PULSED DOUBLE-QUANTUM COHERENCE ELECTRON PARAMAGNETIC RESONANCE IN PROTEIN STRUCTURE DETERMINATION

161 pagesElectron paramagnetic resonance (EPR) or more specifically, pulsed dipolar EPR spectroscopy (PDS), combined with the site-directed spin labelling (SDSL) technique has emerged as a key technique in protein structure determination. The core concept is to filter out the weak dipolar interaction between a pair of spin labels by applying an appropriate pulse sequence and retrieve the inter-spin distance from the dipolar EPR signal. Double-quantum coherence (DQC) and double electron-electron resonance (DEER) are two such methods primarily used in studying the structure of proteins and other biomacromolecules. There are two main classes of spin labels used in PDS studies, (i) triarylmethyl (TAM) and (ii) nitroxides. DQC signal expression of nitroxide spin labels is extremely complex and without knowing the analytic form of the signal, the resulting spectra, especially in 2D, cannot be analyzed both accurately and efficiently. In the first part of the thesis, we derive analytic expressions of DQC signals for both TAM and nitroxide spin labels. These expressions are extremely useful in analyzing experimental signals using personal computers. Hence, we believe that this innovation is an important and necessary step in motivating the scientific community to use DQC more frequently in their studies. Another key challenge in PDS signal processing is the removal of intermolecular or background signal. An error in the process of background signal removal can translate into a critical error in obtaining the distance distribution. We have derived an analytic expression of the total DQC signal for spin, S=1/2, particles in frozen samples and this expression can be integrated over the spatial variables to derive the functional form of the signal. We have demonstrated the importance of the analytic expression in studying the spatial distribution of the spin-labeled proteins in frozen samples. In the last chapter, we present experimental studies that demonstrate the effect of the rate of freezing on the distance distributions derived from DEER experiments. In the same project, we have explored the effect of varying the amount of cryoprotectant and using different spin labels on the reconstructed distance distributions. We conclude that both slow freezing (>= 1 s) at 30% glycerol by weight and rapid freeze-quench (100 micro-s) at 10% glycerol result into reduced intermolecular spin-spin interactions and improved signal-to-noise ratio (snr). Additionally, we find that the effect of the conformational sub-states of the spin-labels on reconstructed distance distributions is averaged out in slow freezing, while the trapping of the conformational sub-states in rapid-quenched samples yields broadened distance distributions

Hyperfine Decoupling of ESR Spectra Using Wavelet Transform

The objective of spectral analysis is to resolve and extract relevant features from experimental data in an optimal fashion. In continuous-wave (cw) electron spin resonance (ESR) spectroscopy, both g values of a paramagnetic center and hyperfine splitting (A) caused by its interaction with neighboring magnetic nuclei in a molecule provide important structural and electronic information. However, in the presence of g- and/or A-anisotropy and/or large number of resonance lines, spectral analysis becomes highly challenging. Either high-resolution experimental techniques are employed to resolve the spectra in those cases or a range of suitable ESR frequencies are used in combination with simulations to identify the corresponding g and A values. In this work, we present a wavelet transform technique in resolving both simulated and experimental cw-ESR spectra by separating the hyperfine and super-hyperfine components. We exploit the multiresolution property of wavelet transforms that allow the separation of distinct features of a spectrum based on simultaneous analysis of spectrum and its varying frequency. We retain the wavelet components that stored the hyperfine and/or super-hyperfine features, while eliminating the wavelet components representing the remaining spectrum. We tested the method on simulated cases of metal–ligand adducts at L-, S-, and X-band frequencies, and showed that extracted g values, hyperfine and super-hyperfine coupling constants from simulated spectra, were in excellent agreement with the values of those parameters used in the simulations. For the experimental case of a copper(II) complex with distorted octahedral geometry, the method was able to extract g and hyperfine coupling constant values, and revealed features that were buried in the overlapped spectra

Unsupervised Analysis of Small Molecule Mixtures by Wavelet-Based Super-Resolved NMR

Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility, and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency, and/or the requirement of prior knowledge. Recently, we resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating the WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets

Analysis of small molecule mixtures by super-resolved 1H NMR spectroscopy

Analysis of small molecules is essential to metabolomics, natural products, drug discovery, food technology and many other areas of interest. Current barriers preclude from identifying the constituent molecules in a mixture as overlapping clusters of NMR lines pose a major challenge in resolving signature frequencies for individual molecules. While homonuclear decoupling techniques produce much simplified pure shift spectra, they often affect sensitivity. Conversion of typical NMR spectra to pure shift spectra by signal processing without a priori knowledge about the coupling patterns is essential for accurate analysis. We developed a super-resolved wavelet packet transform based 1H NMR spectroscopy that can be used in high-throughput studies to reliably decouple individual constituents of small molecule mixtures. We demonstrate the efficacy of the method on the model mixtures of saccharides and amino acids in the presence of significant noise

Analysis of Small-Molecule Mixtures by Super-Resolved ¹H NMR Spectroscopy

Analysis of small molecules is essential to metabolomics, natural products, drug discovery, food technology, and many other areas of interest. Current barriers preclude from identifying the constituent molecules in a mixture as overlapping clusters of NMR lines pose a major challenge in resolving signature frequencies for individual molecules. While homonuclear decoupling techniques produce much simplified pure shift spectra, they often affect sensitivity. Conversion of typical NMR spectra to pure shift spectra by signal processing without a priori knowledge about the coupling patterns is essential for accurate analysis. We developed a super-resolved wavelet packet transform based 1H NMR spectroscopy that can be used in high-throughput studies to reliably decouple individual constituents of small molecule mixtures. We demonstrate the efficacy of the method on the model mixtures of saccharides and amino acids in the presence of significant noise