Energy landscapes of a hairpin peptide including NMR chemical shift restraints

文献信息

发布日期 2015-07-17
DOI 10.1039/C5CP01259G
影响因子 3.676
作者

Joanne M. Carr, Chris S. Whittleston, David C. Wade, David J. Wales


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摘要

Methods recently introduced to improve the efficiency of protein structure prediction simulations by adding a restraint potential to a molecular mechanics force field introduce additional input parameters that can affect the performance. Here we investigate the changes in the energy landscape as the relative weight of the two contributions, force field and restraint potential, is systematically altered, for restraint functions constructed from calculated nuclear magnetic resonance chemical shifts. Benchmarking calculations were performed on a 12-residue peptide, tryptophan zipper 1, which features both secondary structure (a β-hairpin) and specific packing of tryptophan sidechains. Basin-hopping global optimization was performed to assess the efficiency with which lowest-energy structures are located, and the discrete path sampling approach was employed to survey the energy landscapes between unfolded and folded structures. We find that inclusion of the chemical shift restraints improves the efficiency of structure prediction because the energy landscape becomes more funnelled and the proportion of local minima classified as native increases. However, the funnelling nature of the landscape is reduced as the relative contribution of the chemical shift restraint potential is increased past an optimal value.

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Contents

Front/Back Matter

DOI: 10.1039/B501283J

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来源期刊

Physical Chemistry Chemical Physics

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.

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