Publications

Peer-Reviewed Articles

1. Ellen Koag, Simon G. Hulse, Gregory L. Helms, Kevin M. Call, Michael F. Summers, Jan Marchant and Bruce A. Johnson. "NMR data processing, visualization, analysis and structure calculation with NMRFx". In: Communications Chemistry. 8 (2025), p. 400.
   DOI: 10.1038/s42004-025-01812-8
   paper.pdf si.pdf
   Abstract

   NMR spectroscopy is applied in many scientific disciplines to derive chemical, structural, and dynamical insights into molecular systems. The utility of the technique depends on robust computational protocols for processing, visualizing, and analyzing data acquired using a wide range of experiments. Here we introduce NMRFx, a software application that integrates and augments features of our existing NMRViewJ and NMRFx Processor applications. NMRFx facilitates data processing, peak picking and assignment, chemical shift prediction, molecular structure calculation, and beyond, through a high-speed, feature-rich graphical user interface. This paper describes advances over existing software and presents a series of case studies that demonstrate its utility in diverse contexts. These case studies include the assignments of the protein ubiquitin, a 36 nucleotide RNA construct, and the natural product taccalonolide E, as well as a metabolomics study of triacylglyceride production in algal cells.

2. Simon G. Hulse, Mathias Nilsson, Gareth A. Morris and Mohammadali Foroozandeh. "Full-Signal Ultrahigh-Resolution NMR by Parameter Estimation". In: Analytical Chemistry. 97 (2025), p. 25020-25025.
   DOI: 10.1021/acs.analchem.5c03446
   paper.pdf si.pdf
   Abstract

   Pure shift NMR spectra, in which multiplet structure is suppressed, are widely used but exact a high price in sensitivity. Here we present CUPID (Computer-assisted Undiminished-sensitivity Protocol for Ideal Decoupling), which uses parametric estimation to produce pure shift NMR spectra from easily acquired 2D J-resolved (2DJ) data sets. Unlike previous practical methods for broadband pure shift NMR, it makes use of all of the available signal. CUPID is therefore effective even at sample concentrations where current methods are too insensitive to yield usable spectra. As an additional benefit, the estimation method used allows the extraction of individual multiplet structures from overlapping spectra. CUPID is freely available through NMR Estimation in Python (NMR-EsPy), an open-source package with a simple-to-use API, and comes with a graphical user interface that is accessible via Topspin, a widely used NMR software platform.

3. Simon G. Hulse and Mohammadali Foroozandeh. "Newton meets Ockham: Parameter estimation and model selection of NMR data with NMR-EsPy". In: Journal of Magnetic Resonance. 338 (2022), p. 107173.
   DOI: 10.1016/j.jmr.2022.107173
   paper.pdf si.pdf
   Abstract

   We present NMR-EsPy (NMR Estimation in Python), a versatile, simple-to-use Python package for estimating the signal parameters that describe one-dimensional time-domain NMR data. The software is fully integrated into Topspin, a widely used NMR platform, and comes with a Graphical User Interface, allowing users unfamiliar with the underlying theory and/or Python programming to access the full functionality of the software package. NMR-EsPy utilises Newton's method, an iterative non-linear programming technique. By including the variance of oscillator phases in the optimization, NMR-EsPy can generate parsimonious parameter estimates, giving NMR users access to meaningful quantitative information. This principle is easily extendable to study specific regions of an NMR spectrum to reduce computational cost. The complete mathematical treatment along with examples of the implementation of the estimation routine are presented.

Theses

1. Simon G. Hulse. "Estimation of NMR signals in the time domain: methodology, applications and software". PhD Thesis. University of Oxford, 2023.
   DOI: 10.5287/ora-bpdg8rr9k
   thesis.pdf
   Abstract

   Nucler magnetic resonance (NMR) spectroscopy is an analytical technique employed in many scientific disciplines that is able to provide insights into the structures and dynamics of chemical species. To maximise the utility of NMR, appropriate data treatment and analysis is necessary. The conventional route to extracting quantitative information from the raw experimental data—the free induction decay (FID)—is to convert it to an NMR spectrum, through application of the Fourier Transform (FT). NMR spectra provide a human-interpretable representation of data; trained practitioners are able to rationalise the appearance of a given spectrum by mapping its component peaks to chemical environments in the sample from which the dataset was acquired. However, the FT suffers from poor resolution, with peaks of similar frequencies exhibiting overlap. Disentangling the information associated with such peaks is not feasible using typical methods such as integrating user-defined regions of the spectrum.

   As an alternative approach, parametric estimation techniques aim to provide a detailed description of each signal which contributes to the FID. These methods have been shown to perform effectively even in scenarios where significant spectral peak overlap exists. This thesis focusses on the development of a parametric estimation method for the analysis of FIDs derived from solution-state NMR experiments. The guiding principle behind the method is that it should require as little user input as possible, while being able to provide accurate and reliable signal estimates. Beyond simply providing a breakdown of individual signal components, many useful applications may be realised when estimation techniques are employed. The initial motivation for this work was to develop a procedure for the generation of broadband homodecoupled (pure shift) NMR spectra with desirable properties from 2D J-resolved (2DJ) datasets. Furthermore, a means of analysing datasets such as those from inversion recovery, Carr-Purcell-Meiboom-Gill (CPMG), and diffusion experiments, in which each FID exhibits a variation in its amplitude, is presented. The last application described is a means of producing phased, ultra-broadband NMR spectra from an experiment comprising a single freqency-swept (chirp) excitation pulse.

   The methods presented in this thesis are incorporated into a software package written in the Python programming language, called NMR-EsPy, of which more information can be found at https://github.com/foroozandehgroup/NMR-EsPy.

2. Simon G. Hulse. "An Investigation of Relaxation Phenomena in I₃S Nuclear Spin Systems". MChem Thesis. University of Oxford, 2019.
   DOI: 10.5281/zenodo.14232500
   thesis.pdf
   Abstract

   NMR spectroscopy is a highly valuable technique for the characterisation of structure and dynamics of biomolecules. Despite this, the effects of relaxation limits the size of molecules that can be studied. Transverse Relaxation Optimised Spectroscopy (TROSY) is a method which has increased this limit, though there is a desire to push it even further. We believe that a TROSY experiment which probes ¹³CF₃ moieties could allow studies of macromolecules which are currently deemed too large, in the context of solution-state NMR. Such systems include membrane-bound proteins and virus particles.

   A novel relaxation theory is presented that is well-suited to describe ¹³CF₃ systems. Comparisons of relaxation behaviour between methyl and ¹³CF₃ groups were made using our theory. Our results indicate that magnetisations associated with ¹³CF₃ moieties relax at noticeably slower rates. This observation was determined to be driven largely by dipolar coupling effects, with the ¹⁹F chemical shift anisotropy also playing a significant role. These findings show that the development of a ¹³CF₃ TROSY experiment is a worthwhile pursuit, which could extend the scope of NMR. Validation of this theory was achieved via studies on a small ¹³CH₃-labelled molecule, present in a highly viscous medium. Although our theory described its relaxation well, the molecule was not effective at mimicking proteins.