Kincaidcooney1431
Using all-atom explicit water replica-exchange molecular dynamics simulations, we examined the impact of three popular force fields (FF) on the equilibrium binding of Aβ10-40 peptide to the dimyristoylgylcerophosphocholine (DMPC) bilayer. The comparison included CHARMM22 protein FF with CHARMM36 lipid FF (C22), CHARMM36m protein FF with CHARMM36 lipid FF (C36), and Amber14SB protein FF with Lipid14 lipid FF (A14). Analysis of Aβ10-40 binding to the DMPC bilayer in three FFs revealed a consensus binding mechanism. Its main features include (i) a stable helical structure in the bound peptide, (ii) insertion of the C-terminus and, in part, the central hydrophobic cluster into the bilayer hydrophobic core, (iii) considerable thinning of the DMPC bilayer beneath the bound peptide coupled with significant drop in bilayer density, and (iv) a strong disordering in the DMPC fatty acid tails. this website Although the three FFs diverge on many details concerning Aβ and bilayer conformational ensembles, these discrepancies do not offset the features of the consensus binding mechanism. We compared our findings with other FF evaluations and proposed that an agreement between C22, C36, and A14 is a consequence of a strong ordering effect created by polar-apolar interface in the lipid bilayer. By comparing the consensus Aβ binding mechanism with experimental data, we surmise that the three tested FFs largely correctly capture the interactions of Aβ peptides with the DMPC lipid bilayer.An efficient algorithm to find the binding position and mode of small ligands bound at an active site of protein is proposed based on the spatial distribution function (SDF) obtained from the three-dimensional reference interaction site model (3D-RISM) theory with the Kovalenko-Hirata (KH) closure relation. The ligand examined includes hydrophobic, acidic, and basic molecules and zwitterions. Eighteen different types of proteins, which serve as targets for those ligands, are selected to examine the robustness of the algorithm. An imaginary atom, referred to as an "anchor site", is defined at the center of geometry of a ligand molecule that serves as a center for searching the binding position and mode of the ligand molecule in the translational and rotational spaces. The probable binding sites (PBSs) are identified based on the SDFs of the ligand molecules around the protein, and the PBS is ranked according to the peak height of SDF. The deviations from the mean height of the peak values of SDFs for 50 PBSs are analyzed based on the z-score, which is a measure of prominence of the site. The PBS found at the closest distance from the anchor site of the crystal structure is referred to as the "nearest site". The orientation of the ligand molecule at each PBS is explored by changing the Euler angles, and the most probable binding mode is determined based on the superposition approximation. The binding position of ligand molecules is successfully predicted as one of the distinct peaks in SDF of the anchor site, with a few exceptions. The binding mode of the ligand molecule predicted based on the superposition approximation is consistent with the X-ray crystal structure in nine systems, a half of the systems investigated. The significance of the results is discussed in detail. An application of the new protocol to fragment-based drug discovery is suggested.Reactions of the atomic lanthanide cerium cation (Ce+) with H2, D2, and HD were studied by using guided ion beam tandem mass spectrometry. Analysis of the kinetic-energy-dependent endothermic reactions to form CeH+ (CeD+) led to a 0 K bond dissociation energy (BDE) for CeH+ of 2.19 ± 0.09 eV. Theoretical calculations for CeH+ were performed at the B3LYP, BHLYP, and PBE0 levels of theory and overestimate the experimental BDE. In contrast, extrapolation to the complete basis set limit using coupled-cluster with single, double, and perturbative triple excitations, CCSD(T), gave a value (2.33 eV) in reasonable agreement with the experimental BDE. The branching ratio of the CeH+ and CeD+ products in the HD reaction suggests that the reaction occurs via a statistical mechanism involving a long-lived intermediate. Relaxed potential energy surfaces for CeH2+ were computed and are consistent with the availability of such an intermediate, but the crossing point between quartet and doublet surfaces helps explain the inefficiency of the association reaction observed in the literature. The reactivity and CeH+ BDE are compared with previous results for group 4 transition metal cations (Ti+, Zr+, and Hf+), other lanthanides (La+, Sm+, Gd+, and Lu+), and the isovalent actinide Th+. Periodic trends and insight into the role of the electronic configuration on metal-hydride bond strength are discussed.The 0 K bond dissociation energies (BDE) of Au2+-CH4 and Au2CH4+-CH4 have been determined using two separate experimental methods. Analysis of collision-induced dissociation cross sections for Au2CH4+ + Xe and Au2(CH4)2+ + Xe measured using a guided ion beam tandem mass spectrometer (GIBMS) yield BDEs of 0.71 ± 0.05 and 0.57 ± 0.07 eV, respectively. Statistical modeling of association kinetics of Au2(CH4)0-2+ + CH4 + He measured from 200 - 400 K and 0.3 - 0.9 Torr using a selected-ion flow tube (SIFT) apparatus yield slightly higher values of 0.81 ± 0.20 and 0.75 ± 0.25 eV. The SIFT data also place a lower limit on the BDE of Au2C2H8+-CH4 of 0.35 eV, likely an activated isomer, not Au2(CH4)2+-CH4. Particular emphasis is placed on determining the uncertainty in the derivation from association kinetics measurements, including uncertainties in collisional energy transfer, calculated harmonic frequencies, and possible contribution of isomerization of the association complexes. This evaluation indicates than an uncertainty of ±0.2 eV should be expected, and an uncertainty of better than ±0.1 eV is unlikely to be reasonable.Multimodal mass spectrometry imaging (MSI) data presents unique big data challenges in handling and analysis. Here, we present a pipeline for co-registering matrix-assisted laser desorption/ionization MSI and confocal immunofluorescence imaging data for extracting single-cell metabolite signatures. We further describe methods and introduce software for the simultaneous analysis of these concatenated data sets, which are designed to establish a connection between cell traits of interest (shape metrics, position within sample) and the cells' own metabolic signatures.