General Protocol for Constructing Molecular Models of Nanodiscs

Kjølbye, Lisbeth Ravnkilde; Maria, Leonardo De; Wassenaar, Tsjerk A.; Abdizadeh, Haleh; Marrink, Siewert J.; Ferkinghoff‐Borg, Jesper; Schiøtt, Birgit

doi:10.1021/acs.jcim.1c00157

Cited by 7 publications

(7 citation statements)

References 95 publications

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“…csMSP1D1 nanodiscs persistently have the largest axis ratio, which varies between 1.6 and 1.8, whereas csMSP1D1ÁH5 nanodiscs have the smallest, varying between 1.3 and 1.5, and csMSP1E3D1 lies in between with values varying between 1.45 and 1.65. Although seemingly incidental, this coincides with a recent course-grained moleculardynamics study of the same circularized MSPs (cMSPs, nonsupercharged; Kjølbye et al, 2021), where cMSP1D1 was found to have the highest degree of anisotropy, with cMSP1D1ÁH5 being the most circular and cMSP1E3D1 falling in between. These results suggest that there are other factors influencing the shape of nanodiscs besides the degree of lipid loading, especially the choice of MSP and its intrinsic rigidity.…”

Section: Modelling and Data Analysissupporting

confidence: 87%

Global fitting of multiple data frames from SEC–SAXS to investigate the structure of next-generation nanodiscs

Barclay

Johansen

Tidemand

et al. 2022

Acta Crystallogr D Struct Biol

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The combination of online size-exclusion chromatography and small-angle X-ray scattering (SEC–SAXS) is rapidly becoming a key technique for structural investigations of elaborate biophysical samples in solution. Here, a novel model-refinement strategy centred around the technique is outlined and its utility is demonstrated by analysing data series from several SEC–SAXS experiments on phospholipid bilayer nanodiscs. Using this method, a single model was globally refined against many frames from the same data series, thereby capturing the frame-to-frame tendencies of the irradiated sample. These are compared with models refined in the traditional manner, in which refinement is based on the average profile of a set of consecutive frames from the same data series without an in-depth comparison of individual frames. This is considered to be an attractive model-refinement scheme as it considerably lowers the total number of parameters refined from the data series, produces tendencies that are automatically consistent between frames, and utilizes a considerably larger portion of the recorded data than is often performed in such experiments. Additionally, a method is outlined for correcting a measured UV absorption signal by accounting for potential peak broadening by the experimental setup.

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Section: Modelling and Data Analysissupporting

confidence: 87%

Global fitting of multiple data frames from SEC–SAXS to investigate the structure of next-generation nanodiscs

Barclay

Johansen

Tidemand

et al. 2022

Acta Crystallogr D Struct Biol

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“…In connection to the actual Martini force field, we, and many others, have developed a wide range of tools to facilitate setting up, running, and analyzing MD simulations with this model (Figure 1). Examples include the widely used tools insane 91 and CHARMM‐GUI Martini‐maker 92,93 to build multicomponent lipid‐based systems, tools to facilitate high‐throughput sampling of protein–protein interactions such as DAFT 94 or PANEL, 95 the MERMAID tool 96,97 to help setting up and analyzing membrane proteins, the martinize tool to build Martini topologies from biomolecular structural data, 50 polyply, a python script to build complex starting structures involving arbitrary (bio)polymers, 98 and the Nanodisc Builder, to construct starting structures for protein–lipid nanodiscs 99 …”

Section: A Brief History Of Martinimentioning

confidence: 99%

Two decades of Martini: Better beads, broader scope

Marrink

Monticelli

Melo

et al. 2022

WIREs Comput Mol Sci

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111

109

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The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipidbased systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely highthroughput applications, systems with large complexity, and simulations approaching the scale of whole cells.

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“…In addition, Martini has successfully modeled lipid nanodiscs, which serve as crucial lipid bilayer platforms for studying membrane proteins and are stabilized by membrane scaffold proteins. 225 Moreover, the size and time scales made possible with Martini allow for the probing of larger macrocomplexes in an integrative multiscale computational approach. A large multicomponent 900 kDa proteasome nanopore that controls the unfolding and threading of individual proteins across its pore was recently modeled with Martini.…”

Section: Main Cg Protein Model Applicationsmentioning

confidence: 99%

“…More complex mechanisms such as the membrane toppling mechanism of the folate energy coupling factor transporter , or the peptide recognition determinants of the human signal peptidase complex have been successfully studied as well. In addition, Martini has successfully modeled lipid nanodiscs, which serve as crucial lipid bilayer platforms for studying membrane proteins and are stabilized by membrane scaffold proteins …”

Section: Main Cg Protein Model Applicationsmentioning

confidence: 99%

Pragmatic Coarse-Graining of Proteins: Models and Applications

Borges-Araújo,

Patmanidis,

Singh

et al. 2023

J. Chem. Theory Comput.

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The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

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General Protocol for Constructing Molecular Models of Nanodiscs

Cited by 7 publications

References 95 publications

Global fitting of multiple data frames from SEC–SAXS to investigate the structure of next-generation nanodiscs

Global fitting of multiple data frames from SEC–SAXS to investigate the structure of next-generation nanodiscs

Two decades of Martini: Better beads, broader scope

Pragmatic Coarse-Graining of Proteins: Models and Applications

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