Amylin is an endocrine hormone peptide that consists of 37 residues and is the main component of extracellular amyloid deposits found in the pancreas of most type 2 diabetes patients. Amylin peptides are self-assembled to form oligomers and fibrils. So far, four different molecular structures of the self-assembled amylin fibrils have been observed experimentally: two ssNMR models and two crystal models. This study reveals, for the first time, that there are four self-assembled amylin forms that differ in the orientations of the side chains along the β-arch and are all derived from the two ssNMR models. The two ssNMR models are composed of these four different self-assembled forms of amylin, and the two crystal models are composed of two different self-assembled forms of amylin. This study illustrates at the atomic level the differences among the four experimental models and proposes eight new models of self-assembled amylin that are also composed of the four different self-assembled forms of amylin. Our results show polymorphism of the self-assembled fibril-like amylin, with a slight preference of some of the newly constructed models over the experimental models. Finally, we propose that two different self-assembled fibril-like forms of amylin can interact to form a new fibril-like amylin. We investigated this argument and found that some fibril-like amylin prefers to interact to form stable fibril-like structures, whereas others disfavor it. Our work provides new insights that may suggest strategies for future pharmacological studies that aim to find ways to ameliorate the interactions between polymorphic oligomers and fibrils of amylin.

Abstract. We discuss the experimental feasibility of quantum simulation with trapped ion crystals, using magnetic field gradients. We describe a micro structured planar ion trap, which contains a central wire loop generating a strong magnetic gradient of about 20 T/m in an ion crystal held about 160 µm above the surface. On the theoretical side, we extend a proposal about spin-spin interactions via magnetic gradient induced coupling (MAGIC) [Johanning, et al, J. Phys. B: At. Mol. Opt. Phys. 42, (2009) 154009]. We describe aspects where planar ion traps promise novel physics: Spin-spin coupling strengths of transversal eigenmodes exhibit significant advantages over the coupling schemes in longitudinal direction that have been previously investigated. With a chip device and a magnetic field coil with small inductance, a resonant enhancement of magnetic spin forces through the application of alternating magnetic field gradients is proposed. Such resonantly enhanced spin-spin coupling may be used, for instance, to create Schrödinger cat states. Finally we investigate magnetic gradient interactions in twodimensional ion crystals, and discuss frustration effects in such twodimensional arrangements.

Reliability of molecular mechanics (MM) simulations in describing biomolecular ion-driven processes depends on their ability to accurately model interactions of ions simultaneously with water and other biochemical groups. In these models, ion descriptors are calibrated against reference data on ion-water interactions, and it is then assumed that these descriptors will also satisfactorily describe interactions of ions with other biochemical ligands. Comparison against experiment and high-level quantum mechanical data show that this transferability assumption can break down severely. One approach to improve transferability is to assign cross-terms or separate sets of nonbonded descriptors for every distinct pair of ion type and its coordinating ligand. Here we propose an alternative solution that targets an error-source directly and corrects misrepresented physics. In standard model development, ligand descriptors are never calibrated or benchmarked in the high electric fields present near ions. We demonstrate for a representative MM model that when the polarization descriptors of its ligands are improved to respond to both low and high fields, ligand interactions with ions also improve, and transferability errors reduce substantially. In our case, the overall transferability error reduces from 3.3 to 1.8 kcal/mol. These improvements are observed without compromising on accuracy of low-field interactions of ligands in gas and condensed phases. Reference data for calibration and performance evaluation is taken from experiment and also obtained systematically from "gold-standard" CCSD(T) in the complete basis set limit, followed by benchmarked vdW-inclusive DFT.

Mutations near the fluorescing chromophore of the green fluorescent protein (GFP) have direct effects on the absorption and emission spectra. Some mutants have significant band shifts and most of the mutants exhibit a loss of fluorescence intensity. In this study we continue our investigation of the factors controlling the excited state proton transfer (PT) process of GFP, in particular to study the effects of modifications to the key side chain Ser205 in wt-GFP, proposed to participate in the proton wire. To this aim we combined mutagenesis, X-ray crystallography, steady-state spectroscopy, time-resolved emission spectroscopy and all-atom explicit molecular dynamics (MD) simulations to study the double mutant T203V/S205A. Our results show that while in the previously described GFP double mutant T203V/S205V the PT process does not occur, in the T203V/S205A mutant the PT process does occur, but with a 350 times slower rate than in wild-type GFP (wt-GFP). Furthermore, the kinetic isotope effect in the GFP double mutant T203V/S205A is twice smaller than in the wt-GFP and in the GFP single mutant S205V, which forms a novel PT pathway. On the other hand, the crystal structure of GFP T203V/S205A does not reveal a viable proton transfer pathway. To explain PT in GFP T203V/S205A, we argue on the basis of the MD simulations for an alternative, novel proton-wire pathway which involves the phenol group of the chromophore and water molecules infrequently entering from the bulk. This alternative pathway may explain the dramatically slow PT in the GFP double mutant T203V/S205A compared to wt-GFP.

