Structure and dynamics of a nanodisc by integrating NMR, SAXS and SANS experiments with molecular dynamics simulations

Bengtsen, Tone; Holm, Viktor L.; Kjølbye, Lisbeth Ravnkilde; Midtgaard, Søren Roi; Johansen, Nicolai Tidemand; Tesei, Giulio; Bottaro, Sandro; Schiøtt, Birgit; Lindorff‐Larsen, Kresten

doi:10.7554/elife.56518

Cited by 55 publications

(75 citation statements)

References 66 publications

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“…Tests reproducing DEER and PRE data for the protein systems studied in this article, as well as for a nanodisc [ 29 ], are performed automatically using Travis CI ( travis-ci.com/github/KULL-Centre/DEERpredict ) every time the code is modified on the GitHub repository. The same tests can also be run locally using the test running tool pytest.…”

Section: Design and Implementationmentioning

confidence: 99%

“…We present our implementation, distributed as the DEER-PREdict software, and test it against experimental data on HIV-1 Protease, T4 Lysozyme and the Acyl-CoA-Binding Protein. This software has been previously used for the calculation of both intra- and intermolecular DEER and PRE NMR data [ 28 , 29 ], and has some overlap with the features in RotamerConvolveMD [ 25 ] ( github.com/MDAnalysis/RotamerConvolveMD ). DEER-PREdict is open-source, documented ( deerpredict.readthedocs.io ) and open to contributions from the community.…”

Section: Introductionmentioning

confidence: 99%

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DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles

et al. 2021

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Owing to their plasticity, intrinsically disordered and multidomain proteins require descriptions based on multiple conformations, thus calling for techniques and analysis tools that are capable of dealing with conformational ensembles rather than a single protein structure. Here, we introduce DEER-PREdict, a software program to predict Double Electron-Electron Resonance distance distributions as well as Paramagnetic Relaxation Enhancement rates from ensembles of protein conformations. DEER-PREdict uses an established rotamer library approach to describe the paramagnetic probes which are bound covalently to the protein.DEER-PREdict has been designed to operate efficiently on large conformational ensembles, such as those generated by molecular dynamics simulation, to facilitate the validation or refinement of molecular models as well as the interpretation of experimental data. The performance and accuracy of the software is demonstrated with experimentally characterized protein systems: HIV-1 protease, T4 Lysozyme and Acyl-CoA-binding protein. DEER-PREdict is open source (GPLv3) and available at github.com/KULL-Centre/DEERpredict and as a Python PyPI package pypi.org/project/DEERPREdict.

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Section: Design and Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles

et al. 2021

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“…Use of nanodiscs for simultaneous delivery of antigen and adjuvant has been found to increase the response of the immunological system by orders of magnitude in comparison to traditional vaccines. Due to the variety of possible applications of nanodiscs, their properties are the subject of intensive study (Debnath and Schäfer, 2015;Siuda and Tieleman, 2015;Stepien et al, 2015Stepien et al, , 2020Martinez et al, 2017;Pourmousa and Pastor, 2018;Bengtsen et al, 2020;Schachter et al, 2020); they are tuned via modification of their lipid composition (Augustyn et al, 2019) or alterations to the sequence, thus structure, of the scaffold proteins (Denisov et al, 2004;Nasr et al, 2016).…”

Section: Nanomedicinementioning

confidence: 99%

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery

Bunker

Róg

2020

Front. Mol. Biosci.

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In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.

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“…These methods offer the advantage-like NMR-that the system is investigated in solution and thus under near-physiological conditions. Although inferring structure from scattering curves is a severely ill-posed problem, small-angle scattering is a valuable tool for providing low-resolution shape information, which has been successfully combined in integrative structure modeling approaches with data from other techniques such as X-ray crystallography, NMR, EPR, FRET, or cryo-electron microscopy (3,4,(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).…”

Section: Introductionmentioning

confidence: 99%

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

Klose

Holla

Gmeiner

et al. 2021

Biophysical Journal

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Fo ¨rster resonance energy transfer (FRET) and electron paramagnetic resonance (EPR) spectroscopy are complementary techniques for quantifying distances in the nanometer range. Both approaches are commonly employed for probing the conformations and conformational changes of biological macromolecules based on site-directed fluorescent or paramagnetic labeling. FRET can be applied in solution at ambient temperature and thus provides direct access to dynamics, especially if used at the single-molecule level, whereas EPR requires immobilization or work at cryogenic temperatures but provides data that can be more reliably used to extract distance distributions. However, a combined analysis of the complementary data from the two techniques has been complicated by the lack of a common modeling framework. Here, we demonstrate a systematic analysis approach based on rotamer libraries for both FRET and EPR labels to predict distance distributions between two labels from a structural model. Dynamics of the fluorophores within these distance distributions are taken into account by diffusional averaging, which improves the agreement with experiment. Benchmarking this methodology with a series of surface-exposed pairs of sites in a structured protein domain reveals that the lowest resolved distance differences can be as small as $0.25 nm for both techniques, with quantitative agreement between experimental and simulated transfer efficiencies within a range of 50.045. Rotamer library analysis thus establishes a coherent way of treating experimental data from EPR and FRET and provides a basis for integrative structural modeling, including studies of conformational distributions and dynamics of biological macromolecules using both techniques.

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Structure and dynamics of a nanodisc by integrating NMR, SAXS and SANS experiments with molecular dynamics simulations

Cited by 55 publications

References 66 publications

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

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