Oligomers of Diphenylalanine Interrogated by Cold Ion Spectroscopy and Neural Network-based Conformational Search

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL Physical Chemistry Chemical Physics Pub Date : 2024-10-16 DOI:10.1039/d4cp03476g
Vladimir Kopysov, Rusland Yamaletdinov, Oleg V Boyarkin
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Abstract

Diphenylalanine (Phe2) is the primary building block of many self-assembling nanostructures that are important in biology and material science. Understanding the detailed mechanism of their formation requires knowledge of the structural motives the smallest oligomers attain at the very first steps of the process. Here we, first, employ high-resolution mass spectrometry to assign protonated Phe2 and its 2- to 13-unit oligomers formed in the gas phase from solution by electrospray ionization and then use cold ion spectroscopy to record their UV and, for monomer, dimer and hexamer, IR spectra. UV spectroscopy suggests the likely lack of specific strong proton- interactions in the oligomers larger than octamer, implying their certain structural stabilization. The IR spectroscopy and quantum chemical calculations, enhanced by neural network-based conformational search, jointly have determined the lowest-energy structures of the Phe2 monomer and dimer.
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通过冷离子光谱和基于神经网络的构象搜索对二苯丙氨酸的低聚物进行探测
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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