Unraveling the Structure-Spectrum Relationship of Yeast Phenylalanine Transfer RNA: Insights from Theoretical Modeling of Infrared Spectroscopy
Yeast phenylalanine tRNA (tRNA<sup>phe</sup>) is a paradigmatic model in structural biology. In this work, we combine molecular dynamics simulations and spectroscopy modeling to establish a direct link between its structure, conformational dynamics, and infrared (IR) spectra. Employing recently developed vibrational frequency maps and coupling models, we apply a mixed quantum/classical treatment of the line shape theory to simulate the IR spectra of tRNA<sup>phe</sup> in the 1600-1800 cm<sup>-1</sup> region across its folded and unfolded conformations and under varying concentrations of Mg<sup>2+</sup> ions. The predicted IR spectra of folded and unfolded tRNA<sup>phe</sup> are in good agreement with experimental measurements, validating our theoretical framework. We then elucidate how the characteristic L-shaped tertiary structure of the tRNA and its modulation in response to diverse chemical environments give rise to distinct IR absorption peaks and line shapes. These calculations effectively bridge IR spectroscopy experiments and atomistic molecular simulations, unraveling the molecular origins of the observed IR spectra of tRNA<sup>phe</sup>. This work presents a robust theoretical protocol for modeling the IR spectroscopy of nucleic acids, which will facilitate its application as a sensitive probe for detecting the fluctuating secondary and tertiary structures of these essential biological macromolecules.
Authors
- Lu Wang (ORCID: https://orcid.org/0000-0001-6230-1835)
- Qian Cheng (ORCID: https://orcid.org/0000-0003-4592-5915)
Institutions
- Rutgers, The State University of New Jersey (US)
- Quantitative BioSciences (US)
Publication Details
- Journal
- Biochemistry
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1021/acs.biochem.4c00236
- Citations
- 2
- Primary Topic
- RNA and protein synthesis mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- National Institutes of Health
- Office of Advanced Research Computing, Rutgers, The State University of New Jersey
- National Institute of General Medical Sciences