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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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First-Principles Simulation of Dielectric Function in Biomolecules
The dielectric spectra of complex biomolecules reflect the molecular heterogeneity of the proteins and are particularly important for the calculations of electrostatic (Coulomb) and electrodynamic (van der Waals) interactions in protein physics. The dielectric response of the proteins can be decomposed into different components depending on the size, structure, composition, locality, and environment of the protein in general. We present a new robust simulation method anchored in rigorous ab initio quantum mechanical calculations of explicit atomistic models, without any indeterminate parameters to compute and gain insight into the dielectric spectra of small proteins under different conditions. We implement this methodology to a polypeptide RGD-4C (1FUV) in different environments, and the SD1 domain in the spike protein of SARS-COV-2. Two peaks at 5.2–5.7 eV and 14.4–15.2 eV in the dielectric absorption spectra are observed for 1FUV and SD1 in vacuum as well as in their solvated and salted models.
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- Award ID(s):
- 2028803
- PAR ID:
- 10321663
- Date Published:
- Journal Name:
- Materials
- Volume:
- 14
- Issue:
- 19
- ISSN:
- 1996-1944
- 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/10.3390/ma14195774
