Split Membrane: A New Model to Accelerate All-Atom MD Simulation of Phospholipid Bilayers
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články
PubMed
39779296
PubMed Central
PMC11776049
DOI
10.1021/acs.jcim.4c01664
Knihovny.cz E-zdroje
- MeSH
- difuze MeSH
- erbB receptory chemie metabolismus MeSH
- fosfolipidy * chemie metabolismus MeSH
- lidé MeSH
- lipidové dvojvrstvy * chemie metabolismus MeSH
- simulace molekulární dynamiky * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- erbB receptory MeSH
- fosfolipidy * MeSH
- lipidové dvojvrstvy * MeSH
All-atom molecular dynamics simulations are powerful tools for studying cell membranes and their interactions with proteins and other molecules. However, these processes occur on time scales determined by the diffusion rate of phospholipids, which are challenging to achieve in all-atom models. Here, we present a new all-atom model that accelerates lipid diffusion by splitting phospholipid molecules into head and tail groups. The bilayer structure is maintained by using external lateral potentials, which compensate for the lipid split. This split model enhances lateral lipid diffusion more than ten times, allowing faster and cheaper equilibration of large systems with different phospholipid types. The current model has been tested on membranes containing PSM, POPC, POPS, POPE, POPA, and cholesterol. We have also evaluated the interaction of the split model membranes with the Disheveled DEP domain and amphiphilic helix motif of the transcriptional repressor Opi1 as representative of peripheral proteins as well as the dimeric fragment of the epidermal growth factor receptor transmembrane domain and the Human A2A Adenosine of G protein-coupled receptors as representative of transmembrane proteins. The split model can predict the interaction sites of proteins and their preferred phospholipid type. Thus, the model could be used to identify lipid binding sites and equilibrate large membranes at an affordable computational cost.
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