A systematic study of the valence electronic structure of cyclo(Gly-Phe), cyclo(Trp-Tyr) and cyclo(Trp-Trp) dipeptides in gas phase
Elena Molteni (1, 2), Giuseppe Mattioli (1), Paola Alippi (1),, Lorenzo Avaldi (1), Paola Bolognesi (1), Laura Carlini (1), Federico Vismarra, (3, 4), Yingxuan Wu (3, 4), Rocio Borrego Varillas (4), Mauro Nisoli (3, and 4), Manjot Singh (5), Mohammadhassan Valadan (5, 6)

TL;DR
This study combines experimental gas-phase valence photoelectron spectroscopy with advanced theoretical calculations to analyze the electronic structure of three cyclic dipeptides, providing insights into their conformations and electronic correlations.
Contribution
It introduces an integrated experimental-theoretical approach using multiple computational methods to characterize dipeptide electronic structures in the gas phase.
Findings
Spectra are assigned to specific conformers.
Electronic correlation effects are analyzed.
Theoretical methods are validated against experimental data.
Abstract
The electronic energy levels of cyclo(Glycine-Phenylalanine), cyclo(Tryptophan-Tyrosine) and cyclo(Tryptophan-Tryptophan) dipeptides are investigated with a joint experimental and theoretical approach. Experimentally, valence photoelectron spectra in the gas phase are measured using VUV radiation. Theoretically, we first obtain low-energy conformers through an automated conformer-rotamer ensemble sampling scheme based on tight-binding simulations. Then, different first principles computational schemes are considered to simulate the spectra: Hartree-Fock (HF), density functional theory (DFT) within the B3LYP approximation, the quasi--particle GW correction, and the quantum-chemistry CCSD method. Theory allows to assign the main features of the spectra. A discussion on the role of electronic correlation is provided, by comparing computationally cheaper DFT scheme (and GW) results with the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
