleotides in aqueous solutions were used for further refinement against experimental data. The presented parameters will allow for computational studies of a wide range of RNAs containing modified nucleotides, including the ribosome and transfer RNAs. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. Post‐transcriptionally modified nucleotides are very common in ribonucleic acids (RNA), with approximately 25% of the nucleotides in eukaryotic tRNAs being modified. Of the 112 naturally occurring modified nucleotides that have been described,Lys and tRNALeu leads to reduced translation of the corresponding codons, and hence insufficient mitochondrial protein production.RNA modifications have been implicated in the development of a number of human diseases, mostly related to energy metabolism  but also in various tumors and neurodegenerative diseases.7G) in position 46, and the 5‐methyluridine and pseudouridine (Ψ) in positions 54 and 55, are responsible for local structural folding and flexibility for an individual tRNA.Trp cause stop‐codon read‐through.Modifications add to the RNA structural repertoire by allowing specific interactions contributing to well‐defined three‐dimensional (3D) structures. Such structures often have special functions such as UV sensing and are involved in a range of biological phenomena ranging from regulation of cellular processes while sensing the cell's metabolic stateMolecular simulation and modeling methodsab initio quantum mechanical (QM) data, and then compared results from MD simulations using the initial parameters to experimental data for nucleosides, and oligonucleotides for further refinement and validation; it should be noted that in comparison to the common nucleotides , there is much less experimental data available for validation of the large number of RNA modifications.In the present work we develop CHARMM compatible force field parameters of similar quality as those for the standard nucleotides, including partial atomic charges and bonded parameters, with special attention to the glycosidic torsions, for 112 naturally occurring modified nucleotides. The parametrization approach uses the same methodology as for the additive CHARMM36 Nucleic Acid Force Field (NA36),The potential energy function used in the CHARMM force field is based on the following equation:iq and jq are partial charges of two particles separated by distance ijr, 0ɛ is the vacuum permittivity, and ε is the relative permittivity, generally assigned a value of 1 for explicit solvent simulations. The vdW energy is described by a Lennard‐Jones potential (LJ term) where Rijmin is the distance between the two particles at which the potential reaches its minimum, and ijɛ is the depth of the LJ potential well. The remaining sums are the bonded terms that represent bonds, valence angles and dihedral or torsion angles. For proteins, an extra 2D dihedral energy correction mapbK, θK, KUB and φK are force constants and b0, θ0, r1,3;0, and φ0 are equilibrium values. The dihedral angles are described by cosine functions, where ΦK, n and δ are the amplitude, periodicity and phase angle, respectively. In principle, n can be any integer and δ any value between 0° and 360°, but in the current CHARMM force field, n is only taken to be 1, 2, 3, 4 and 6, and δ is either 0° or 180°. In addition, a given torsion angle may be treated as a Fourier series over a sum over 2 or more periodicities.The first two sums, the so‐called non‐bonded terms, represent electrostatic and van der Waals (vdW) interactions. Here The atom types were mainly taken from CGenFFhttps://cgenff.paramchem.org) that performs atom typing and assigns parameters and charges to new compounds based on analogy.In brief, initial guesses for the parameters of representative model compounds (see “Model compounds” below) were generated using the CGenFF program,Partial atomic charges were optimized targeting interactions between the model compound and individual water molecules, as well as the dipole moment of the model compound. The peripheral atoms in the QM minimized model compound were probed by individual water molecules in idealized linear orientations. Only monohydrates were studied and we used several different rotations of the water molecule around the interaction axis: for polar atoms, the complex was calculated every 60° of water probe rotation, and for nonpolar atoms, every 90° or 180°. The model compound‐water interaction distances were then optimized and the interaction energy calculated. Before comparing with the MM calculations the QM HF/6‐31G(d) interaction energy was multiplied by 1.16 for neutral polar compounds and the minimum interaction distance was offset by −0.2 Å for all polar interactions,ab initio minimum interaction energies, the RMS deviation between ab initio and empirical minimum interaction distances, the absolute difference between the norms of the empirical and ab initio dipole moments, the angle between the empirical and ab initio dipole moments, and a term associated with restraints on the charges. The latter term was specifically introduced to prevent large deviations from the starting guess for charges. The dipole moments were calculated at the HF/6‐31G(d) level, and were not scaled in the charge optimization. Charges of symmetrical atoms were constrained during optimization to have identical values. Charges of aliphatic groups were not optimized, in accord with the standard CHARMM method. For example, all methyl groups have a charge of 0.09 |e| on protons. We also reiterate that the LJ parameters were not subjected to optimization.The charge optimization was performed with a C++ program based on the Powell and Amoeba minimization algorithms from Numerical Recipes.The molecular dipole moment, which is determined by the charge distribution, was used to provide additional target data for optimization of the atomic charges. Only the neutral compounds were considered here; for charged molecules, the dipole moment is ill‐defined, and the net charge, which is the lowest non‐zero electric moment, is the leading contribution to electrostatic interaction instead of the dipole moment. The dipole moment refers to the permanent moment in vacuum at the HF/6‐31G(d) level of the QM MP2 optimized conformation. Since in additive force fields the molecular polarizability is not explicitly taken into account, to reproduce the electronic distribution in aqueous solution the MM estimated dipole moment is typically overestimated by 20% to 50% with respect to the QM values for small polar compounds.Parameters for the bonded terms described by harmonic potentials , as well as for the nonrotatable dihedrals in aromatic rings , were determined as follows. The equilibrium values of the MM parameters were adjusted until the RMSD between the MM and the optimized QM geometries could not be reduced significantly. The force constants were determined by calculating the molecular vibrational frequencies; the contributions of the internal coordinates to the vibrations of the model compound were defined by potential energy distribution (PED) analysis using the internal valence coordinate system.3 carbons were scanned over an interval of ±(60°–90°) around the energy minimum in 3° increments. Each conformation for the MM calculations was extracted from the QM scan and minimized with a harmonic restraint force constant of 104 kcal/mol/radian2 on the target torsion. The MM dihedral parameters were optimized to achieve a minimum deviation between the QM and MM surfaces in the lower energy regions . This dihedral optimization is sensitive to all the other parameters, thus when any atomic charge or bonded term was modified during subsequent testing, the related dihedral parameters were reevaluated.Dihedrals can be considered in two classes. Stiff dihedrals, such as torsions about aromatic or conjugated bonds, were optimized based on vibrational analysis. The other class includes low‐energy barrier rotatable dihedrals that may undergo large fluctuations during simulations. The treatment of this class of dihedral is crucial to the quality of a force field in reproducing conformational properties. Potential energy surface (PES) scans were performed on these torsions, in which acyclic torsion angles were scanned over 0°– 360° in 5° increments, and ring torsions involving spSince the PES contains contributions from all the energy terms, rather than just the dihedral term itself, the resulting dihedral parameters play a role in accounting for limitations in the overall form of the energy function with respect to the change in energy as a function of conformation. Thus, it is common that optimization is performed on low‐penalty dihedral parameters obtained from the CGenFF program. For example, the ideal parameters for the same dihedral between different ring systems will typically differ due to different contributions of the nonbond interactions to the PES. However, given that the same dihedral parameters, based on identical atom types defining the dihedral, cannot be optimized specifically for each model compound in the present study, it is necessary to compromise, which is often done by selecting a model compound for that parameter that is representative of all the compounds that contain that term. Typically, a simplified model compound is designed that contains only the necessary functional groups related to the target dihedral being optimized by substituting specific functional groups on an individual nucleotide by a methyl group or hydrogens. This approach was applied to the 5‐substituted uracils, N4‐substituted cytosines, 7‐substituted deazaguanines, and N6‐substituted adenines, where each group has diverse side chains but identical base ring systems. For example, in the case of the C5‐O7 bond in 5‐substituted uracils, the functional groups in the side chain often interact with O4 in the base Fig. , impactiTo optimize the C5‐O7 dihedral in 5‐carboxymethoxy uracil (OAU and others), methoxylbenzene  was the model compound, and the optimized C6‐C5‐O7‐C8 dihedral parameters were transferred to OAU. While the atom types of C6‐C5‐O7‐C8 in bzmo are slightly different from those in OAU, this allows the generalization of one set of parameters to a family of analogs. Whenever a conformational correction is required for an individual molecule, only the dihedral term unique for that molecule (e.g. C4‐C5‐O7‐C8 for OAU) is updated and the universal dihedral term  is kept unchanged.In the charge optimization, the model compounds for the modified bases were built with a methyl group replacing the ribose. The net charge of this methyl was set to zero to maintain an integer charge for the base, consistent with the CHARMM strategy of using modular building blocks. Modified bases with extra rings or flexible side chains were further broken down into several parts (e.g. side chains and base heterocycle) to avoid confounding intramolecular interactions that may interfere with the transferability of the parameters . If the modification had multiple protonation states and/or tautomers, the physiologically dominant state was treated as the default species. For example, the primary and secondary aliphatic amines had the protonated state as the main species, and the carboxylate was in the ionized, negatively charged state; other accessible states were included in the force field as shown in the Supporting Information SDD.3D structures of modified nucleosides were taken from Aduri et al.