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Modeling membrane geometries implicitly in Rosetta.
Woods, Hope; Leman, Julia Koehler; Meiler, Jens.
Afiliação
  • Woods H; Center of Structural Biology, Vanderbilt University, Nashville, Tennessee, USA.
  • Leman JK; Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee, USA.
  • Meiler J; Center for Computational Biology, Flatiron Institute, New York, New York, USA.
Protein Sci ; 33(3): e4908, 2024 Mar.
Article em En | MEDLINE | ID: mdl-38358133
ABSTRACT
Interactions between membrane proteins (MPs) and lipid bilayers are critical for many cellular functions. In the Rosetta molecular modeling suite, the implicit membrane energy function is based on a "slab" model, which represent the membrane as a flat bilayer. However, in nature membranes often have a curvature that is important for function and/or stability. Even more prevalent, in structural biology research MPs are reconstituted in model membrane systems such as micelles, bicelles, nanodiscs, or liposomes. Thus, we have modified the existing membrane energy potentials within the RosettaMP framework to allow users to model MPs in different membrane geometries. We show that these modifications can be utilized in core applications within Rosetta such as structure refinement, protein-protein docking, and protein design. For MP structures found in curved membranes, refining these structures in curved, implicit membranes produces higher quality models with structures closer to experimentally determined structures. For MP systems embedded in multiple membranes, representing both membranes results in more favorable scores compared to only representing one of the membranes. Modeling MPs in geometries mimicking the membrane model system used in structure determination can improve model quality and model discrimination.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lipossomos / Proteínas de Membrana Tipo de estudo: Prognostic_studies Idioma: En Revista: Protein Sci / Protein sci / Protein science Assunto da revista: BIOQUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lipossomos / Proteínas de Membrana Tipo de estudo: Prognostic_studies Idioma: En Revista: Protein Sci / Protein sci / Protein science Assunto da revista: BIOQUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos