Computer Modeling of Spin Labels: NASNOX, PRONOX, and ALLNOX

Revealing light-induced structural shifts in G-quadruplex-porphyrin complexes: a pulsed dipolar EPR study

The binding of G-quadruplex structures (G4s) with photosensitizers is of considerable importance in medicinal chemistry and drug discovery due to their promising potential in photodynamic therapy applications. G4s can experience structural changes as a result of ligand interactions and light exposure. Understanding these modifications is essential to uncover the fundamental biological roles of the complexes and optimize their therapeutic potential. The structural diversity of G4s makes it challenging to study their complexes with ligands, necessitating the use of various complementary methods to fully understand these interactions. In this study, we introduce, for the first time, the application of laser-induced dipolar EPR as a method to characterize G-quadruplex DNA complexes containing photosensitizers and to investigate light-induced structural modifications in these systems. To demonstrate the feasibility of this approach, we studied complexes of the human telomeric G-quadruplex (HTel-22) with cationic 5,10,15,20-tetrakis(1-methyl-4-pyridinio) porphyrin tetra(p-toluenesulfonate) (TMPyP4). In addition to showcasing a new methodology, we also aimed to provide insights into the mechanisms underlying photoinduced HTel-22/TMPyP4 structural changes, thereby aiding in the advancement of approaches targeting G4s in photodynamic therapy. EPR revealed G-quadruplex unfolding and dimer formation upon light exposure. Our findings demonstrate the potential of EPR spectroscopy for examining G4 complexes with photosensitizers and contribute to a better understanding of G4s' interactions with ligands under light.

A novel approach to modeling side chain ensembles of the bifunctional spin label RX

We introduce a novel approach to modeling side chain ensembles of bifunctional spin labels. This approach utilizes rotamer libraries to generate side chain conformational ensembles. Because the bifunctional label is constrained by two attachment sites, the label is split into two monofunctional rotamers which are first attached to their respective sites, then rejoined by a local optimization in dihedral space. We validate this method against a set of previously published experimental data using the bifunctional spin label, RX. This method is relatively fast and can readily be used for both experimental analysis and protein modeling, providing significant advantages over modeling bifunctional labels with molecular dynamics simulations. Use of bifunctional labels for site directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy dramatically reduces label mobility, which can significantly improve resolution of small changes in protein backbone structure and dynamics. Coupling the use of bifunctional labels with side chain modeling methods allows for improved quantitative application of experimental SDSL EPR data to protein modeling.

chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling

Here we introduce chiLife, a Python package for site-directed spin label (SDSL) modeling for electron paramagnetic resonance (EPR) spectroscopy, in particular double electron-electron resonance (DEER). It is based on in silico attachment of rotamer ensemble representations of spin labels to protein structures. chiLife enables the development of custom protein analysis and modeling pipelines using SDSL EPR experimental data. It allows the user to add custom spin labels, scoring functions and spin label modeling methods. chiLife is designed with integration into third-party software in mind, to take advantage of the diverse and rapidly expanding set of molecular modeling tools available with a Python interface. This article describes the main design principles of chiLife and presents a series of examples.

Comparative evaluation of spin-label modeling methods for protein structural studies

Site-directed spin-labeling electron paramagnetic resonance spectroscopy is a powerful technique for the investigation of protein structure and dynamics. Accurate spin-label modeling methods are essential to make full quantitative use of site-directed spin-labeling electron paramagnetic resonance data for protein modeling and model validation. Using a set of double electron-electron resonance data from seven different site pairs on maltodextrin/maltose-binding protein under two different conditions using five different spin labels, we compare the ability of two widely used spin-label modeling methods, based on accessible volume sampling and rotamer libraries, to predict experimental distance distributions. We present a spin-label modeling approach inspired by canonical side-chain modeling methods and compare modeling accuracy with the established methods.

Phosphorothioate-Based Site-Specific Labeling of Large RNAs for Structural and Dynamic Studies

Pulsed electron-electron double resonance (PELDOR) spectroscopy, X-ray scattering interferometry (XSI), and single-molecule Förster resonance energy transfer (smFRET) are molecular rulers that provide inter- or intramolecular pair-wise distance distributions in the nanometer range, thus being ideally suitable for structural and dynamic studies of biomolecules including RNAs. The prerequisite for such applications requires site-specific labeling of biomolecules with spin labels, gold nanoparticles, and fluorescent tags, respectively. Recently, site-specific labeling of large RNAs has been achieved by a combination of transcription of an expanded genetic alphabet containing A-T/G-C base pairs and NaM-TPT3 unnatural base pair (UBP) with post-transcriptional modifications at UBP bases by click chemistry or amine-NHS ester reactions. However, due to the bulky sizes of functional groups or labeling probes used, such strategies might cause structural perturbation and decrease the accuracy of distance measurements. Here, we synthesize an α-thiophosphorylated variant of rTPT3TP (rTPT3αS), which allows for post-transcriptional site-specific labeling of large RNAs at the internal α-phosphate backbone via maleimide-modified probes. Subsequent PELDOR, XSI, and smFRET measurements result in narrower distance distributions than labeling at the TPT3 base. The presented strategy provides a new route to empower the molecular rulers for structural and dynamic studies of large RNA and its complex.