Amylin is an endocrine hormone and is a member of the family of amyloid peptides and proteins that emerge as potential scaffolds by self-assembly processes. Zn(2+) ions can bind to amylin peptides to form self-assembled Zn(2+)-amylin oligomers. In the current work the binding sites of Zn(2+) ions in the self-assembled amylin oligomers at various concentrations of zinc have been investigated. Our results yield two conclusions. First, in the absence of Zn(2+) ions polymorphic states (i.e. various classes of amylin oligomers) are obtained, but when Zn(2+) ions bind to amylin peptides to form Zn(2+)-amylin oligomers, the polymorphism is decreased, i.e. Zn(2+) ions bind only to specific classes of amylin. At low concentrations of Zn(2+) ions the polymorphism is smaller than at high concentrations. Second, the structural features of the self-assembled amylin oligomers are not affected by the presence of Zn(2+) ions. This study proposes new molecular mechanisms of the self-assembly of Zn(2+)-amylin oligomers.

Ion descriptors in molecular mechanics models are calibrated against reference data on ion−water interactions. It is then typically assumed that these descriptors will also satisfactorily describe interactions of ions with other functional groups, such as those present in biomolecules. However, several studies now demonstrate that this transferability assumption produces, in many different cases, large errors. Here we address this issue in a representative polarizable model and focus on transferability of cationic interactions from water to a series of alcohols. Both water and alcohols use hydroxyls for ion-coordination, and, therefore, this set of molecules constitutes the simplest possible case of transferability. We obtain gas phase reference data systematically from "gold-standard" quantum Monte Carlo and CCSD(T) methods, followed by benchmarked vdW-corrected DFT. We learn that the original polarizable model yields large gas phase water → alcohol transferability errors − the RMS and maximum errors are 2.3 and 5.1 kcal/mol, respectively. These errors are, nevertheless, systematic in that ion-alcohol interactions are overstabilized, and systematic errors typically imply that some essential physics is either missing or misrepresented. A comprehensive analysis shows that when both low-and high-field responses of ligand dipole polarization are described accurately, then transferability improves significantly − the RMS and maximum errors in the gas phase reduce, respectively, to 0.9 and 2.5 kcal/mol. Additionally, predictions of condensed phase transfer free energies also improve. Nevertheless, within the limits of the extrathermodynamic assumptions necessary to separate experimental estimates of salt dissolution into constituent cationic and anionic contributions, we note that the error in the condensed phase is systematic, which we attribute, at least, partially to the parametrization in long-range electrostatics. Overall, this work demonstrates a rational approach to boosting transferability of ionic interactions that will be applicable broadly to improving other polarizable and nonpolarizable models.

Therapeutic implications of Li + , in many cases, stem from its ability to inhibit certain Mg 2+-dependent enzymes, where it interacts with or substitutes for Mg 2+. The underlying details of its action are, however, unknown. Molecular simulations can provide insight, but their reliability depends on how well they describe relative interactions of Li + and Mg 2+ with water and other biochemical groups. Here we explore, benchmark and recommend improvements to two simulation approaches, one that employs an all-atom polarizable molecular mechanics (MM) model, and the other that uses a hybrid quantum and molecular mechanics implementation of the quasi-chemical theory (QCT). The strength of the former is that it describes thermal motions explicitly, and that of latter is that it derives local contributions from electron densities. Reference data is taken from experiment, and also obtained systematically from CCSD(T) theory, followed by benchmarked vdW-inclusive density functional theory. We find that the QCT model predicts relative hydration energies and structures in agreement with experiment, and without need for additional parameterization. This implies that accurate descriptions of local interactions are essential. Consistent with this observation, recalibration of local interactions in the MM model, which reduces errors from 10.0 to 1.4 kcal/mol, also fixes aqueous phase properties. Finally, we show that ion-ligand transferability errors in the MM model can be reduced significantly from 10.3 to 1.2 kcal/mol by correcting the ligand's polarization term, and introducing Lennard-Jones cross-terms. In general, this work sets up systematic approaches to evaluate and improve molecular models of ions binding to proteins.

The reliability of molecular mechanics simulations to predict effects of ion binding to proteins depends on their ability to simultaneously describe ion–protein, ion–water, and protein–water interactions. Force fields (FFs) to describe protein–water and ion–water interactions have been constructed carefully and have also been refined routinely to improve accuracy. Descriptions for ion–protein interactions have also been refined, although in an a posteriori manner through the use of “nonbonded-fix (NB-fix)” approaches in which parameters from default Lennard-Jones mixing rules are replaced with those optimized against some reference data. However, even after NB-fix corrections, there remains a significant need for improvement. This is also true for polarizable FFs that include self-consistent inducible moments. Our recent studies on the polarizable AMOEBA FF suggested that the problem associated with modeling ion–protein interactions could be alleviated by recalibrating polarization models of cation-coordinating functional groups so that they respond better to the high electric fields present near ions. Here, we present such a recalibration of carbonyls, carboxylates, and hydroxyls in the AMOEBA protein FF and report that it does improve predictions substantiallymean absolute errors in Na+–protein and K+–protein interaction energies decrease from 8.7 to 5.3 and 9.6 to 6.3 kcal/mol, respectively. Errors are computed with respect to estimates from van der Waals-inclusive density functional theory benchmarked against high-level quantum mechanical calculations and experiments. While recalibration does improve ion–protein interaction energies, they still remain underestimated, suggesting that further improvements can be made in a systematic manner through modifications in classical formalism. Nevertheless, we show that by applying our many-body NB-fix correction to Lennard-Jones components, these errors are further reduced to 2.7 and 2.6 kcal/mol, respectively, for Na+ and K+ ions. Finally, we show that the recalibrated AMOEBA protein FF retains its intrinsic reliability in predicting protein structure and dynamics in the condensed phase.