A novel strategy for the assignment of side-chain resonances in completely deuterated large proteins using 13C spectroscopy

The assignment of the aliphatic 13C resonances of trimeric Bacillus Subtilis chorismate mutase, a protein with a molecular mass of 44kDa, consisting of three 127-residue monomers is presented by use of two-dimensional (2D) 13C-start and 13C-observe NMR experiments. These experiments start with 13C excitation and end with 13C observation while relying on the long transverse relaxation times of 13C spins in uniformly deuterated and 13C,15N-labeled large proteins. Gains in sensitivity are achieved by the use of a paramagnetic relaxation enhancement agent to reduce 13C T 1 relaxation times with little effect on 13C T 2 relaxation times. Such 2D 13C-only NMR experiments circumvent problems associated with the application of conventional experiments for side-chain assignment to proteins of larger sizes, for instance, the absence or low concentration of the side-chain 1H spins, the transfer of the side-chain spin polarization to the 1HN spins for signal acquisition, or the necessity of a quantitative reprotonation of the methyl moieties in the otherwise fully deuterated side-chains. We demonstrate that having obtained a nearly complete assignment of the side-chain aliphatic 13C resonances, the side-chain 1H chemical shifts can be assigned in a semiautomatic fashion using 3D 15N-resolved and 13C-resolved NOESY experiments measured with a randomly partially protonated protein sample. We also discuss perspectives for structure determination of larger proteins by using novel strategies which are based on the 1H,1H NOEs in combination with multiple residual dipolar couplings between adjacent 13C spins determined with 2D 13C-only experiment

Computational design of rare-earth reduced permanent magnets

Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic material composition. Iron (Fe)-rich magnetic phases suitable for permanent magnets can be found by means of adaptive genetic algorithms. The intrinsic properties computed by ab intro simulations are used as input for micromagnetic simulations of the hysteresis properties of permanent magnets with a realistic structure. Using machine learning techniques, the magnet's structure can be optimized so that the upper limits for coercivity and energy density product for a given phase can be estimated. Structure property relations of synthetic permanent magnets were computed for several candidate hard magnetic phases. The following pairs (coercive field (T), energy density product (kJ.m(-3))) were obtained for iron-tin-antimony (Fe3Sn0.75Sb0.25): (0.49, 290), L1(0) -ordered iron-nickel (L1(0) FeNi): (1, 400), cobalt-iron-tantalum (CoFe6Ta): (0.87, 425), and manganese-aluminum (MnAl): (0.53, 80).Web of Science6215314

Self-organizing magnetic beads for biomedical applications

In the field of biomedicine magnetic beads are used for drug delivery and to treat hyperthermia. Here we propose to use self-organized bead structures to isolate circulating tumor cells using lab-on-chip technologies. Typically blood flows past microposts functionalized with antibodies for circulating tumor cells. Creating these microposts with interacting magnetic beads makes it possible to tune the geometry in size, position and shape. We developed a simulation tool that combines micromagnetics and discrete particle dynamics, in order to design micropost arrays made of interacting beads. The simulation takes into account the viscous drag of the blood flow, magnetostatic interactions between the magnetic beads and gradient forces from external aligned magnets. We developed a particle-particle particle-mesh method for effective computation of the magnetic force and torque acting on the particles