‐O‐methylnucleotides and dihydrouridine. The modified nucleotides including their designation, and tautomer names as well as the 2D structures are in Table S1 in the Supporting Information and Figure We use three types of names for the modified nucleosides: the IUPAC common name, the symbol used in the text, and the three‐letter code used in the force field toppar files. The symbol designations are consistent with the RNA Modification Database, which have been widely accepted in the literature. In most cases, the three‐letter codes adopted the AMBER convention‐O‐methyl carbon was named CM2 as generally occurs in the PDB, and the 2′‐O‐ribosylation atom names end with “A” for ribosyl atoms and “X” for phosphate atoms. Since there is currently no standard nomenclature for modified nucleotides, users are advised to check and make sure the nucleotide and atom names are consistent with the topology file.Atom names from the PDB were used when possible, but significant differences are present in a number of nucleotides. In these cases, the PDB nonunique atom names were changed and we used the following numbering scheme: For the bases, atoms in the substituent side chain were numbered starting from #7 in pyrimidines and from #10 in purines, with the number increasing along the chain of nonhydrogen atoms; carbonyl or hydroxyl oxygen and all hydrogens were given the same number as the heavy atom to which they are attached. All backbone ribose atom names end with a prime as is done in NA36. The 2′−5 Hartree/Bohr (Opt = tight) for structural optimizations. Geometry optimizations, frequency and potential energy calculations were performed with the MP2 method, while for water‐compound interactions (except for thio‐compounds) the HF method was used. The basis set 6‐31G(d) was applied for neutral and cationic compounds, and 6‐31+G(d) for anions. Dipole moments were the HF/6‐31G(d) values based on the MP2/6‐31G(d) geometries. Empirical force field calculations were performed with CHARMM.−5 kcal/mol/Å. In PES a harmonic restraint with a 104 kcal/mol/radian2 force constant was applied on the target dihedral. The PED of vibrational analysis was carried out using MOLVIBAll QM calculations were performed with Gaussian09 , with an RMS force convergence criterion of 10anti, north conformations. Oligonucleotides were built using Maestro9.3 in an A‐RNA conformation, and modifications were generated in an energy minimum conformation using CHARMM while keeping the sugar pucker and glycosidic torsion unchanged. In all cases the 5′ and 3′ termini of oligonucleotides were terminated with a hydroxyl group. Simulations were performed in rhombic dodecahedral solution boxes using the CHARMM‐modified TIP3P water model+ ions were added to achieve charge neutrality by randomly substituting the appropriate number of water molecules. After the solvent box setup, a harmonic restraint with a force constant of 80 kcal/mol/Å2 was applied to the solute nonhydrogen atoms, and 100 to 300 steps of ABNR minimization was performed.Coordinates for the nucleotides used in MD simulations were initially generated in In production simulations, all harmonic restraints on solute atoms were released. The SHAKE algorithmφ) about a rotatable bond is always defined using nonhydrogen atoms unless the terminal atom is hydrogen. When the first atom eclipses the fourth atom (φ = 0°) the dihedral is cis, and when φ = 180° the dihedral is trans. The glycosidic torsion (χ), which is about the base‐ribose linkage, is defined by the dihedral O4′‐C1′‐N1‐C2 (pyrimidine), O4′‐C1′‐N9‐C4 (purine) or O4′‐C1′‐C5‐C4 (pseudouridine), and its conformation is denoted as anti for 170° < χ < 300° and as syn for 30° < χ < 90°.The dihedral (P) which is a combination of five ring torsions. Thus the ribose pucker is denoted by the pseudorotation quadrants, which are north (315° < P ≤ 45°), west (45° < P ≤ 135°), south (135° < P ≤ 225°), and east (225° < P ≤ 315°). Since in unmodified RNA the puckers are mainly found in the north (P ≈ 18°) and south (P ≈ 162°) quadrants,C3'endo (270° < P ≤ 90°) which includes north, and C2'endo (90° < P ≤ 270°) which includes south. In QM PES, the furanose was kept in C3'endo by restricting C4′‐O4′‐C1′‐C2′ = 0.0°, and in C2'endo by restricting C3′‐C4′‐O4′‐C1′ = 0.0° as previously described.The pucker of a five‐membered ring is defined by the pseudorotation phase angleR) between two glycosidic nitrogen atoms, the pseudo dihedral (Φ) formed by two base‐axis atoms, i.e. N1‐C4 of pyrimidine (Y) or N9‐C6 of purine (R), and the angle (Θ) between normal vectors of the two bases.R ≤ 6 Å, (Φ0 – 40°) ≤ Φ ≤ (Φ0 + 40°), and Θ ≤ 40° or Θ ≥ 140°, where Φ0 is the value when two bases are stacked in the ideal A‐RNA geometry .Base stacking was described using three geometric terms: the distance . These molecules were subjected to charge, bonded, and dihedral parameter optimization.For the parameter optimization the nucleotides were split into smaller model compounds, based on two structural classes. The first class includes bases with a simple modification  and aromatic or conjugated molecules without a long aliphatic side chain. Examples in this class are the bases of inosine, 4‐methylcytidine, 7‐methylguanosine, 2‐thiouridine, pseudouridine, and wyosine, as well as the scaffold of a group of complicated modified bases (e.g. 7‐deazaguanine and 2‐aminocytosine). These molecules were subjected to optimization of the charges and bonded energy terms and, in general, did not require any dihedral PES scans. The second class contains flexible chains that have been separated from the bases  and any nonaromatic bases and ribose , six on O2 and N3 (water rotated 60° around the Hw···O2/N3 axis), two on H5 and H6 (water rotated 90° around the Ow···H5/H6 axis), and one on H41 and H43. Interactions with H42 were excluded because the interacting waters were very close to N3, resulting in an unfavorable interaction. Thus, a total of 21 water‐model compound complexes were used in the charge optimization of 4MC (Table 51 in Supporting Information SDD 1.17).The atomic charges were optimized targeting water‐model compound minimum interaction energies and distances along with dipole moment magnitudes and orientations. We illustrate the charge optimization protocol with N1, N4‐dimethylcytosine  . For 4MC three water probes were used on H4  were calculated as ΔE=Ecomplex−E4MC−Ewater and R=r4MC−rwater, where rx represents the coordinates of the two directly interacting atoms. As previously described,w···H5/H6/H41,3 interactions were excluded).In each HE = 1.16ΔEQM – ΔEMM and ΔR = RQM+Roffset– RMM) between MM and QM calculations were fully minimized, yielding an RMS difference of 0.20 kcal/mol for energies and 0.10 Å for distances. For comparison, the results calculated using initial charges gave RMS differences of 0.54 kcal/mol and 0.10 Å for the interaction energies and distances, respectively. Consistent with previous CHARMM parametrization effortsThe starting atomic charges were generated by the CGenFF program using the ParamChem website. The atomic charges were then adjusted iteratively until the interaction energy and geometry differences  was obtained.μQM) of A, G, and U is directed from N9/N1 to H9/H1, while in C it is in the opposite direction, from H1 to N1. When the H9/H1 is replaced by a methyl group, the methyl group had a small positive charge in the QM calculation, so the ǁμQMǁ remained largely unchanged for the four bases; slightly increasing for A, U, and G and slightly decreasing for C  were transferred directly from CGenFF to the modified nucleotides. Thus, there were only a limited number of bonded parameters for optimization for each model compound. For this reason there are a few angles with differences >3° in the 4MC case (Table 185 in Supporting Information SDD 2.9). Table The parameters of flexible dihedrals were determined using PES. Here we mainly focus on the determination of glycosidic torsions and the reproduction of nucleoside conformations. The fitted energy surfaces of all torsions are in the Supporting Information, and additional technical details concerning determination of torsion parameters can be found in the previous CGenFF publications.χ) represent an interesting situation as they contain atom types from two different sets of initial parameters; NA36 for the sugar and CGenFF for the bases. In NA36, there are unique χ parameters for each nucleoside, while in CGenFF there are only two sets (one for A/G and one for C/U). The χ torsion parameters in NA36 were adjusted accurately for the anti and then the syn conformations, as required to treat the conformational properties of oligonucleotides in condensed phase simulations.χ parameters from CGenFF we first calculated the PES using both NA36 and CGenFF for a number of model compounds , showing the CGenFF parameters to be consistent with NA36, especially for the minima and barriers. Furthermore, when both sets of parameters were used in nucleoside simulations in solution, a significant difference only occurred with uridine , with the population of the C3'endo sugar pucker of uridine being larger than that obtained in NMR experiments.C3'endo) conformation.