Evidence map›Paper›PMID 23818175›Full record

ArticleProteins2014

Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics.

Abil E Aliev, Martin Kulke, Harmeet S Khaneja, Vijay Chudasama, Tom D Sheppard, Rachel M Lanigan

Abstract read
In one paragraph

Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

113 citing papers in PubMed.

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53 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Abil E AlievDepartment of Chemistry, University College London, London, WC1H 0AJ, United Kingdom.
Martin Kulke
Harmeet S Khaneja
Vijay Chudasama
Tom D Sheppard
Rachel M Lanigan

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use (13) C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone.

Indexed as

Molecular Dynamics SimulationAlgorithmsAmino Acid MotifsAmino Acid SequenceHumansHydroxyprolineNuclear Magnetic Resonance, BiomolecularProlineThermodynamicsUbiquitinHydroxyprolineProlineUbiquitinbiomolecular force fieldconformational analysismolecular dynamics simulationsNMRpeptidesprolineproteinsstructure

Identifiers

PMID23818175
PMCPMC4282583

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.