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Improving the Brightness of Pyronin Fluorophore Systems through Quantum-Mechanical Predictions.

ABSTRACT: The pyronin class of fluorophores serves a critical role in numerous imaging applications, particularly involving preferential staining of RNA through base pair intercalation. Despite this important role in molecular staining applications, the same set of century-old pyronins (i.e., pyronin Y (PY) and pyronin B (PB)), which possess relatively low fluorophore brightness, are still predominantly being used due to the lack of methodology for generating enhanced variants. Here, we use TD-DFT calculations of interconversion energies between structures on the S₁ surface as a preliminary means to evaluate fluorophore brightness for a proposed set of pyronins containing variable substitution patterns at the 2, 3, 6, and 7 positions. Using a nucleophilic aromatic substitution/hydride addition approach, we synthesized the same set of pyronins and demonstrate that quantum-mechanical computations are useful for predicting fluorophore performance. We produced the brightest series of pyronin fluorophores described to date, which possess considerable gains over PY and PB.

SUBMITTER: Walls B

PROVIDER: S-EPMC10543078 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Improving the Brightness of Pyronin Fluorophore Systems through Quantum-Mechanical Predictions.

Walls Brandon B Suleiman Olabisi O Arambula Carlos C Hall Alyssa A Adeyiga Olajumoke O Boumelhem Fadel F Koh Jungjae J Odoh Samuel O SO Woydziak Zachary R ZR

The journal of physical chemistry letters 20220830 35

The pyronin class of fluorophores serves a critical role in numerous imaging applications, particularly involving preferential staining of RNA through base pair intercalation. Despite this important role in molecular staining applications, the same set of century-old pyronins (i.e., pyronin Y (PY) and pyronin B (PB)), which possess relatively low fluorophore brightness, are still predominantly being used due to the lack of methodology for generating enhanced variants. Here, we use TD-DFT calcula ...[more]

PMID: 36040023

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Project description:Conspectus Quantum mechanics (QM) has revolutionized our understanding of the structure and reactivity of small molecular systems. Given the tremendous impact of QM in this research area, it is attractive to believe that this could also be brought into the biological realm where systems of a few thousand atoms and beyond are routine. Applying QM methods to biological problems brings an improved representation to these systems by the direct inclusion of inherently QM effects such as polarization and charge transfer. Because of the improved representation, novel insights can be gleaned from the application of QM tools to biomacromolecules in aqueous solution. To achieve this goal, the computational bottlenecks of QM methods had to be addressed. In semiempirical theory, matrix diagonalization is rate limiting, while in density functional theory or Hartree-Fock theory electron repulsion integral computation is rate-limiting. In this Account, we primarily focus on semiempirical models where the divide and conquer (D&C) approach linearizes the matrix diagonalization step with respect to the system size. Through the D&C approach, a number of applications to biological problems became tractable. Herein, we provide examples of QM studies on biological systems that focus on protein solvation as viewed by QM, QM enabled structure-based drug design, and NMR and X-ray biological structure refinement using QM derived restraints. Through the examples chosen, we show the power of QM to provide novel insights into biological systems, while also impacting practical applications such as structure refinement. While these methods can be more expensive than classical approaches, they make up for this deficiency by the more realistic modeling of the electronic nature of biological systems and in their ability to be broadly applied. Of the tools and applications discussed in this Account, X-ray structure refinement using QM models is now generally available to the community in the refinement package Phenix. While the power of this approach is manifest, challenges still remain. In particular, QM models are generally applied to static structures, so ways in which to include sampling is an ongoing challenge. Car-Parrinello or Born-Oppenheimer molecular dynamics approaches address the short time scale sampling issue, but how to effectively use QM to study phenomenon covering longer time scales will be the focus of future research. Finally, how to accurately and efficiently include electron correlation effects to facilitate the modeling of, for example, dispersive interactions, is also a major hurdle that a broad range of groups are addressing The use of QM models in biology is in its infancy, leading to the expectation that the most significant use of these tools to address biological problems will be seen in the coming years. It is hoped that while this Account summarizes where we have been, it will also help set the stage for future research directions at the interface of quantum mechanics and biology.

Dataset Information

Improving the Brightness of Pyronin Fluorophore Systems through Quantum-Mechanical Predictions.

Publications

Improving the Brightness of Pyronin Fluorophore Systems through Quantum-Mechanical Predictions.

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