Endonuclease PvuII (1PVI) DNA - GATTACAGATTACA
CAP - Catabolite gene Activating Protein (1BER)
DNA - GATTACAGATTACAGATTACA Endonuclease PvuII bound to palindromic DNA recognition site CAGCTG (1PVI) DNA - GATTACAGATTACAGATTACA TBP - TATA box  Binding Protein (1C9B)
CAP - Catabolite gene Activating Protein (1BER)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
GCN4 - leucine zipper transcription factor bound to palindromic DNA recognition site ATGAC(G)TCAT (1YSA)
TBP - TATA box  Binding Protein (1C9B)
 

Simulation of membrane proteins in YASARA


The simulation of membrane proteins is a sensible task that is complicated by numerous pitfalls. Small errors in the initial setup can quickly let the membrane fall apart, long before the self-stabilizing hydrophobic forces can take effect. YASARA features a complete simulation protocol for membrane proteins, that takes all the required steps automatically at the touch of a button, starting from the PDB file of your membrane protein. The following screenshots summarize the individual steps, the macro is included in YASARA and can also be downloaded here:



Step 1

Step 2

Step 1: YASARA scans the protein for secondary structure elements that contain lots of exposed hydrophobic residues and could be part of a potential transmembrane region. This example shows bovine rhodopsin, glycosylated and with retinal bound.


Step 2: Based on the identified secondary structure elements, the protein is oriented relative to the membrane, then the final membrane position is determined by scanning the entire protein surface for the most hydrophobic region.

Step 3

Step 4

Step 3: YASARA shows the suggested membrane embedding. If required, one can now interactively fine-tune the membrane position and size.


Step 4: YASARA builds a membrane of the required size and with the chosen lipid composition (current options are phosphatidyl-ethanolamine, -choline, -serine, and cholesterol).

Step 5

Step 6

Step 5: Having cut out exactly the required number of lipids from the initial membrane, YASARA runs a compression simulation, where the simulation cell is shrunk continuously, so that the membrane edges can fuse at the periodic boundaries.


Step 6: YASARA embeds the compressed protein in the membrane, deletes the lipids that bump into the protein, and then slowly expands the protein during a simulation to fill the pore, while the lipids adapt. Force field parameters for all non-standard residues like lipids, ligands and posttranslational modifications are derived automatically using AutoSMILES.

Step 7

Step 8

Step 7: YASARA fills the cell with water, carefully avoiding to place water molecules between the lipids. Then the whole system is energy minimized to remove any conformation stress from bumps.


Step 8: YASARA runs an equilibration simulation lasting 250 ps. During this equilibration phase, the membrane is artificially stabilized, so that it can adapt to the protein and the right density without being damaged.