Descended from: https://github.com/BranniganLab/densitymap
Detailed protocol is in preparation.
Clone this repository
Install the DTA package with the following commands:
cd Polar_Binning_DeltaG
cd python
#[Optional:] conda create -n DTA
#[Optional:] conda activate DTA
pip install .
Create or obtain unbiased coarse-grained (e.g. Martini) simulations of a membrane protein (only one protein currently possible without modifications)
Make sure the trajectory is whole (e.g. gmx trjconv -f [inputname].xtc -s md.tpr -o [ouputname].xtc -ur compact -pbc mol -center
)
Load your trajectory into VMD
On first use for this protein:
a) write an assign_helices script based on one of the examples provided in ./TCL
b) Test your helix assignment script from the tk console:
> source <helix assignment script path>
c) In graphical representations, color the protein by occupancy and confirm that different colors correspond to different helices
Make a config file:
a) Select the closest config file from ./TCL/sample_configs and edit accordingly.
b) Test the selection strings that you used in the config file using the graphical representations window in VMD
From the tk console:
> source polarDensity_for_DTA.tcl
> polarDensity <config file path>
Open the plot_enrichment.ipynb jupyter notebook using your method of choice (e.g. VSCode or a local host)
Update the paths and lipid names to point to your data and run
Select bins for the binding site (the show_bins notebook may be useful here)
Determine the accessible area for the site (many optional methods for this, get_accessible_area.ipynb describes one method)
Determine the expected mode of the bead probabilities in the bulk for a patch equal to the accessible area (e.g. using get_Npeak.ipynb)
Calculate the dG_bind using the get_probability_distributions.ipynb notebook