On the mechanism of spontaneous thiol–disulfide exchange in proteins

文献信息

发布日期 2018-05-24

DOI 10.1039/C8CP01325J

影响因子 3.676

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摘要

The thiol–disulfide exchange reaction in model systems and small peptides was investigated by means of a combined QM/MM metadynamics scheme. The free energy landscapes of these systems were generated, providing the structures of reactants and products with atomic detail, as well as the heights of free energy barriers (or, activation energies) opposing the spontaneous exchange. A QM/MM scheme with purely classical water turned out to be an efficient and accurate compromise solution. The calculations yielded the expected symmetric trisulfide transition state at S–S distances of 2.7 Å, interestingly, with a slight deviation from linearity at an S–S–S angle of 165°. The structure of the transition state as well as the free energy barrier were very similar for the intramolecular thiol–disulfide reactions in model peptides. While CXC disulfide bonds were found sterically unfavorable, CXXC were favored over longer-range disulfide bonds along the peptide backbone, in line with the high abundance of CXXC motifs in redox proteins.

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来源期刊

Physical Chemistry Chemical Physics

CiteScore: 5.5

自引率: 10.3%

年发文量: 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.