Probing Columnar Discotic Liquid Crystals by EPR Spectroscopy with a Rigid-Core Nitroxide Spin Probe

Discotics studied by EPR: The application of EPR spectroscopy to columnar discotic liquid crystals using a novel rigid-core nitroxide spin probe (see picture) is possible. EPR spectra measured at different temperatures across three phases of hexakis(n-hexyloxy)triphenylene show a strong sensitivity to the phase composition, molecular rotational dynamics, and columnar order

The spatial effect of protein deuteration on nitroxide spin-label relaxation:implications for EPR distance measurement

This work was supported by a Wellcome Trust Senior Fellowship (095062) to T.O.-H. The Authors would also like to acknowledge funding from The MRC – United Kingdom, Grant G1100021.Pulsed electron-electron double resonance (PELDOR) coupled with site-directed spin labeling is a powerful technique for the elucidation of protein or nucleic acid, macromolecular structure and interactions. The intrinsic high sensitivity of electron paramagnetic resonance enables measurement on small quantities of bio-macromolecules, however short relaxation times impose a limit on the sensitivity and size of distances that can be measured using this technique. The persistence of the electron spin-echo, in the PELDOR experiment, is one of the most crucial limitations to distance measurement. At a temperature of around 50 K one of the predominant factors affecting persistence of an echo, and as such, the sensitivity and measurable distance between spin labels, is the electron spin echo dephasing time (Tm). It has become normal practice to use deuterated solvents to extend Tm and recently it has been demonstrated that deuteration of the underlying protein significantly extends Tm. Here we examine the spatial effect of segmental deuteration of the underlying protein, and also explore the concentration and temperature dependence of highly deuterated systems.Publisher PDFPeer reviewe

Investigating the dynamic nature of the ABC transporters: ABCB1 and MsbA as examples for the potential synergies of MD theory and EPR applications

ABC transporters are primary active transporters found in all kingdoms of life. Human multidrug resistance transporter ABCB1, or P-glycoprotein, has an extremely broad substrate spectrum and confers resistance against chemotherapy drug treatment in cancer cells. The bacterial ABC transporter MsbA is a lipid A flippase and a homolog to the human ABCB1 transporter, with which it partially shares its substrate spectrum. Crystal structures of MsbA and ABCB1 have been solved in multiple conformations, providing a glimpse into the possible conformational changes the transporter could be going through during the transport cycle. Crystal structures are inherently static, while a dynamic picture of the transporter in motion is needed for a complete understanding of transporter function. Molecular dynamics (MD) simulations and electron paramagnetic resonance (EPR) spectroscopy can provide structural information on ABC transporters, but the strength of these two methods lies in the potential to characterise the dynamic regime of these transporters. Information from the two methods is quite complementary. MD simulations provide an all atom dynamic picture of the time evolution of the molecular system, though with a narrow time window. EPR spectroscopy can probe structural, environmental and dynamic properties of the transporter in several time regimes, but only through the attachment sites of an exogenous spin label. In this review the synergistic effects that can be achieved by combining the two methods are highlighted, and a brief methodological background is also presented

Molecular structure refinement by direct fitting of atomic coordinates to experimental ESR spectra

An attempt is made to bypass spectral analysis and fit internal coordinates of radicals directly to experimental liquid- and solid-state electron spin resonance (ESR) spectra. We take advantage of the recently introduced large-scale spin dynamics simulation algorithms and of the fact that the accuracy of quantum mechanical calculations of ESR parameters has improved to the point of quantitative correctness. Partial solutions are offered to the local minimum problem in spectral fitting and to the problem of spin interaction parameters (hyperfine couplings, chemical shifts, etc.) being very sensitive to distortions in molecular geometry.Comment: Submitted for publicatio

Signal transduction in light-oxygen-voltage receptors lacking the adduct- forming cysteine residue

Light–oxygen–voltage (LOV) receptors sense blue light through the photochemical generation of a covalent adduct between a flavin-nucleotide chromophore and a strictly conserved cysteine residue. Here we show that, after cysteine removal, the circadian-clock LOV-protein Vivid still undergoes light-induced dimerization and signalling because of flavin photoreduction to the neutral semiquinone (NSQ). Similarly, photoreduction of the engineered LOV histidine kinase YF1 to the NSQ modulates activity and downstream effects on gene expression. Signal transduction in both proteins hence hinges on flavin protonation, which is common to both the cysteinyl adduct and the NSQ. This general mechanism is also conserved by natural cysteine-less, LOV-like regulators that respond to chemical or photoreduction of their flavin cofactors. As LOV proteins can react to light even when devoid of the adduct- forming cysteine, modern LOV photoreceptors may have arisen from ancestral redox-active flavoproteins. The ability to tune LOV reactivity through photoreduction may have important implications for LOV mechanism and optogenetic applications