χ parameters. Accordingly, the χ parameters of CGenFF were adopted for the modified bases.The glycosidic dihedrals , have new χ parameters and optimization was necessary. The model compounds for χ parametrization included the whole base (except for lysidine or agmatidine whose long side chain was excluded), whereas the ribose was represented by tetrahydrofuran (with the same atom numbering and atom typing as ribose), the simplest model to mimic the ribose pucker. The χ torsions were scanned with the furanose restricted in both C2'endo and C3'endo puckers (Supporting Information SDD 3.58–3.62). The parameter determination combined with the conformational analysis is discussed in the next section.Most modifications in the base do not explicitly change the atom types about the glycosidic bond so the χ torsions, dihedrals of ribose 2′‐O‐modifications also involve atom types from both NA36 and CGenFF. The ribose ring atoms use NA36 atom types and the atoms in the substituent, including O2′ and CM2, use CGenFF atom types. The 2′‐O‐ribosylation is bulky and restricts the conformational diversity of the ribose; optimization of the 2′‐O‐ribosyl linkage is not discussed here, but shown in the SI. The dihedral about the C2′‐O2′ bond of 2′‐O‐Me was determined with both the C2′endo and C3′endo furanose puckers; the conformational details of the four nucleosides Am, Cm, Gm, and Um are discussed below.In addition to the χ torsion is often coupled with the sugar pucker (P), mediated by the O5′ group.χ parameters. In nucleosides that adopt the canonical χ parameters small modifications of atomic charges in the base were made to correct deviations from experimental conformations, and one example illustrated below is ac4C. The conformational effect of 2′O‐methylation will also be discussed since it is a very frequent modification in nucleic acids. Finally an example of N‐methylated bases will also be described to show that in many cases fitting gas‐phase QM PES is adequate to yield good agreement with experimental conformational properties. These nucleoside 2D‐structures are shown in Figure The glycosidic torsion is very important for structural properties of nucleotides, and contributes to base pairing and stacking. At the nucleoside or nucleotide level, the χ torsion has been reported as anti,C2'endo pucker, and also imparts flexibility to the local RNA structure, thereby destabilizing the A‐form helix.χ torsion had similar barrier heights and positions of the minima for both the C3'endo and C2'endo puckers , shifts the base outward from the ribose ring around the O4′‐C1′ bond, and shifts the χ torsion to higher values.In simulations of the dihydrouridine nucleosides the ion Fig. a, indicaPES Fig. a. The sundo Fig. b. HoweveΨ induces more C3'endo in its neighbors and enhances the rigidity of the local structure, and thus stabilizes the A‐form RNA architecture.Ψ is like a uracil flipped 180° around the N3‐C6 axis, and C5 becomes the linkage atom  and deprotonated (enol) zwitterionic states, its biochemical functions are mostly related to the protonated state.7G keeps the same configuration as guanine, in contrast to the N1 deprotonated state, so that hydrogen bonding and stacking patterns in tRNA are not disturbed.7G and its base‐alkyl derivatives.7‐methylguanosine is a common nucleoside, especially in tRNA, and it is also the 5′‐cap of eukaryotic mRNA.anti) around 180° and barrier heights in both furanose puckers  in the crystal structure.west pucker (P ≈ 50°) was related to the syn‐C3'endo conformation, while it was still north (P ≈ 18°) in anti. Similar to the pseudouridylation on U, the 7‐methylation on G induces a strong correlation between anti and C3'endo  and agmatidine (C+) are hypermodified cytidines with the 2‐carbonyl replaced by lysine and arginine, respectively. They are mainly found in the wobble position in the antcodon of tRNAIle where they are paired with A instead of G, and thus tRNAIle can read the Isoleucine codon AUA rather than the initiator codon AUG.χ torsion parameters. To avoid confounding interactions between the amino acid chain at the 2 position and the rest of the molecule, the side chain was replaced by a methyl group on N2 (Supporting Information SDD 3.61) for the PES scan of the torsion O4′‐C1′‐N1‐C2. However, the bulky methyl substitution (with the methyl group toward the furanose) still contaminated the potential energy along the χ torsion. Rotating the 2‐methylamino group 180° introduced an interaction between the amino hydrogen and furanose oxygen, so this did not alleviate the problem. Considering that in practice the k2C and C+ conformations will be very restricted, and that electrostatic attraction and steric repulsion of the 2‐position side chain will dominate the χ conformational sampling rather than the χ torsion, χ parameters were optimized directly targeting the PES of the 2‐aminomethyl analog.Lysidine , O3′ (190°–280°) and O4′ (305°–360°), with Base dominating in solution.‐O‐methylation is a very common modification, and it occurs in dozens of different nucleotides. This modification is often considered to increase the north pucker.The 2′‐hydroxyl group, which is the major chemical difference between DNA and RNA, increases the Base 30°–°, O3′ . The torsion C1′‐C2′‐O2′‐CM2 of the methoxy group was scanned with the sugar in both C2'endo and C3'endo conformations. In the QM PES the energy patterns along the 2′‐OMe torsion are similar in both puckers ; the second minimum was around 85° (Base) and ∼1.5 kcal/mol higher, and the third minimum, which is 4 to 5 kcal/mol higher in energy, was around 300° (O4′). The first two conformations can also be denoted g+ and g‐ (defining the torsion as H2′‐C2′‐O2′‐CM2), respectively. The barrier across O4′ was ∼3 kcal/mol higher in C3'endo than in C2'endo.To determine the parameters of the 2′‐OMe torsion, a similar model as for the Base orientation in pyrimidines, and alternatively as Base and O3′ in purines , compared with the corresponding 2′‐OH nucleotides, but the effects on their neighbors were less significant, and also different between purines and pyrimidines. For the 3′ A following a 2′‐OMe pyrimidine C3'endo increased while after a purine some amount of C3'endo was lost. In contrast, the 5′ A preceding a 2′‐OMe purine increased C3'endo, while the 5'A preceding a pyrimidine decreased C3'endo puckering. Furthermore, stacking on both sides was increased with a central 2′‐OMe purine, but for pyrimidine only stacking with the 3′ A was increased and stacking with the 5′ A even decreased. Stabilization of the 3′ neighbor is expected since the C3'endo enhancement for the 3′ nucleotide was reported in dinucleotides containing Cm,Ψ. Thus, in short and single strands, thermal motion might mask its effect. Also structural stability is sequence dependent. For example, the 3′ A following Am and Gm had less C3'endo but better stacking, which indicates that the base had a bigger influence than the ribose. We have not been able to further elucidate a detailed mechanism based on the current models.The four central 2′‐OMe nucleotides increased their Base conformation, because of the steric repulsion of the bulky methyl group with the phosphodiester backbone. As occurs in nucleosides, Base was correlated with C3'endo pucker, hence a 2′‐OMe nucleotide prefers north pucker in oligonucleotides more than a ribose nucleotide, whose 2′‐OH torsion is able to rotate to induce both A‐form (Base) and noncanonical (O3′) structures in oligonucleotides.Base orientation as well as the C3'endo conformation of the sugar, analogous to what occurs with a 2′‐OMe.The 2′‐OMe torsion in oligonucleotides is only compatible with the E. coli elongator tRNAmmet anticodon, which matches only one codon (AUG) and prevents misreading of AUA, an isoleucine codon, in contrast to unmodified cytidine which reads both AUG and AUA.4C the substituted acetyl group shares the delocalized electrons with the C4‐N4 bond and is conjugated to the pyrimidine ring, so the acetyl group is coplanar with the ring. The crystal structure reported the 4‐acetyl group to be in a trans orientation to N34C can form a WC base pair with a G. Our PES of the torsion N3‐C4‐N4‐C7 in vacuum (Supporting Information SDD 2.28) and a previous QM calculation using density functional theorycis and trans was ∼10 kcal/mol. However, this difference had to be increased to >14 kcal/mol in order to obtain trans in solution simulation, indicative of a significant solvation effect. Conformations where O7 and N3 would not come close in vacuum were stabilized in aqueous solution by a water bridge. At the same time, the reduced electrostatic attraction between O7 and H5 further counteracts the trans preference. In short, the energy barrier for interconversion between trans and cis is lowered in solution. This effect is similar to the 2′‐OH orientation in NA36,Base/O3′ energy minimum in 2′‐OMe. We have not found any published data that would allow an accurate determination of the force constant of this torsion. As a general strategy, we made the sampling of both conformations almost equal . This is observed in NMR experimentAnother important structural feature of ac4C is the 4C, the C4‐N4 torsion in N4‐methylcytidine (m4C) showed a 20:1 preference of being cis to N3 in solution NMR , and the activation enthalpies of converting from cis to trans were 11 to 18 kcal/mol.4C where the energy barrier is higher than 12 kcal/mol and the difference between the two minima is 1.5 kcal/mol . Note that although the rotation of C4‐N4 bond in the two directions is equivalent, the barriers in the figure are different, as in the QM scan the sp2 N4 distorts during rotation out‐of‐plane and assumes a pyramidal configuration; thus the orientation of H4 influences the energy, which is lower when H4 is directed toward N3 and higher when H4 points toward C5. This artifact was also found in similar exocyclic N‐methylations, for example N2‐methylguanine  and N6‐methyladenine . The conformational distribution from the m4C nucleoside simulation was consistent with the PES prediction . For m2G the minimum was trans to N1 which is correct for WC base pairing, and though m6A had a similar minimum as m4C (Fig. 6A.This N‐C torsion disturbance occurs in other exocyclic mono The present study involved a comprehensive development of empirical force field