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UV absorption is widely used for characterizing proteins structures. The mapping of UV spectra to atomic structure of proteins relies on expensive theoretical simulations, circumventing the heavy computational cost which involves repeated quantum-mechanical simulations of excited-state properties of many fluctuating protein geometries, which has been a long-time challenge. Here we show that a neural network machine-learning technique can predict electronic absorption spectra of N -methylacetamide (NMA), which is a widely used model system for the peptide bond. Using ground-state geometric parameters and charge information as descriptors, we employed a neural network to predict transition energies, ground-state, and transition dipole moments of many molecular-dynamics conformations at different temperatures, in agreement with time-dependent density-functional theory calculations. The neural network simulations are nearly 3,000× faster than comparable quantum calculations. Machine learning should provide a cost-effective tool for simulating optical properties of proteins.
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Experimental Assessment of the Electronic and Geometrical Structure of a Near-Infrared Absorbing and Highly Fluorescent Microbial Rhodopsin
The recently discovered Neorhodopsin (NeoR) exhibits absorption and emission maxima in the near-infrared spectral region, which together with the high fluorescence quantum yield makes it an attractive retinal protein for optogenetic applications. The unique optical properties can be rationalized by a theoretical model that predicts a high charge transfer character in the electronic ground state (S0) which is otherwise typical of the excited state S1 in canonical retinal proteins. The present study sets out to assess the electronic structure of the NeoR chromophore by resonance Raman (RR) spectroscopy since frequencies and relative intensities of RR bands are controlled by the ground and excited state’s properties. The RR spectra of NeoR differ dramatically from those of canonical rhodopsins but can be reliably reproduced by the calculations carried out within two different structural models. The remarkable agreement between the experimental and calculated spectra confirms the consistency and robustness of the theoretical approach.
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- Award ID(s):
- 2102619
- PAR ID:
- 10555126
- Publisher / Repository:
- The American Chemical Society
- Date Published:
- Journal Name:
- The Journal of Physical Chemistry Letters
- Volume:
- 14
- Issue:
- 41
- ISSN:
- 1948-7185
- Page Range / eLocation ID:
- 9291 to 9295
- Subject(s) / Keyword(s):
- Chromophores drug resistance electronic structure peptides proteins photoisomerization solvation dynamics and solvent effects
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1021/acs.jpclett.3c02167