Base-specific spin-labeling of RNA for structure determination

To facilitate the measurement of intramolecular distances in solvated RNA systems, a combination of spin-labeling, electron paramagnetic resonance (EPR), and molecular dynamics (MD) simulation is presented. The fairly rigid spin label 2,2,5,5-tetramethyl-pyrrolin-1-yloxyl-3-acetylene (TPA) was base and site specifically introduced into RNA through a Sonogashira palladium catalyzed crosscoupling on column. For this purpose 5-iodouridine, 5-iodo-cytidine and 2-iodo-adenosine phosphoramidites were synthesized and incorporated into RNA-sequences. Application of the recently developed ACE (R) chemistry presented the main advantage to limit the reduction of the nitroxide to an amine during the oligonucleotide automated synthesis and thus to increase substantially the reliability of the synthesis and the yield of labeled oligonucleotides. 4-Pulse Electron Double Resonance (PELDOR) was then successfully used to measure the intramolecular spin–spin distances in six doubly labeled RNA-duplexes. Comparison of these results with our previous work on DNA showed that A- and B-Form can be differentiated. Using an all-atom force field with explicit solvent, MD simulations gave results in good agreement with the measured distances and indicated that the RNA A-Form was conserved despite a local destabilization effect of the nitroxide label. The applicability of the method to more complex biological systems is discussed

A facile method for attaching nitroxide spin labels at the 5′ terminus of nucleic acids†

In site-directed spin labeling (SDSL), a nitroxide moiety containing a stable, unpaired electron is covalently attached to a specific site within a macromolecule, and structural and dynamic information at the labeling site is obtained via electron paramagnetic resonance (EPR) spectroscopy. Successful SDSL requires efficient site-specific incorporation of nitroxides. Work reported here presents a new method for facile nitroxide labeling at the 5′ terminus of nucleic acids of arbitrary sizes. T4-polynucleotide kinase was used to enzymatically substitute a phosphorothioate group at the 5′ terminus of a nucleic acid, and the resulting phosphorothioate was then reacted with an iodomethyl derivative of a nitroxide. The method was successfully demonstrated on both chemically synthesized and naturally occurring nucleic acids. The attached nitroxides reported duplex formation as well as tertiary folding of nucleic acids, indicating that they serve as a valid probe in nucleic acid studies

Site-directed spin labeling measurements of nanometer distances in nucleic acids using a sequence-independent nitroxide probe

In site-directed spin labeling (SDSL), local structural and dynamic information is obtained via electron paramagnetic resonance (EPR) spectroscopy of a stable nitroxide radical attached site-specifically to a macromolecule. Analysis of electron spin dipolar interactions between pairs of nitroxides yields the inter-nitroxide distance, which provides quantitative structural information. The development of pulse EPR methods has enabled such distance measurements up to 70 Å in bio-molecules, thus opening up the possibility of SDSL global structural mapping. This study evaluates SDSL distance measurement using a nitroxide (designated as R5) that can be attached, in an efficient and cost-effective manner, to a phosphorothioate backbone position at arbitrary DNA or RNA sequences. R5 pairs were attached to selected positions of a dodecamer DNA duplex with a known NMR structure, and eight distances, ranging from 20 to 40 Å, were measured using double electron-electron resonance (DEER). The measured distances correlated strongly (R(2) = 0.98) with the predicted values calculated based on a search of sterically allowable R5 conformations in the NMR structure, thus demonstrating accurate distance measurements using R5. Furthermore, distance measurement in a 42 kD DNA was demonstrated. The results establish R5 as a sequence-independent probe for global structural mapping of DNA and DNA–protein complexes

Neural network interpretation techniques for analysis of histological images of breast abnormalities

Background. Neural networks are actively used in digital pathology to analyze histological images and support medical decision-making. A common approach is to solve the classification problem, where only class labels are the only model responses. However, one should understand which areas of the image have the most significant impact on the model's response. Machine learning interpretation techniques help solve this problem. Aim. To study the consistency of different methods of neural network interpretation when classifying histological images of the breast and to obtain an expert assessment of the results of the evaluated methods. Materials and methods. We performed a preliminary analysis and pre-processing of the existing data set used to train pre-selected neural network models. The existing methods of visualizing the areas of attention of trained models on easy-to-understand data were applied, followed by verification of their correct use. The same neural network models were trained on histological data, and the selected interpretation methods were used to systematize histological images, followed by the evaluation of the results consistency and an expert assessment of the results. Results. In this paper, several methods of interpreting machine learning are studied using two different neural network architectures and a set of histological images of breast abnormalities. Results of ResNet18 and ViT-B-16 models training on a set of histological images on the test sample: accuracy metric 0.89 and 0.89, ROC_AUC metric 0.99 and 0.96, respectively. The results were also evaluated by an expert using the Label Studio tool. For each pair of images, the expert was asked to select the most appropriate answer ("Yes" or "No") to the question: "The highlighted areas generally correspond to the Malignant class." The "Yes" response rate for the ResNet_Malignant category was 0.56; for ViT_Malignant, it was 1.0. Conclusion. Interpretability experiments were conducted with two different architectures: the ResNet18 convolutional network and the ViT-B-16 attention-enhanced network. The results of the trained models were visualized using the GradCAM and Attention Rollout methods, respectively. First, experiments were conducted on a simple-to-interpret dataset to ensure they were used correctly. The methods are then applied to the set of histological images. In easy-to-understand images (cat images), the convolutional network is more consistent with human perception; on the contrary, in histological images of breast cancer, ViT-B-16 provided results much more similar to the expert's perception