parameters for the 112 known modified ribonucleotides. The parametrization was performed to be consistent with the philosophy behind the development of the CHARMM additive force field, such that the quality of the parameters will be compatible with the other components in the CHARMM force field. The parameters were optimized targeting QM data and further refined against experimental data when possible. Notable was the optimization of the partial atomic charges based on the reproduction of water‐model compound minimum interaction energies. Starting from the partial atomic charges obtained from the CGenFF program, additional optimization was performed using a least squares fitting approach that always reduced the RMS difference for each model compound. We note that quality of the optimized charges is mainly determined by the initial guess. In this work we started from the CGenFF charges, which were already optimized targeting similar compounds. To further ensure that the optimized charges do not deviate strongly from the CGenFF charges restraints were applied on the charges during the charge optimization. Given the overall improvements obtained in the interactions with water and in the dipole moments, this approach is recommended for fine tuning of charge distributions when extending CGenFF to new species.Concerning the intramolecular parameters, the dihedral terms in particular were carefully optimized to reproduce reasonable conformational properties based on an extensive set of PES scans. Notable is the quality of the new glycosidic and 2′‐OMe torsions and selected sugar torsions that were fine‐tuned based on MD simulations to achieve good agreement between simulations and experiments. Given the care taken in the force field optimization, in addition to extending the CHARMM force field to modified nucleotides, the parameters developed in this study will be included in the training set of the CGenFF program, significantly expanding the coverage of the force field.Ψ, m7G and 2'OMe, and destabilized by D. In addition to the previously characterized χ/P correlation for canonical nucleic acids,anti/C3'endo and Base/C3'endo were found for Ψ and m7G and 2'OMe nucleotides, respectively, thereby illustrating how they stabilize RNA structures.Emphasis was placed on the quality of some of the more common modified nucleotides, including dihydrouridines, pseudouridines, 7‐methylguanosine, and 2′‐OMe nucleotides, whose conformations were shown to be consistent with experimental data. Important properties include that the A form of RNA can be structurally stabilized by χ or 2'OMe torsion parameters were fine‐tuned in a number of cases. In cases where the parameters of the ribose were identical to canonical nucleic acids, the χ torsion and sugar pucker could not be optimized, which indeed provided a challenge. Although we assumed that base modifications would not have a large effect on backbone conformational properties, there are known relationships between base modifications and sugar pucker.C3'endo for uridines whereas electron‐donating 5‐substitutions increase C2'endo. In this force field all 5‐substituted uridines use the same χ and pucker parameters as U. In this case to improve the sugar pucker small changes in the base charges were made. However, this is risky as base charges were optimized targeting water interaction and changing them significantly would adversely affect the behavior in solution. Thus, compromises were required that were very carefully assessed based on available experimental evidence. An example is ac4C whose C3'endo population was improved by adjusting the base charges, leading to better agreement with NMR data.Initial parameters were obtained from NA36, Carb36, and CGenFF, with parameters not previously in the force field assigned values by analogy using the CGenFF program. Subsequently, only parameters that were not previously in the force field were subjected to optimization, with new parameters with low CGenFF penalties not subjected to additional optimization with the exception of selected dihedral parameters. For example, the 4C, where without the revision based on simulation, the conformation from the force field would have been opposite to the experimental observation. Therefore if experimental data are available, it is always worth calibrating the associated parameters based on explicit solvent simulations.The parametrization of base torsions was relatively straight forward due to these terms often being chemically specific for a few molecules. Nevertheless the difficulty here is the elusive solvent effect on torsions involving polar atoms. This led to discrepancies between vacuum QM energies and solution MD simulation conformational sampling in acSupporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.


The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na A mulations .+ and Ca2+ ion channels without needing to treat them as a special case. Hence the competition for space is now modulated by the volume defined by these pore wall spheres. Implicit in using such a volume to modulate the competition for space is that the spheres representing the solute ions also have sizes that correspond to the atomistic structure   and [B] are the sum of hydration state subpopulations. We can calculate these relative populations (see A⋅X] is the sum of the interactions of hydration state subpopulations of A at some point within the SF (X).The major output of the CSC MC simulation is a population profile of ions within the simulation cell, and in particular within the SF. The separation of timescales between hydration and cation passage for Naions see  using thB ⋅ mH2O and A ⋅ nH2O decrease by several orders of magnitude as the cation hydration number, m and n, decreases resulting in 〈[(B ⋅ mH2O) ⋅ X]〉 and 〈[(A ⋅ nH2O) ⋅ X]〉 rapidly converging to zero due to the limits of finite sized simulation. On the other hand, only values of m and n, that allow B ⋅ mH2O or A ⋅ nH2O to fit within the SF and therefore pass through the ion channel will have non-zero contributions to [B ⋅ X] and [A ⋅ X]. We therefore perform preferential sampling of the critical hydration states by ignoring values of m and n for which the values of 〈[(B ⋅ mH2O) ⋅ X]〉 and 〈[(A ⋅ nH2O) ⋅ X]〉 will be zero. This involves determining the largest hydration numbers, ⌈m⌉ and ⌈n⌉, that allows the hydrated cation to fit in the SF. These maximum numbers and consecutively lower values of m and n which have populations within three orders of magnitude of the populations of ⌈m⌉ and ⌈n⌉ are the hydration states included in the final simulations.A complete model calculation would involve a simulation containing all hydration states. In practice two factors limit the practicality of such simulations. Firstly, the sub-populations A]bulk. This enhanced sampling of the critical hydration states then requires a rescaling factor of the ratio of the sum of the sub-populations used in the simulations to the full population of A to be applied:In these simulations the sum of the partially hydrated ions in the bulk is still that of the original  and [B ⋅ X], Figs A ⋅ X]min and [B ⋅ X]min) to the ratios in the bulk solution (for details see the supporting information):α values   + channes (NavAb ), a typiel KcsA , 47) and and+ cha (CavAb) , the onl factors  leads toα values  show qua+ channels. The hydration level of cations in the Na+ channels studied is in agreement with suggestions from recent X-ray [+ hydration state, (Na ⋅ 4(H2O))+, and the third K+ state, (K ⋅ 3(H2O))+. Thus, even though hydration states 4 and 3 are included in our simulations for both Na+ and K+, the (K ⋅ 4(H2O))+ cation is not present in the SF. This allows the value of 2O))+ has over (K ⋅ 4(H2O))+ in a real aqueous solution , leading to Na+ selectivity overall.A key finding is that our model reproduces selectivity in the bacterial Nant X-ray –15 and cnt X-ray , 16, 17 αsim,dehyd). (ii) The representation of the partially dehydrated cation as a sphere of a certain radius.We introduced a simple model of hydration that contributes two key factors into the calculation of selectivity: (i) The population of the partially dehydrated ions as set by their relative partial dehydration energies . The Ca2+αsim,hyd values . All selectivities are reduced when using the smaller dehydrated radii cations, with the key selectivity between Ca2+ and Na+ falling below the experimental value. This can be explained from knowing that selectivity decreases as volume increases [2+ ions can not enter the Na+ selective channels whereas fully dehydrated Ca2+ ions could enter the Na+ selective channels which would lead to (results not shown) these channels being predicted as Ca2+ selective. This shows that including atomistic detail in the SF must be matched with realistically sized hydrated ions.To test if using hydrated ions is required we compared these selectivities with ones from simulations with cations at their fully dehydrated radii  , 49 follH4+<Rb+) , 51 rathb+≊NH4+) , 53. Fro+ and Ca2+ channels is not present. The main attractive interaction is the interaction of the cations with the carbonyl oxygens, the geometry allowing up to eight atoms in the SF to coordinate with a single cation. This is represented in the CSC Hamiltonian only as an electrostatic interaction between the cation and the partial charge on the carbonyl oxygens. The ability of this attractive electrostatic interaction to mimic the attractive interaction inferred from the experimental results was evaluated by comparing simulations with different charges on the oxygens atoms in pore wall of the SF. When going from -0.1 to 0.0 . Terms omitted from the current model include non-electrostatic attractive forces, a large number of details of the protein structure outside the SF, the bulk dynamics of the protein and the membrane voltage [We have presented here a model that is specific to the needs of simulating the confined geometry of ion channel SFs within the CSC method. As in any model, ours has advantages and disadvantages. Some of these have been described in previous sections. In addition, a limiting factor we have found are the limited number of published experimental values for partial hydration free energies over the full range of cations used in biological studies Click here for additional data file.


