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Xavier Periole

Researcher at University of Groningen

Publications -  45
Citations -  8007

Xavier Periole is an academic researcher from University of Groningen. The author has contributed to research in topics: Molecular dynamics & Photosystem II. The author has an hindex of 31, co-authored 45 publications receiving 6848 citations. Previous affiliations of Xavier Periole include Rockefeller University & Icahn School of Medicine at Mount Sinai.

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The MARTINI Coarse-Grained Force Field: Extension to Proteins

TL;DR: A new CG model for proteins as an extension of the MARTINI force field is developed and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.
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Improved Parameters for the Martini Coarse-Grained Protein Force Field

TL;DR: Improve some of the bonded terms in the Martini protein force field that lead to a more realistic length of α-helices and to improved numerical stability for polyalanine and glycine repeats.
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Lipid organization of the plasma membrane.

TL;DR: In this paper, the authors provided a high-resolution view of the lipid organization of a plasma membrane at an unprecedented level of complexity by combining 14 types of headgroups and 11 types of tails asymmetrically distributed across the two leaflets, closely mimicking an idealized mammalian plasma membrane.
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Combining an Elastic Network With a Coarse-Grained Molecular Force Field: Structure, Dynamics, and Intermolecular Recognition

TL;DR: The results for this series of tests indicate that ELNEDIN models allow microsecond time-scale molecular dynamics simulations to be carried out readily, that large biological entities such as the viral capsid of the cowpea mosaic virus can be stably modeled as assemblies of independent ELNedIN models, and that ELnEDin models show significant promise for modeling protein-protein association processes.
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The power of coarse graining in biomolecular simulations

TL;DR: An overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity, are provided.