Preprints  

The 20 genetically encoded amino acids provide the basis for most proteins and peptides that make up the machinery of life. This limited repertoire is vastly expanded by the introduction of non-canonical amino acids (ncAAs). To study the structure of a protein containing an ncAA requires new computational representation that are compatible with existing modelling software. We have developed an online tool for this, to aid future structural studies of this class of complex biopolymers.

Recent advances in machine learning have opened new opportunities toward the automated analysis and spectral reconstruction of highly complex NMR spectra, including ones encountered in metabolomics. We demonstrate the combined power of the deep neural network “DEEP Picker 1D” and “Voigt Fitter1D” software for the quantitative streamlined analysis of 1D 1H NMR spectra extending the reach of a wide range of NMR applications.

Light-induced pulsed dipolar EPR spectroscopy (PDS) is an emerging field that uses photoexcited triplet states to determine distance restraints in the nanometer range. So far, light-induced PDS data have been analyzed with methods that were developed for techniques that do not invoke triplets. Here, we provide a new theoretical description that takes the full nature of the triplet state into account and demonstrate that it leads to more accurate fits of experimental data.

R-PDLF NMR spectroscopy is a powerful method to obtain molecular structural information from biological membrane models. However, the conventional analysis of the experiments relies on a Fourier transform in the indirect time domain preventing its application to complex samples. We propose a new methodology, namely to fit the indirect time-domain with simulations that account for RF inhomogeneity, making possible to study far more complex biological membranes than what has been done previously.

This Tutorial Paper shows how to simulate NMR spectra at zero- ultra low-field. The process is presented in detail, including the tricks that are usually omitted from research papers and assuming as little prior knowledge from the reader as possible. In this attempt to make NMR simulation approachable, the authors wish to pay a tribute to the late Prof. Konstantin L’vovich Ivanov.

Diffusion MRI is a clinically important tool for noninvasive detection of pathological conditions that lead to microscopic changes in cell and tissue structures, but suffers from interpretational ambiguities when applied to heterogeneous and disordered tissues comprising cells with multiple sizes, shapes, and orientations. We propose a simple scheme to encode the MRI signal with sufficient amount of information to resolve and study all properties simultaneously.

Nanometer distance measurements between spin labels by pulse EPR techniques yield structural information on the molecular level. Here, backed by experimental data, we derive a description for the total signal of the single frequency technique for refocusing dipolar couplings (SIFTER) showing how the different spin-spin interactions give rise to dipolar signal and background – the latter has thus far been unknown.

Providing evidence that proteins are dynamical molecules is a major contribution of solution NMR to structural biology. But the classical experiments to measure dynamics can only be applied to small proteins. This is regretful, because larger proteins often display conformational changes in which dynamics plays a functional role. We show here that dynamic information can be extracted from HSQC NMR spectra using a computational approach. Such spectra are widely available also for larger proteins.

We show here that information about protein molecular dynamics can be directly extracted out of a single NMR spectrum. Understanding protein dynamics is essential to understanding its function, energetics and biology. We hope that this contribution helps bring this insight to a much broader application field and audience community than previously possible.

The demonstration of the Finite Pulse Radio Frequency Driven Recoupling experiment was firstly published over the past 20 years. Since it has become one of the used experiments. In this article we consider that experiment using other theoretical and simulated approaches with respect to the previous works. These approaches help us to understand more clearly the influence of each part of that experiment and to see how exactly the spin system is evaluated during it.

We recently added 2D NMR spectroscopy to the well-established techniques able to obtain information on the process of unfolding using resonances of residues in the hydrophobic core of a protein. We asked whether a detailed analysis of the individual stability curves could provide additional site-specific information. By monitoring both cold and heat denaturation of individual residues we convincingly demonstrate that the two unfolding processes are intrinsically different.

Nowadays, almost all MRI technique used in clinical applications are based on a Fourier transformation of the raw data. Alternative non-Fourier magnetic resonance imaging techniques can offer some advantages under certain conditions. SPatio-temporal ENcoding (SPEN) is a non-Fourier method that usually employs frequency-swept radio frequency pulses and can give good images in inhomogeneous magnetic fields. In this work we show how one can improve this technique by using quadratic gradients.