Characterizing gaseous peptide structure with action-EET and simulated annealing

Literature Information

Publication Date 2015-04-30
DOI 10.1039/C5CP01617G
Impact Factor 3.676
Authors

Nathan G. Hendricks, Ryan R. Julian


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Abstract

Evaluation of biomolecular structure in the gas phase is challenging, but worthwhile due to advantages in sensitivity and speed relative to traditional condensed phase approaches. Herein, we demonstrate that a recently developed method utilizing energy transfer to establish distance constraints can be combined with molecular dynamics calculations to rapidly and accurately reveal gaseous peptide structures. Three peptides in various charge states are examined. The influence of increasing charge state on peptide structure is easily observed. The presence of multiple conformations can be detected. Furthermore, the method is demonstrated to aid the assignment of charge, which is frequently nontrivial for peptides containing numerous acidic and basic residues that could adopt a variety of conformers of equal charge state. Comparison with ion mobility reveals that many low energy structures that are distinguishable by distance constraints would not be resolvable by collision cross section. Action-EET is demonstrated to be a powerful new tool for structure elucidation.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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