/MemProtMD

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MemProtMD

A selection of Google Colab Workflows for inserting protein structures into membranes

We recomend using Google Chrome or Firefox to run, as Safari has issues with the sizes of a PDB file upload. The references for each of the methods used in the workflows are cited below.

MemProtMD with Insane - Assembly of a predefined membrane around an input protein structure

Protein PDB File -> Memembed1 -> martinize2 -> insane3 -> CGMD5 -> CG2AT6 -> Atomistic PDB in membrane

MemProtMD Self Assembly - Self-Assembly of randomly oriented lipids into a bilayer around an input protein structure

Protein PDB File -> Memembed1 -> martinize2 -> self-assemble4 -> CGMD5 -> CG2AT6 -> Atomistic PDB in membrane

MemProtMD Single Pass TM helix with Insane - Assembly of a predefined membrane around an input sequence of a single-pass transmembrane helix

Amino Acid Sequence -> PyMOL -> TM helix PDB File -> Memembed1 -> martinize2 -> insane3 -> CGMD5 -> CG2AT6 -> Atomistic PDB in membrane

MemProtMD Single Pass TM helix Self-Assembly - Self-Assembly of randomly oriented lipids into a bilayer around an input sequence of a single-pass transmembrane helix

Amino Acid Sequence -> PyMOL -> TM helix PDB File -> Memembed1 -> martinize2 -> self-assemble4 -> CGMD5 -> CG2AT6 -> Atomistic PDB in membrane

MemProtMD Multimer - Set-up for Self-Association of 2 membrane protein structures - 1 central 'target' protein and 8 'search' proteins

 2x PDBs File -> Memembed1 -> martinize2 -> insane3

MemProtMD Association - Set-up for Self-Association of a soluble protein structure with a membrane.

 PDB File -> martinize2 -> insane3

MemProtMD Association with a Membrane Protein - Set-up for Self-Association of a soluble protein structure with a membrane, which contains a membrane protein.

 2x PDBs File -> Memembed1 -> martinize2 -> insane3

Energy Minimise - Add any missing side-chains and energy minimise a protein structure for use with MemProtMD.

 PDBs File -> PDB2PQR7 -> minimisation5

References

  1. Nugent & Jones (2013) Membrane protein orientation and refinement using a knowledge-based statistical potential. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-14-276 [https://github.com/psipred/MemEmbed]
  2. Souza et al. (2021) Martini 3: a general purpose force field for coarse-grained molecular dynamics. Nature Methods. https://doi.org/10.1038/s41592-021-01098-3 [https://github.com/marrink-lab/vermouth-martinize]
  3. Wassenaar et al. (2015) Computational Lipidomics with insane: A Versatile Tool for Generating Custom Membranes for Molecular Simulations. JCTC. https://doi.org/10.1021/acs.jctc.5b00209 [https://github.com/Tsjerk/Insane]
  4. Stansfeld et al. (2015) MemProtMD: automated insertion of membrane protein structures into explicit lipid membranes. Structure. https://doi.org/10.1016/j.str.2015.05.006
  5. Abraham et al. (2015) GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputer. SoftwareX. https://doi.org/10.1016/j.softx.2015.06.001
  6. Vickery & Stansfeld (2021) CG2AT2: an Enhanced Fragment-Based Approach for Serial Multi-scale Molecular Dynamics Simulations. JCTC. https://doi.org/10.1021/acs.jctc.1c00295 [https://github.com/pstansfeld/cg2at]
  7. Jurrus et al. (2018) Improvements to the APBS biomolecular solvation software suite. Protein Science. https://onlinelibrary.wiley.com/doi/10.1002/pro.3280