Glenn L. Millhauser

Two‐dimensional electron spin echo spectroscopy and slow motions

A technique is described for the study of slow molecular motions that employs two‐dimensional electron spin echo (2D‐ESE) spectroscopy. An ‘‘echo‐induced ESR spectrum’’ is obtained with a two pulse 90° (τ)/() 180° sequence by recording the echo height as the dc field is swept. A series of sweeps with different τ are Fourier transformed to yield a two‐dimensional spectrum comprised of an echo‐induced spectrum along the x axis and the homogeneous widths along the y axis. A convenient theoretical analysis appropriate for slow motions is given and it is shown that the 2D spectrum may be regarded as a graph of the widths vs the resonance positions of the individual ‘‘dynamics spin packets’’ that constitute the spectrum. An experimental study of the spin probe Tempone in 85% glycerol/H2O solvent for slow motions (i.e., rotational correlational times of order 10−5–10−6 s) shows variations in homogeneous widths (i.e., T−12) over the spectrum. This is analyzed in terms of canonical models of rotational reorientati...

Two-dimensional electron spin echoes: magnetization transfer and molecular dynamics

Abstract The utility of inversion recovery and stimulated echoes in studying slow motional dynamics is analyzed. A comparison between theory and experiment is provided for a nitroxide radical in viscous solvent. A new two-dimensional stimulated echo technique, suggested by the theory, is applied to study NO2 physisorbed on vycor.

Linear prediction and resolution enhancement of complex line shapes in two‐dimensional electron‐spin‐echo spectroscopy

A new type of two‐dimensional electron‐spin‐echo (2D‐ESE) spectroscopy was recently shown to be useful for studying slow molecular motions in liquids. A recently developed method of spectral enhancement based upon linear prediction with singular value decomposition (LPSVD) is applied in the present work to dramatically improve the signal‐to‐noise ratio and to correct for finite dead time in the data from this 2D‐ESE experiment. This permitted a more accurate comparison between theory and experiment. Good agreement is now obtained with a model of nearly isotropic Brownian motion for tempone in glycerol/water solvent.

Rapid singular value decomposition for time-domain analysis of magnetic resonance signals by use of the lanczos algorithm

Time-series analysis has become an integral part of signal interpretation in magnetic resonance and other experiments. As an example, linear prediction with singular value decomposition (LPSVD) (I, 2) and the related method, Hankel SVD (HSVD) (3)) have been recently applied to problems in NMR (2)) 2D NMR (4), 2D electron spin-echo spectroscopy (2D ESE) (5,6), Fourier transform ESR correlation spectroscopy ( 7)) time-resolved femtosecond spectroscopy (8)) and nonstationary neurological currents ( 9). The minimal goal of time-series analysis is to separate signal from noise. Spectral transform methods, such as FFT filtering (IO), maximum entropy ( MEM ) ( I I ) , and LPZ ( 12)) replace the original data with a new time series (or its spectrum) that has an enhanced signal-to-noise ratio. In contrast spectral decomposition methods, such as LPSVD or HSVD, which assume a certain functional form for the time series, provide both a recipe for separating signal from noise and a listing of the harmonic components contained in the original data. This harmonic list simplifies spectral analysis and can be used to (1) extend the noise-reduced time series, (2) selectively reconstruct certain regions of the harmonic spectrum, and (3) data-compress the signal. The substantial benefits of spectral decomposition are often offset by the requirements of considerable computational time and memory storage. For a time series of N data points spectral transform techniques usually require computational time of O(N logzN) to O(N’) and storage of O(N) whereas spectral decomposition, such as HSVD, requires computational time of 0( N3) and storage of O(N2). We have investigated a new approach for solving the spectral decomposition problem which is based on the Lanczos algorithm (LA) (13). In the past the LA has provided an effective means for solving slow-motional magnetic resonance spectra ( 14, 15) as well as other complicated problems in chemical physics ( 16, 17). The LA is an extremely fast method for solving large eigenelement problems when either (1)

Application of EPR methods in studies of immobilized enzyme systems

Electron paramagnetic resonance (EPR) spectroscopy has recently proven to be an extremely powerful tool for studying structure-function and structure-stability relationships in immobilized chymotrypsin catalysis.-5 Currently, EPR methods are being used to examine other immobilized enzyme systems as well, including immobilized horse liver alcohol dehydrogenase and immobilized bovine liver 8-galactosidase. This report describes some preliminary results from these studies and illustrates the significant potential of this methodology to enhance molecular-level understanding of immobilized enzyme behavior.

Diffusion model in ion channel gating. Extension to agonist-activated ion channels.

Previously, we described a model which treats ion channel gating as a discrete diffusion problem. In the case of agonist-activated channels at high agonist concentration, the model predicts that the closed lifetime probability density function from single channel recording approximates a power law with an exponent of -3/2 (Millhauser, G. L., E. E. Salpeter, and R. E. Oswald. 1988a. Proc. Natl. Acad. Sci. USA. 85: 1503-1507). This prediction is consistent with distributions derived from a number of ligand-gated channels at high agonist concentration (Millhauser, G. L., E. E. Salpeter, and R. E. Oswald. 1988b. Biophys. J. 54: 1165-1168.) but does not describe the behavior of ion channels at low activator concentrations. We examine here an extension of this model to include an agonist binding step. This extended model is consistent with the closed time distributions generated from the BC3H-1 nicotinic acetylcholine receptor for agonist concentrations varying over three orders of magnitude.

Structural and functional responses of enzymes to immobilization: new insights from EPR spectroscopy.

Greater understanding at the molecular level of how immobilization affects the properties of enzymes is a major goal of current research. However, many analytical methods are unsuitable for studying immobilized enzymes due to interference from the support matrix. One method not subject to this limitation that has recently proven extremely useful for elucidating structure-function relationships in immobilized enzyme catalysis is electron paramagnetic resonance (EPR) spectroscopy. In this paper, new insights obtained from EPR investigations of different immobilized horse liver alcohol dehydrogenase preparations are discussed. These results illustrate the significant potential of EPR spectroscopy as a tool for studying and characterizing immobilized enzyme behavior.