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Peptide nucleic acids (PNAs) are a promising group of synthetic analogues of DNA and RNA that offer several distinct advantages over the naturally occurring nucleic acids for applications in biosensing, drug delivery, and nanoelectronics. Because of its structural differences from DNA/RNA, methods to analyze and assess the structure, conformations, and dynamics are needed. In this work, we develop synergistic techniques for the study of the PNA conformation. We use CuQ2, a Cu(II) complex with 8-hydroxyquinoline (HQ), as an alternative base pair and as a spin label in electron paramagnetic resonance (EPR) distance methods. We use molecular dynamics (MD) simulations with newly developed force field parameters for the spin labels to interpret the distance constraints determined by EPR. We complement these methods by UV–vis and circular dichroism measurements and assess the efficacy of the Cu(II) label on a PNA duplex whose backbone is based on aminoethylglycine and a duplex with a hydroxymethyl backbone modification. We show that the Cu(II) label functions efficiently within the standard PNA and the hydroxymethyl-modified PNA and that the MD parameters may be used to accurately reproduce our EPR findings. Through the combination of EPR and MD, we gain new insights into the PNA structure and conformations as well as into the mechanism of orientational selectivity in Cu(II) EPR at X-band. These results present for the first time a rigid Cu(II) spin label used for EPR distance measurements in PNA and the accompanying MD force fields for the spin label. Our studies also reveal that the spin labels have a low impact on the structure of the PNA duplexes. The combined MD and EPR approach represents an important new tool for the characterization of the PNA duplex structure and provides valuable information to aid in the rational application of PNA at large.
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Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics
Abstract Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large‐amplitude conformational transition, a coarse‐grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE‐MD including all intermediate states.
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- PAR ID:
- 10486873
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- ChemPlusChem
- Volume:
- 89
- Issue:
- 1
- ISSN:
- 2192-6506
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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