Benchmark Test and Guidelines for DEER/PELDOR Experiments on Nitroxide-Labeled Biomolecules

Distance distribution information obtained by pulsed dipolar EPR spectroscopy provides an important contribution to many studies in structural biology. Increasingly, such information is used in integrative structural modeling, where it delivers unique restraints on the width of conformational ensembles. In order to ensure reliability of the structural models and of biological conclusions, we herein define quality standards for sample preparation and characterization, for measurements of distributed dipole-dipole couplings between paramagnetic labels, for conversion of the primary time-domain data into distance distributions, for interpreting these distributions, and for reporting results. These guidelines are substantiated by a multi-laboratory benchmark study and by analysis of data sets with known distance distribution ground truth. The study and the guidelines focus on proteins labeled with nitroxides and on double electron-electron resonance (DEER aka PELDOR) measurements and provide suggestions on how to proceed analogously in other cases.

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

Förster resonance energy transfer (FRET) and electron paramagnetic resonance (EPR) spectroscopy are complementary techniques for quantifying distances in the nanometer range. Both approaches are commonly employed for probing the conformations and conformational changes of biological macromolecules based on site-directed fluorescent or paramagnetic labeling. FRET can be applied in solution at ambient temperature and thus provides direct access to dynamics, especially if used at the single-molecule level, whereas EPR requires immobilization or work at cryogenic temperatures but provides data that can be more reliably used to extract distance distributions. However, a combined analysis of the complementary data from the two techniques has been complicated by the lack of a common modeling framework. Here, we demonstrate a systematic analysis approach based on rotamer libraries for both FRET and EPR labels to predict distance distributions between two labels from a structural model. Dynamics of the fluorophores within these distance distributions are taken into account by diffusional averaging, which improves the agreement with experiment. Benchmarking this methodology with a series of surface-exposed pairs of sites in a structured protein domain reveals that the lowest resolved distance differences can be as small as ∼0.25 nm for both techniques, with quantitative agreement between experimental and simulated transfer efficiencies within a range of ±0.045. Rotamer library analysis thus establishes a coherent way of treating experimental data from EPR and FRET and provides a basis for integrative structural modeling, including studies of conformational distributions and dynamics of biological macromolecules using both techniques.

DEER and RIDME Measurements of the Nitroxide-Spin Labelled Copper-Bound Amine Oxidase Homodimer from Arthrobacter Globiformis

In the study of biological structures, pulse dipolar spectroscopy (PDS) is used to elucidate spin-spin distances at nanometre-scale by measuring dipole-dipole interactions between paramagnetic centres. The PDS methods of Double Electron Electron Resonance (DEER) and Relaxation Induced Dipolar Modulation Enhancement (RIDME) are employed, and their results compared, for the measurement of the dipolar coupling between nitroxide spin labels and copper-II (Cu(II)) paramagnetic centres within the copper amine oxidase from Arthrobacter globiformis (AGAO). The distance distribution results obtained indicate that two distinct distances can be measured, with the longer of these at c.a. 5 nm. Conditions for optimising the RIDME experiment such that it may outperform DEER for these long distances are discussed. Modelling methods are used to show that the distances obtained after data analysis are consistent with the structure of AGAO.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00723-021-01321-6.

2'-Alkynyl spin-labelling is a minimally perturbing tool for DNA structural analysis

The determination of distances between specific points in nucleic acids is essential to understanding their behaviour at the molecular level. The ability to measure distances of 2-10 nm is particularly important: deformations arising from protein binding commonly fall within this range, but the reliable measurement of such distances for a conformational ensemble remains a significant challenge. Using several techniques, we show that electron paramagnetic resonance (EPR) spectroscopy of oligonucleotides spin-labelled with triazole-appended nitroxides at the 2' position offers a robust and minimally perturbing tool for obtaining such measurements. For two nitroxides, we present results from EPR spectroscopy, X-ray crystal structures of B-form spin-labelled DNA duplexes, molecular dynamics simulations and nuclear magnetic resonance spectroscopy. These four methods are mutually supportive, and pinpoint the locations of the spin labels on the duplexes. In doing so, this work establishes 2'-alkynyl nitroxide spin-labelling as a minimally perturbing method for probing DNA conformation.

Experimental Validation of the ALLNOX Program for Studying Protein-Nucleic Acid Complexes

Measurement of distances between spectroscopic labels (e.g., spin labels, fluorophores) attached to specific sites of biomolecules is an important method for studying biomolecular complexes. ALLNOX (Addition of Labels and Linkers) has been developed as a program to model interlabel distances based on an input macromolecule structure. Here, we report validation of ALLNOX using measured distances between nitroxide spin labels attached to specific sites of a protein-DNA complex. The results demonstrate that ALLNOX predicts average interspin distances that matched with values measured with pairs of labels attached at the protein and/or DNA. This establishes a solid foundation for using spin labeling in conjunction with ALLNOX to investigate complexes without high-resolution structures. With its high degree of flexibility for the label or the target biomolecule, ALLNOX provides a useful tool for investigating the structure-function relationship in a large variety of biological molecules.

The contribution of modern EPR to structural biology

Electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labelling is applicable to biomolecules and their complexes irrespective of system size and in a broad range of environments. Neither short-range nor long-range order is required to obtain structural restraints on accessibility of sites to water or oxygen, on secondary structure, and on distances between sites. Many of the experiments characterize a static ensemble obtained by shock-freezing. Compared with characterizing the dynamic ensemble at ambient temperature, analysis is simplified and information loss due to overlapping timescales of measurement and system dynamics is avoided. The necessity for labelling leads to sparse restraint sets that require integration with data from other methodologies for building models. The double electron–electron resonance experiment provides distance distributions in the nanometre range that carry information not only on the mean conformation but also on the width of the native ensemble. The distribution widths are often inconsistent with Anfinsen's concept that a sequence encodes a single native conformation defined at atomic resolution under physiological conditions.

MMM: A toolbox for integrative structure modeling

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.