Searching low-energy conformers of neutral and protonated di-, tri-, and tetra-glycine using first-principles accuracy assisted by the use of neural network potentials-Reference-Cited by-同舟云学术

Searching low-energy conformers of neutral and protonated di-, tri-, and tetra-glycine using first-principles accuracy assisted by the use of neural network potentials

Published:2024 Issue:14 Volume:26 Page:11126-11139
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Dong Hieu Cao¹²³,Hsu Po-Jen¹^ORCID,Kuo Jer-Lai¹²³⁴^ORCID

Affiliation:

1. Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, 10617, Taiwan

2. Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 11529, Taiwan

3. International Graduate Program of Molecular Science and Technology (NTU-MST), National Taiwan University, Taipei 10617, Taiwan

4. Department of Chemistry, National Tsing Hua University, Hsinchu 30013, Taiwan

Abstract

Application of neural network potentials accelerate the discovery of low-energy conformers of peptides to understand how the interplay of different interactions lead to their three-dimensional structures.

Funder

National Science and Technology Council

Academia Sinica

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/CP/D3CP05659G

Reference43 articles.

1. Gas-Phase Infrared Spectroscopy of Neutral Peptides: Insights from the Far-IR and THz Domain

2. Neutral Peptides in the Gas Phase: Conformation and Aggregation Issues

3. In-depth structural analysis of glycans in the gas phase

4. Isomer-Specific IR–IR Double Resonance Spectroscopy of D2-Tagged Protonated Dipeptides Prepared in a Cryogenic Ion Trap

5. Modeling Anharmonic Effects in the Vibrational Spectra of High-Frequency Modes