III‐HS in oceanic conditions into bioavailable aquatic FeII forms, highlights the importance of river‐derived HS as an iron source for marine organisms. Consequently, such mechanisms are a vital component of the upper‐ocean iron biogeochemistry cycle.Humic substances (HS) are important iron chelators responsible for the transport of iron from freshwater systems to the open sea, where iron is essential for marine organisms. Evidence suggests that iron complexed to HS comprises the bulk of the iron ligand pool in near‐coastal waters and shelf seas. River‐derived HS have been investigated to study their transport to, and dwell in oceanic waters. A library of iron model compounds and river‐derived Fe‐HS samples were probed in a combined X‐ray absorption spectroscopy (XAS) and valence‐to‐core X‐ray emission spectroscopy (VtC‐XES) study at the Fe K‐edge. The analyses performed revealed that iron complexation in HS samples is only dependent on oxygen‐containing HS functional groups, such as carboxyl and phenol. The photoreduction mechanism of Fe For the first time, VtC‐XESX‐ray absorption near edge structure (XANES) and extended X‐ray absorption fine structure (EXAFS) techniques have previously been used to investigate Fe‐HS complexes in lakes and soils.1–15) containing FeII and FeIII oxidation states, and with different ligand scaffolds  were investigated as references. The model compounds reflected the possible oxidation states and coordination modes that might be contained within the aquatic HS samples. The XANES spectra and the first derivative of the model compounds are shown in Figure S2 (Supporting Information), while the edge energies based on the first maximum in the first derivative are tabulated in Table S1 (Supporting Information). The edge energies of the model compounds span a range of about 5 eV, with increasing edge energy upon increasing oxidation state and electronegativity of the first shell atoms. Figure S3 (Supporting Information) shows the normalized XANES spectra and the first derivative of HS samples  differ markedly in the XANES region compared to the HS samples.In Figure III to FeII was observed in NR samples exposed to diffuse natural sunlight on a daily basis  is shown in Figure III complexes with the marine siderophore aquachelin showed a similar timescale, with 70 % of FeIII reduced into FeII after 4.5 hours.Besides a shift in the Fe K‐edges of iron in the NR samples, a small shift and sharpening of the pre‐edge peak (transformation from a centrosymmetric to a non‐centrosymmetric site4 (FeIIIO6), 5 (FeIIIO6), and 13 (FeIIO6). The use of model compounds very similar to 4 and 5 were shown to give the best fitting results in an earlier study of HS.4, 52 % 5) and CB0 13 10 s  supports the previous assignment of FeIIIO6 coordination. As reduction proceeds in the NR and CB0 13 samples, the amounts of 4 (FeIIIO6) and 5 (FeIIIO6) decrease. By comparison, 13 (FeIIO6) increases and reaches its highest proportions in NR 3/21 (64 %) and CB0 13 60s (61 %). The reduced FeII species may possess an FeIIO6 coordination environment, either as [Fe(H2O)6]2+ and/or as lower‐affinity Fe‐HS complexes available to biota, as exemplified in Figure Linear combination fitting was performed to obtain quantitative information on the most likely first shell coordination modes in the photoreduced NR and CB0 13 samples. The normalized spectra of HS were fitted  to model compounds 5 (FeIIIO6), 6 (FeIIIO6), 9 (FeIIIO3N3), 10 (FeIIIO3S3), 12 (FeIIIC2N4), and 14 (FeIIN6) were measured and used to fit the study object, the high molecular weight fraction CB0 13. The model compounds contain different first shell neighbors and geometries that are likely to be present in CB0 13. The k3‐weighted EXAFS spectra are shown in Figure S5 (Supporting Information) and all compounds were fitted close to crystallographic values using FEFF1 (FeIIIO6), 4 (FeIIIO6), 5 (FeIIIO6), and 9 (FeIIIO3N3), leading to the satisfactory fit shown in Figure III in an octahedral configuration, and similar results have been described for Eliott SoilIII in the HS samples is confirmed once more, as the bond distance for FeII is longer (2.10 Å).III and small organic ligands,III coordination environments, such as carboxyl, hydroxy and catecholic groups. Attempts to include Fe−Fe paths gave unsatisfactory fits with oscillations in k‐space that are out of phase with the experimental data , 9 (FeIIIO3N3), and 10 (FeIIIO3S3), as well as HS samples CB0 13, SW, and SW std., to allow resolution of the first shell composition and to distinguish between oxygen, nitrogen, and sulfur ligands. The spectral Kβ2,5 ) and Kβ′′  transitions are given in Figure 9 (FeIIIO3N3) and 10 (FeIIIO3S3), respectively.VtC‐XES experiments were performed on model compounds  9 FeIIION3, and 14 (FeIIIO6) shows only one Kβ′′ line, which is attributed to the six oxygen atoms in the first shell. SW, SW std., and CB0 13 are very similar to 4 (FeIIIO6), unambiguously proving that iron is exclusively surrounded by oxygen atoms in the HS samples, which is an important complement to the XAS data. During transport from freshwaters to the ocean, while in the estuarine mixing zone, Fe‐HS complexes go through dissociation and reassociation of Fe‐HS of a lower molecular weight,Compound III‐HS complexes are continuously released from terrestrial surroundings into freshwaters, and are subsequently transported to open oceans where they are photochemically reduced to crucial bioavailable iron species that are sequestered by phytoplankton. Light reactions in humic‐rich freshwaters are avoided to a large extent since they contain a significantly higher concentration of light absorbing substances compared to oceanic waters.IIIO6; Figure III‐HS in the high molecular weight fraction, CB0 13, form mononuclear complexes  should be addressed to the authors.SupplementaryClick here for additional data file.


The steady two-dimensional stagnation-point flow and heat transfer past a permeable stretching/shrinking sheet with effects of viscous dissipation, Joule heating and partial velocity slip in the presence of a magnetic field is investigated. The partial differential equations are reduced to nonlinear ordinary differential equations by using a similarity transformation, before being solved numerically by shooting technique. Results indicate that the skin friction coefficient and the local Nusselt number increase as magnetic parameter increases. It is found that for the stretching sheet the solution is unique while for the shrinking sheet there exist nonunique solutions  in certain range of parameters. The stability analysis shows that the upper branch solution is stable while the lower branch solution is unstable. The flow and heat transfer of a viscous (Newtonian) and non-Newtonian fluid past a static flat plate is a classical problem and has been studied by many authors  flow is λ being a positive constant for the stretching sheet and λ a negative constant for the shrinking sheet. The constant applied magnetic field, parallel to the Consider a steady two dimensional, electrically conducting viscous and incompressible fluid over a permeable stretching/shrinking sheet coinciding with the plane The boundary conditions of Eqs. where b are positive constants. The momentum and energy equations In order that Eqs. where prime denotes differentiation with respect to where Substituting Eq. and the boundary conditions (4) becomeM is the constant magnetic parameter and where Physical quantities of interest are the skin friction coefficient Using variables (5), we obtainwhere et al.20et al.et al.We mention that there are several papers that have performed the stability analysis to determine which solution is stable and physically reliable, such as Merkint denotes the time. Based on the variables (5), we introduce the following new dimensionless variables:where so that (2) and (3) can be written asand are subjected to the boundary conditionsf(η) = f0(η) and θ(η) = θ0(η) satisfying the boundary value problem (1)–(4), we writeTo test the stability of the steady flow solution F and G are small relative to f0(η) and θ0(η). Solutions of the eigenvalue problem (16)–(18) give an infinite set of eigenvalues where along with the boundary conditionsf(η) = f0(η) and θ(η) = θ0(η) of the steady equations τ = 0. Hence F(η) = F0(η) and G(η) = G0(η) in (20) and (21) identify initial growth or decay of the solution (19). In this respect, we have to solve the linear eigenvalue problemThe solutions along with the boundary conditionsf0(η) and θ0(η) are determined by the smallest eigenvalue et al.F0(η) or G0(η). For the present problem, we relax the condition that λ we solve the system (23)–(25) along with the new boundary conditions It should be stated that for particular values of Pr and S, magnetic parameter M, power law stretching/shrinking parameter λ, Prandtl number Pr, Eckert number Ec, velocity slip parameter γ, and their effects on the flow and heat transfer characteristics are analyzed and discussed.The system of ordinary differential equations et al.M = 0 and γ = 0 for shrinking case (λ < 0). The stated data clarify the good agreement with the previous data which support the validity of our numerical results.fRex1/2 and the local Nusselt number Nux/Rex1/2 (heat transfer rate at the surface) for different values of the magnetic parameter M. These figures show that a unique solution exists for equations M is to increase the range of λ for which the solution exists. The skin friction coefficient and the heat transfer rate at the surface increase as the magnetic parameter M increases.To test the stability of the dual solutions, the stability analysis was performed to find the eigenvalues ε see Eq. . If the M = 0.1, Pr = 1, Ec = 0.5, S = 2 and γ = 0.1. From the figures we can see that the boundary layer thickness for the lower solution is thicker compared to upper solution. For a particular value of parameter, there exist two different profiles as presented in M increases. It was found that there exist dual solutions for the shrinking sheet while only unique solution for the stretching sheet. The stability analysis showed that there is an initial decay for the upper branch solution while there is initial growth of disturbance for the lower branch solution. Thus the upper branch is linearly stable and physically reliable while the lower branch solution is not.We have numerically investigated how magnetic parameters influence the effects of viscous dissipation, Joule heating and partial velocity slip. The skin friction coefficient and heat transfer rate at the surface increase as magnetic parameter How to cite this article: Yasin, M. H. M. et al. MHD Stagnation-Point Flow and Heat Transfer with Effects of Viscous Dissipation, Joule Heating and Partial Velocity Slip. Sci. Rep.5, 17848; doi: 10.1038/srep17848 (2015).


