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Falk Hoffmann

Researcher at Ruhr University Bochum

Publications -  14
Citations -  157

Falk Hoffmann is an academic researcher from Ruhr University Bochum. The author has contributed to research in topics: Computer science & Relaxation (NMR). The author has an hindex of 5, co-authored 9 publications receiving 75 citations. Previous affiliations of Falk Hoffmann include Forschungszentrum Jülich.

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Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields.

TL;DR: It is shown that an accurate description of the methyl dynamics requires reparametrization of the potential energy barriers of methyl group rotation in the AMBER ff99SB*-ILDN force field (and related parameter sets), and that the TIP4P/2005 solvation model yields overall tumbling correlation times that are in close agreement with experimental data.
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Narrowing the gap between experimental and computational determination of methyl group dynamics in proteins

TL;DR: It is found that properly accounting for anisotropic protein tumbling is an important factor to improve the match between NMR and MD in terms of methyl axis order parameters, spectral densities, and relaxation rates.
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Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers.

TL;DR: Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations even now display very good agreement with the experiment.
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Fitting Side-Chain NMR Relaxation Data Using Molecular Simulations.

TL;DR: In this article, an approach to integrate side-chain NMR relaxation measurements with molecular dynamics simulations to study the structure and dynamics of protein motions is presented, which can be used to find a set of trajectories that are in agreement with relaxation measurements.
Posted ContentDOI

Fitting side-chain NMR relaxation data using molecular simulations

TL;DR: An approach to integrate side chain NMR relaxation measurements with molecular dynamics simulations to study the structure and dynamics of protein dynamics, and shows how fitting of dynamic quantities leads to improved agreement with static properties.