Nature Communications (Nov 2023)

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

  • T. Bertie Ansell,
  • Wanling Song,
  • Claire E. Coupland,
  • Loic Carrique,
  • Robin A. Corey,
  • Anna L. Duncan,
  • C. Keith Cassidy,
  • Maxwell M. G. Geurts,
  • Tim Rasmussen,
  • Andrew B. Ward,
  • Christian Siebold,
  • Phillip J. Stansfeld,
  • Mark S. P. Sansom

DOI
https://doi.org/10.1038/s41467-023-43392-y
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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Abstract Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.