The unique hollow nanocage structures shorten the length of Li-ion diffusion. The hollow structure offers a sufficient void space, which sufficiently alleviates the mechanical stress caused by volume change. Besides, the hybrid elements allow the volume change to take place in a stepwise manner during electrochemical cycle. And thus, the hierarchical hollow NiFe2O4 nanocage electrode exhibits extraordinary electrochemical performance. The stable cyclic performance is obtained for all rates from 1 C to 10 C. Even when the current reaches 10 C, the capacity can also arrive at 652 mAhg−1. Subsequently, a specific capacity of ca. 975 mAhg−1 is recovered when the current rate reduces back to 1 C after 200 cycles. This strategy that derived from NMOFs may shed light on a new route for large-scale synthesis of hollow porous hybrid nanocages for energy storage, environmental remediation and other novel applications.A hollow hybrid Ni-Fe-O nanomaterial (NiFe Cho et al.2O3 prepared from a typical iron-based NMOF template (MIL-88-Fe). Most recently, some nonspherical hollow-structured porous shell materials were synthesized by our group and others24Regarding the templates used for hollow structured electrode materials, nanostructured metal-organic frameworks (NMOFs)2122102O4 with a hollow nanocage structure is synthesized to validate our proposed strategy in preparing hollow porous nanocages using NMOFs as a template  to fast diffusion for reversible lithium ion storage, resulting in a good toleration to volume change during cycling12132O4 nanocages synthesized using nano metal-organic frameworks and its associated high electrochemical performance when used as the anode materials for LIBs.In this work, a hybrid nanostructured NiFetemplate . The adv3COO)2 and 0.993 g of sodium citrate in 100 mL of distilled water with stirring. Solution B was prepared by adding 1.32 g of K3[Fe(CN)6] into 100 mL of aqueous solution of PVP K30 (4 g) with stirring. Then Solution A and Solution B were mixed together under stirring. After 20 minutes of stirring, an eggplant turbid liquid was formed and then aged for 24 hours for forming a precipitate. Then the precipitate was treated by several centrifuge-wash cycles with distilled water and ethanol, and then dried at room temperature for 10 hours. The collected powder of hollow porous NiFe2O4 nanocages was annealed in Air at 350 °C for 2 hours at a heating rate of 1 °C min−1 to obtain the product.All chemicals used in this work were analytical grade and used without further purification. For a typical synthetic experiment, Solution A was synthesized by dissolving 0.187 g of Ni was used for recording the FTIR spectra of the sample ranged from 500 to 4000 cm−1. The microstructural characteristics of NiFe2O4 nanocages were recorded by high-resolution transmission electron microscope  working at 200 kV accelerating voltage, and the lattice structure was identified by selected area electron diffraction (SAED) technique.X-ray diffraction (XRD) was used to identity the phase composition of synthesized samples over the 22O4 nanocages, acetylene black powder and polyvinylidene fluoride (PVDF) were used as conductive additive and binder, respectively. In the preparation, the synthesized NiFe2O4 nanocages were mixed with acetylene black and PVDF dissolved in N-methyl-pyrrolidinone in a weight ratio of 85:10:5 to form slurry, which was then painted on a copper foil to form the working electrode. This copper foil was served as both the material support and current collector. After solvent evaporation, the electrode was pressed and dried at 120 oC under vacuum for 48 hours. The electrochemical cells were assembled in a argon filled glove-box. Metallic lithium foil was used as the counter electrode. The electrolyte was 1M LiPF6 in a mixture of ethylene carbonate (EC) and dimethyl carbonate (DMC) (1:1 in vol. ratio). Cycling tests were carried out at different current densities (1c = 914 mAg−1), in the voltage range of 0.01–1.5 V versus Li/Li+ by using a Land 2100A tester.For electrochemical performance evaluation, half-cell measurements were performed. For preparation of working electrode containing NiFe2O4 nanocages are analyzed by XRD, as shown in 2Fe(CN)6 does not contain impurity. All the diffraction peaks of final products, shown in 2O4 (JCPDS card no. 10–0325) without impurity peaks, indicating a complete thermal conversion of the NMOF precursors into NiFe2O4 nanostructures. The FTIR spectrum images of the prepared hollow structured NiFe2O4 nanocage sample and its Ni2Fe(CN)6 precursor are shown in −1 can be assigned to the stretching vibrations of the -OH group of absorbed water molecules and absorption of CO2 in the air. According to the spectrum of Ni2Fe(CN)6, the peaks from 1654 to 1601 cm−1 can be assigned to the bending vibrations of the water molecules; the spike of 2108 cm−1 is assigned to the stretching vibrations of the cyano group of precursor. These peaks are all disappeared in the spectrum of synthesized NiFe2O4 samples, indicating that these groups have decomposed after the calcinations. The strongest broad peaks in the range of 992 to 500 cm−1 are contributed from the bands of metal-oxideThe crystallographic structure and phase purity of the precursor and as-synthesized hollow porous NiFe2Fe(CN)6 precursors. It is clear that the precursors are solid submicro-cubes with an average diameter of ca.100 nm according to 2O4 nanocage sample is also characterized by SEM, TEM and HR-TEM, as illustrated in 2Fe(CN)6 precursors at 350 °C for 4 hours, a fluffy black powder contains uniformly distributed nanocubes with a shrunk size as in 2O4 sample from NMOFs is not a solid box but a visible hollow porous interior structure with an average diameter of ca. 80 nm, as evidenced by the partial broken shell vividly, as shown in 2O4 powder is made up from nano-sized small particles of ca. 3–9 nm, which is in a good agreement with XRD results. The selected-area electron diffraction (SAED) pattern (2O4 (3 1 1) plane spacing 6 is converted into NiFe2O4, the carbon and nitrogen in CN– are oxidized into gases and escaped.The formation mechanism can be described as schematically illustrated in 2O4 obtained after calcination at 150 °C, 200 °C, 250 °C, 300 °C, 350 °C and 400 °C for 4 hours, respectively. It can be seen that only solid nanocages with a smooth surface can be formed after calcination at 150 °C  electrode are shown in 3+ and Ni2+ to their metallic states and the formation of Li2O2O4 with Li can be written as Equations  and charge (Li+ extraction) curve at a current density of 1 C in the voltage window of 0.01–3 V  and the reduction of metal oxide to metal with Li2O formation. These results are consistent with CV analysis. From the second cycle onwards, the long potential plateau is replaced by a long slope between 1.2 and 0.73 V. After 200 cycles, the capacity can also be kept at 1071 mAhg−1, showing the excellent reversibility of electrode. To further investigate electrochemical performance, 2O4 electrode at different charging rates from 1 C to 10 C with 40 cycles. It can be seen that the stable cyclic performance can be obtained at all rates. Even when the current reaches 10 C, the capacity can also maintain at 652 mAh g−1. Subsequently, a specific capacity of ca. 975 mAhg−1 is recovered when the current rate reduces back to 1 C after 200 cycles. The overall rate performance demonstrates the high capacities in both low and high current rates of the prepared NiFe2O4 nanocage electrode. In 2O4 electrode after 200 cycles at a current rate of 1 C reveals that the structure of this anode material can be retained well without breakage in the process of charge-discharge. Compared with the previously reported TMOs materials243334352O4 material in this work exhibits an enhanced electrochemical performance with our novel strategy. The unique hollow nanocage structures can shorten the length of Li-ion diffusion, which is beneficial to the rate performance. Furthermore, the hollow structure can offer a sufficient void space, sufficiently alleviating the mechanical stress caused by the volume change. Besides, the hybrid elements allow the volume change to take place in a stepwise manner during electrochemical cycle. As a result, the hierarchical hollow NiFe2O4 nanocage electrode can exhibit an extraordinary high electrochemical performance.Similar to the simple oxide Fe0.01–3 V  shows a 2O4 nanocage from NMOFs is successfully synthesized by a facile and fast benign procedure. When it is used as an anode material for Lithium-ion battery, a stable reversible capacity can be retained at 1017 mAhg−1 after 200 cycles with an excellent rate performance. This novel synthetic strategy may shed light on a novel avenue for the effective synthesis of hollow porous hybrid nanocage materials derived from NMOFs for energy storage, sensor, catalyst, environmental remediation and other new applications.In summary, material with a structure of hollow porous NiFeHow to cite this article: Guo, H. et al. Self-assembly formation of hollow Ni-Fe-O nanocage architectures by metal-organic frameworks with high-performance lithium storage. Sci. Rep. 5, 13310; doi: 10.1038/srep13310 (2015).


Accumulation of the amyloid-beta (Aβ) peptide is a central factor in Alzheimer’s disease (AD) pathogenesis as supported by continuing evidence. This review concisely summarizes this evidence supporting a critical role for Aβ in AD before discussing the clearance of this peptide. Mechanisms of clearance of Aβ are critical for preventing pathological elevations in Aβ concentration. Direct degradation of Aβ by endopeptidases has emerged as one important pathway for clearance. Of particular interest are endopeptidases that are sensitive to the neprilysin (NEP) inhibitors thiorphan and phosphoramidon  as these inhibitors induce a dramatic increase in Aβ levels in rodents. This review will focus on neprilysin-2 (NEP2), a NEP-like endopeptidase which cooperates with NEP to control Aβ levels in the brain. The evidence for the involvement of NEP2 in AD is discussed as well as the therapeutic relevance with regards to gene therapy and the development of molecular markers for the disease. The involvement of Aβ in AD is a prerequisite to the significance of Aβ clearance to AD. Therefore, we will present a rationale for the clear link between Aβ and AD progression. The formation of Aβ has been well studied 1 . While various Aβ peptide lengths are produced by γ-secretase, it is Aβ42 and Aβ40 that have received the most attention. The additional two hydrophobic residues in Aβ42 increase its ability to aggregate, providing the scaffold for oligomeric and fibrillar forms of Aβ  is a devastating neurodegenerative disorder that leads to behavioral, cognitive, and memory deficits. Familial AD (FAD) is inherited in an autosomal dominant pattern with symptoms typically presenting in the 4th or 5th decade of life. Sporadic late onset AD (LOAD) has a much later age of onset, usually beginning in the 7th–8th decade. Confirmed post mortem, AD pathology shows accumulations of extracellular amyloid-beta (Aβ) containing plaques and intracellular neurofibrillary 42: Aβ40 ratio, or its aggregation  has a distinct root cause(s) that is not dependent on Aβ. While this is a possibility, several lines of evidence suggest otherwise. First, these two forms of AD have very similar pathology  increase in Aβ levels that are far from the levels needed to induce plaque deposition, as observed with NEP inhibitors, until very advanced age . NEP2 is also a zinc metalloendopeptidase belonging to the same M13 family as NEP. It has also been demonstrated in rodents that NEP2 is sensitive to the same NEP inhibitors, phosphoramidon and thiorphan , and mNEP2-β/γ had nearly undetectable activity against Aβ. However, subsequent studies using live cell assays demonstrated that mNEP2-α and hNEP2-β are able to degrade Aβ40, and more importantly, Aβ42 with comparable efficiency with NEP , and AD subjects, NEP2 mRNA expression levels in the mid-temporal gyrus were found to be lowered in women with MCI compared to non-impaired women (Huang et al., The impact that Alzheimer’s disease will have on the future of medicine over the next 40 years cannot be understated, and the accumulation of Aβ is currently the best theory to describe the main drive for the overall disease process. Therefore continued research into the mechanisms of Aβ clearance remains of upmost importance. The discovery of endopeptidases that degrade Aβ, such as NEP and NEP2 highlight an avenue of intervention via viral-mediated gene therapy. While NEP studies have produced encouraging results, studies utilizing NEP2 as a therapeutic agent are still warranted as NEP2 may be more selective for Aβ (Whyteside and Turner, The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Page 5, “T6SS and pathogenesis” section.1. “The T6SS organelle is functionally analogous to T3SS, and may have a critical function in the process of bacterial infection .” .is supposed to be functionally analogous to T3SS, and may have a critical function in the process of V. parahaemolyticus adhesion.correct to “The T6SS organelle chromosome I,” .2. “T6SS2 has been found in both clinical and environmental isolates, is encoded on chromosome II,”correct to “T6SS2 has been found in both clinical and environmental isolates, is encoded on 3. The sentence “The VP1415 is another effector for T6SS1, and it is sufficient to exert toxicity .” should be added at the last of this section. .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


PBP3) from Pseudomonas aeruginosa is the molecular target of β‐lactam‐based antibiotics. Structures of PBP3 in complexes with azlocillin and cefoperazone, which are in clinical use for the treatment of pseudomonad infections, have been determined to 2.0 Å resolution. Together with data from other complexes, these structures identify a common set of residues involved in the binding of β‐lactams to PBP3. Comparison of wild‐type and an active site mutant (S294A) showed that increased thermal stability of PBP3 following azlocillin binding was entirely due to covalent binding to S294, whereas cefoperazone binding produces some increase in stability without the covalent link. Consistent with this, a third crystal structure was determined in which the hydrolysis product of cefoperazone was noncovalently bound in the active site of PBP3. This is the first structure of a complex between a penicillin‐binding protein and cephalosporic acid and may be important in the design of new noncovalent PBP3 inhibitors.Penicillin‐binding protein 3 ( ACAanhydrodesacetyl cephalosporoic acidAECacyl–enzyme complexHMWhigh molecular weightLMWlow molecular weightPBP3penicillin‐binding protein 3TGtransglycosylationTmmelting temperatureTPtranspeptidasePseudomonas aeruginosa is a membrane bound transpeptidase located on the periplasmic side of the inner membrane. It is involved in the synthesis of the peptidoglycan component of the bacterial cell wall by catalysing the cross‐linking of ᴅ‐alanine to form N‐acetylglucosamine‐N‐acetyl muramic polymers P. aeruginosa, to β‐lactam antibiotics has become a major issue Penicillin‐binding protein 3 (PBP3) of P. aeruginosa (MIC50 50 μg·mL−1) 50 25 μg·mL−1) 5S)‐penicilloic acid (PA), a product of deacylated PBP3–piperacillin AEC P. aeruginosa in complexes with azlocillin and cefoperazone. The structure of the PBP3–azlocillin complex shows the ring‐opened β‐lactam intermediate covalently bound to S294. For the PBP3–cefoperazone complex, two different crystal structures were obtained. In one case, similar to the azlocillin complex, the cefoperazone (introduced by soaking) forms a covalent intermediate to the catalytic S294 of the active site. In the second structure, the ester‐linkage of cefoperazone with S294 is hydrolysed during the crystallization process and the product of the reaction, anhydrodesacetyl cephalosporoic acid (ACA), is observed bound in the active site. Similarities and differences between the three antibiotic bound structures and related ones are discussed.Azlocillin Fig. A is repret al. Escherichia coli Rosetta™ 2(DE3) cells grown in autoinduction media m Tris pH 7.5, 200 mm NaCl. Fractions containing PBP3 were combined and concentrated prior to use.The soluble domain of PBP3 (residues 35‐579) was produced using the method of Sainsbury −1 in 200 nL volume sitting drops by vapour diffusion as previously described m azlocillin in a standard three row optimization of 2.5 m NaCl; 0.1 m imidazole pH 8.0  using the method of Walter et al. m cefoperazone in 1.26 m (NH4)2SO4; 0.1 m CHES pH 9.5; 0.2 m NaCl . Diffraction data were collected 9 days after the crystallization plates were set up. Data from a type (a) crystal showed no azlocillin at the active site of PBP3, while data from a type (b) crystal showed binding of the deacylated product of cefoperazone at the active site of PBP3. PBP3–azlocillin and PBP3–cefoperazone covalent complexes were then obtained by soaking the two penicillins separately with type (a) crystals for about 2 h at a concentration of 20 mg·mL−1, equating to 31 mm cefoperazone and 43 mm azlocillin respectively.Crystallization screening experiments were performed with PBP3 at 4.3 mg·mL4KQO) as search model. Structures were refined with PHENIX X‐ray diffraction data were collected at 100K at beam lines I04‐1 and I02, Diamond Light Source. Diffraction images were indexed, integrated and merged with HKL2000 −1 along with 3 μL of 10 mm antibiotic solution. The sample was made up to 50 μL with 20 mm Tris pH 7.5 and 200 mm NaCl, sealed and heated in an Mx3005p qPCR machine  from 25 to 95 °C at a rate of 1 °C·min−1Tm) values. Experiments were carried out in triplicate and Tm values were calculated for each well and compared to the reference Tm values to obtain ΔTm for each compound.Five microlitre of 20× SYPRO orange dye was added to 15 μL of protein at 4 mg·mLPBP3 (residues 35‐579) was produced as previously described 4KQO and Fig. There are three conserved motifs found in the active site among all types of PBPs, SXXK, SXN and KSGT which are important in the catalysis The structure of PBP3–cefoperazone covalent complex was obtained by soaking a type (a) crystal with cefoperazone prior to data collection Table . Examina4KQO) shows that the two acyl complexes are very similar , bound in the active site Figs D and 3C.P. aeruginosa noncovalently bound to a deacylated β‐lactam product, namely (5S)‐penicilloic acid (PA). In this case the complex was obtained by both cocrystallization of PBP3 with piperacillin and crystal soaking with the reaction product of piperacillin and a metallo‐β‐lactamase. In the PBP3–ACA structure, the thiazine ring is a (6R) epimer  epimer ‐PA, which was gradually converted to (5S)‐PA There is one other report of PBP3 from mer Figs  and 4D cmer Figs  and 4D. R) stereochemistry its dimethyl group would clash with F533, whereas (6R)‐ACA is accommodated. To avoid steric clashes, the epimerization of PA also results in rotation ~ 80° of the carboxylate produced from the cleavage of the ester‐linkage. In both the covalent PBP3–cefoperazone and PBP3–ACA noncovalent complexes, the inhibitor makes addition hydrogen bonds compared to piperacillin and PA due to differences in substituents. The hydroxyphenyl side‐chain of ACA/cefoperazone forms a hydrogen bond with Y532 , a large space surrounded by N terminus of α11 and C‐termini of α4 and α10 is not occupied. This space can be targeted by addition of a chemical group to the thiadine ring of ACA or the thiazolidine ring of PA to increase the inhibitor interactions with PBP3 to make more potent non‐β‐lactam inhibitor.Tm) of PBP3. The Tm of PBP3 alone was 40 ± 1 °C  was changed to alanine and the mutated protein evaluated in the thermal shift assay. The results showed that preventing formation of the acyl complex by the S294A mutation, abolished the thermal shift due to addition of azlocillin  shows that a common set of residues, including the active site serine which becomes acylated, are key for binding. Additional hydrogen bond interactions contribute to the binding of different β‐lactams as determined by their substituents on the β‐lactam core. In all cases binding of the inhibitors is associated with a narrowing of the substrate‐binding cleft compared to the unliganded enzyme. Deacylation of the active site serine occurs over time and the crystal structures of the PBP3–ACA and PBP3–PA show that some inhibitors remain bound in the substrate‐binding cleft of the enzyme. This raises the possibility of using this structural information in the design of new nonlactam inhibitors which would not be susceptible to degradation by beta‐lactamases and hence overcome at least one mechanism of antibiotic resistance in the treatment of Pseudomonas infections.Structural analysis of PBP3 from JR, JN, DIS and RJO devised the study, JN and AM purified and crystallized the PBP3 complexes, JR solved the structures of the PBP3 complexes. JR and RJO analysed the results and all authors contributed to writing the paper.


Transport across the blood–brain barrier (BBB) is an important mediator of beta-amyloid (Aβ) accumulation in the brain and a contributing factor in the pathogenesis of Alzheimer’s disease (AD). One of the receptors responsible for the transport of Aβ in the BBB is the low density lipoprotein receptor-related protein 1 (LRP1). LRP1 is susceptible to proteolytic shedding at the cell surface, which prevents endocytic transport of ligands. Previously, we reported a strong inverse correlation between LRP1 shedding in the brain and Aβ transit across the BBB. Several proteases contribute to the ectodomain shedding of LRP1 including the α-secretase, a desintegrin and metalloproteinase domain containing protein 10 (ADAM10).The role of ADAM10 in the shedding of LRP1 and Aβ BBB clearance was assessed through pharmacological inhibition of ADAM10 in an in vitro model of the BBB and through the use of ADAM10 endothelial specific knock-out mice. In addition, an acute treatment paradigm with an ADAM10 inhibitor was also tested in an AD mouse model to assess the effect of ADAM10 inhibition on LRP1 shedding and Aβbrain accumulation.In the current studies, inhibition of ADAM10 reduced LRP1 shedding in brain endothelial cultures and increased Aβ42 transit across an in vitro model of the BBB. Similarly, transgenic ADAM10 endothelial knockout mice displayed lower LRP1 shedding in the brain and significantly enhanced Aβ clearance across the BBB compared to wild-type animals. Acute treatment with the ADAM10-selective inhibitor GI254023X in an AD mouse model substantially reduced brain LRP1 shedding and increased Aβ40 levels in the plasma, indicating enhanced Aβ transit from the brain to the periphery. Furthermore, both soluble and insoluble Aβ40 and Aβ42 brain levels were decreased following GI254023X treatment, but these effects lacked statistical significance.These studies demonstrate a role for ADAM10 in the ectodomain shedding of LRP1 in the brain and the clearance of Aβ across the BBB, which may provide a novel strategy for attenuating Aβ accumulation in the AD brain. Alzheimer’s disease is the most common cause of dementia in the elderly and is characterized, in part, by the deposition of amyloid beta (Aβ) in the brain and cerebrovasculature. The accumulation of soluble Aβ precedes the initial neurodegeneratitive and neurotoxic cascade and correlates strongly with reductions in cognitive performance –3. It haOne of the prominent mechanisms responsible for the elimination of Aβ from the brain involves transcytosis across the blood–brain barrier (BBB). The rate in which Aβ is cleared from the brain to the blood through the BBB is greater than the rate in which it can be removed via interstitial fluid bulk flow , likely In addition to the membrane-associated protein, LRP1 also exists in a soluble form as a result of proteolytic cleavage at the surface of the cell. This soluble LRP1 fragment retains its binding capacity, but loses its ability to endocytose and transport ligands –16. In lADAM10 endothelial KO mice were kindly provided, by Dr. Carl Blobel , Dr. B. De Strooper  and Dr. P. Saftig . These mice were generated by crossing ADAM10 flox/flox mice  with TieUsing a standard protocol to limit aggregation, both human recombinant Aβ42 and fluorescein labeled Aβ42 were solubilized in 1,1,1,3,3,3-hexafluoro-2-propanol to acquire a monomeric/dimeric sample and minimize the formation of β-sheet structures as we previously described .2 onto fibronectin-coated 6-well plates as previously described by our group [Human Brain Microvessel endothelial cells (HBMECs)  were seeded at 50,000 cells per cmur group . When apur group . After tThe impact of ADAM10 on Aβ42 transcytosis was assessed using an in vitro BBB model previously described by our group . HBMECs g for 15 min to remove intact cells, cell associated proteins and non-soluble components. The levels of LRP1 in the soluble fraction were measured in the supernatant using a LRP1 ELISA  and normalized to the total protein content in the brain homogenate as determined by the bicinchoninic acid (BCA) protein assay . Soluble LRP1 levels were expressed as ng of LRP1 per mg protein.To determine the role of ADAM10 in the clearance of Aβ42 from the brain to the periphery, we examined the appearance of human Aβ42 in the plasma after intracranial Aβ administration as previously described by our group , 26. Brig for 30 min at 4 °C. 100 μl of the resulting supernatant was mixed with 5 M guanidine in TRIS buffer resulting in the guanidine soluble (GS) fraction. For the guanidine insoluble (GI) fraction, 100 μl of the guanidine stock was combined with the original tissue pellet. Both GS and GI fractions were subsequently incubated at room temperature for 1 h and were mixed every 15 min. All samples were stored at −80 °C prior to analysis. Quantification of Aβ40 and Aβ42 in the GS, GI, and plasma fractions was determined using an ELISA for human Aβ40 and Aβ42  and expressed as ng of Aβ per μg total protein. The left hemisphere was used to examine the levels of soluble LRP1 in the brain. Here, the hemisphere was homogenized using a Dounce homogenizer in ice cold in HBSS using the same procedure as the in vivo LRP1 shedding studies above. LRP1 levels in the soluble brain fraction and plasma were assessed using a mouse ELISA for LRP1 . Soluble brain LRP1 was normalized to the total protein content in the brain homogenate as determined by the BCA protein assay . Soluble brain LRP1 levels were expressed as ng of LRP1 per mg protein. Plasma LRP1 levels were expressed as ng/ml. In addition, sAPPα levels were examined in the brain homogenate of these same animals using an ELISA for sAPPα . The sAPPα levels were normalized to the total protein content in the brain homogenate as determined by the BCA protein assay and expressed as ng of sAPPα per mg protein.PSAPP mice at 35 weeks of age were injected intraperitoneally with 200 mg/kg of GI254023X or vehicle (DMSO) once per day for 5 consecutive days. At this age, PSAPP mice display elevated levels of Aβ peptides in the brain . This trStatistical analyses were performed using a one-way ANOVA followed by Tukey’s post hoc analysis . Moreover, where only 2 groups were compared, unpaired t tests were used to evaluate statistical significance.Exposure of HBMECs to Aβ42 induced a significant increase in the extracellular shedding of LRP1 compared to control conditions (twofold)  Fig. a, b 1.1c, d (1.2Dysfunction within the cerebrovascular system is now recognized as a major contributory factor in the development of AD . It has Previous investigations have implicated the α-secretase enzyme, ADAM10, in the ectodomain shedding of LRP1 , 37. In As we identified a role for ADAM10 in mediating Aβ clearance across the BBB, we next examined the impact of ADAM10 inhibition on Aβ tissue levels in an animal model of AD. Using an acute 5-day treatment paradigm with the ADAM10-selective inhibitor GI254023X in PSAPP mice, we observed a substantial decrease in LRP1 shedding in the brain compared to vehicle-treated animals. Moreover, as previous studies have reported that soluble LRP1 levels in the plasma can facilitate Aβ removal from the brain by acting as a peripheral sink , we inveTo examine the impact of ADAM10 inhibition on Aβ levels in the brain, we examined both soluble and insoluble Aβ following GI254023X treatment in PSAPP animals. While we observed reductions in both soluble and insoluble Aβ40 and Aβ42 in the brain following GI254023X treatment, none of these effects were statistically significant. It is unclear why this treatment paradigm did not modulate Aβ levels in the brain more effectively. Both our prior work  and our A primary concern in targeting an enzyme like ADAM10, especially in AD, is the potential impact on other substrates that are metabolized by ADAM10. ADAM10 is one of the α-secretases which processes APP through the non-amyloidogenic pathway, resulting in the formation of sAPPα while at the same time avoiding the production of Aβ peptides. As such, inhibition of this pathway could facilitate Aβ synthesis and potentially exacerbate Aβ burden in the AD brain. Our data suggests this is not the case, as Aβ levels in the brain did not increase upon ADAM10 inhibition, but in fact decreased. To ascertain whether GI254023X treatment influenced the α-secretase pathway specifically, we measured sAPPα levels in the brain and found no difference between GI254023X-treated animals and the vehicle control group. These data indicate ADAM10 can be modulated to reduce LRP1 shedding in the brain without affecting the α-secretase cleavage of APP. One explanation for this may be the presence of other α-secretase enzymes, which process APP when ADAM10 is diminished or absent. To this point, it was previously found that sAPPα formation was preserved in fibroblast cells derived from ADAM10-deficient animals . It has Previously, our work demonstrated a strong inverse correlation between LRP1 shedding in the brain and Aβ clearance across the BBB. In the present studies, we show that modulation of the ADAM10 enzyme can effectively reduce LRP1 shedding and promote Aβ transport out of the brain. In an AD mouse model, acute treatment with an ADAM10 inhibitor substantially lowered LRP1 brain shedding and increased the appearance of Aβ40 in the plasma, indicating enhanced Aβ transit from the brain to the periphery. Alternatively, while ADAM10 inhibition decreased both Aβ40 and Aβ42 brain levels in the AD mice, these values were not statistically significant, indicating a more chronic treatment paradigm may be necessary to observe demonstrable changes in Aβ brain burden. Nevertheless, while further interrogation of this therapeutic approach is necessary, our findings indicate LRP1 sheddases can be targeted to facilitate Aβ elimination from the brain, providing a novel therapeutic strategy to mitigate Aβ accumulation in the AD brain.