Modified for python3 support by Zheng Ruan (26 Mar, 2020)
LipidWrapper 1.0
As ever larger and more complex biological systems are modeled in
silico, approximating physiological lipid bilayers with simple
planar models becomes increasingly unrealistic. When building
large-scale models of whole subcellular environments, models of
lipid membranes with carefully considered, biologically relevant
curvature are essential. We here present a computer program called
LipidWrapper, written by Jacob Durrant in the lab of Rommie E. Amaro,
capable of creating curved membrane models with geometries derived
from various possible sources, both experimental and theoretical. We
are hopeful that this utility will be a useful tool for the
computational-biology community.
Installation
============
As a python script, LipidWrapper should run on any operating system
that has python, numpy, and scipy installed, without requiring the
installation of additional software. If the user optionally wishes
to generate lipid-bilayer models from PNG images, the Python Imaging
Library must also be installed. LipidWrapper has been explicitly
tested on Scientific Linux 6.2, OS X, Windows XP, and Windows 7.
The program download includes an "examples" directory that demonstrate
how to use the software. Examples are provided showing how to generate
lipid-bilayer models wrapped around equations, PDB point files, DAE
models, and image-defined surfaces. Test PDB, DAE, and PNG files are
included.
Command-Line Parameters
=======================
Methods for creating a surface mesh
===================================
--surface_equation: Generate a surface mesh from a python-formatted
equation defining z, given x and y. The --min_x, --max_x,
--min_y, and --max_y parameters are used to specify the region
over which the function should be evaluated. The --step_x and
--step_y parameters define the x-y distance between adjacent
points. Python functions from the math, numpy, and scipy modules
can be used. Example: --surface_equation "z =
250*numpy.sin(x*x/60000 +y*y/60000)"
--surface_filename: If this parameter specifies a file with the PDB
extension, a surface mesh is generated from the coordinates of
the PDB atoms. Example: --surface_filename mymesh.pdb
--surface_filename: If this parameter specifies a file that does not
have the PDB extension, the file is assumed to be a gray-scale
image, where black represents regions that are topologically
low, and white represents regions that are topologically high.
The --min_x, --max_x, --min_y, and --max_y parameters are used
to specify the region where the mesh should be generated. The
--step_x and --step_y parameters define the x-y distance between
adjacent points. The --max_height parameter determines the
height of the bilayer model at those locations where the image
is white; black regions are assigned a height of 0. This feature
is only available if the python PIL module has been installed on
your system. Example: --surface_filename mymesh.png
The initial lipid model
=======================
--lipid_pdb_filename: This parameter specifies a PDB file containing
an all-atom model of a planar lipid bilayer. LipidWrapper will
wrap this lipid around the user-generated mesh. Example:
--lipid_pdb_filename lipid.pdb
--lipid_headgroup_marker: A unique atom representing the headgroup of
each lipid residue must be specified. The
--lipid_headgroup_marker accepts a comma-separated lists of atom
specifications (RESNAME_ATOMNAME). If either RESNAME or ATOMNAME
is omitted, any value will be accepted. By default, LipidWrapper
identifies lipid headgroups by looking for any atom named "P"
(_P) or any atom named "O3" belonging to a cholesterol molecule
(CHL1_O3). Example: --lipid_headgroup_marker "_P,CHL1_O3"
Methods for resolving lipid clashes
===================================
--delete_clashing_lipids: It's common for lipids to sterically clash
at the interface of two adjacent surface-mesh tessellated
triangles. If this parameter is set to TRUE, any clashing lipids
are deleted. Example: --delete_clashing_lipids TRUE
--clash_cutoff: If you do choose to delete clashing lipids, this
parameter determines how close two atoms must be (in Angstroms)
to constitute a steric clash. Example: --clash_cutoff 2.0
--fill_holes: Deleting lipids often leaves holes in the membrane. If
this parameter is set to TRUE, LipidWrapper tries to fill the
hole. Example: --fill_holes TRUE
--fill_hole_exhaustiveness: Essentially, how long LipidWrapper should
try to fill the holes. Example: --fill_hole_exhaustiveness 10
--clashing_potential_margin: Lipid clashes occur at the edges of
adjacent tessellated triangles. If these triangles are very
large, it's faster to only check for clashes and holes near the
triangle edges. This variable specifies how far from the edges,
in Angstroms, that LipidWrapper should look for clashes and
holes. Example: --clashing_potential_margin 25.0
--very_distant_lipids_cutoff: LipidWrapper determines if two lipids
clash by comparing the distance between every atom in the first
lipid with every atom in the second lipid. This can be
computationally expensive. However, sometimes two lipids are so
distant from each other, that it's obvious there are no clashes,
making the pair-wise comparison unnecessary. Before performing
this expensive pair-wise comparison, LipidWrapper calculates the
distance between one atom of each lipid. If this distance is
greater than this user-specified cutoff, the program will simply
assume there are no clashes. WARNING: Remember to consider the
width of your lipid bilayer when choosing this value. Adjacent
lipids on opposite sides of the bilayer can seem distant when
considering the distance between their headgroups, for example.
Example: --very_distant_lipids_cutoff 50.0
--triangle_center_proximity_cutoff_distance: Lipid steric
clashes/holes typically occur between lipids that belong to
adjacent tessellated triangles. However, if tessellated
triangles are small enough, clashes are possible between lipids
that belong to non-adjacent triangles as well. Consequently, in
addition to checking for adjacency, LipidWrapper also checks the
distance between the triangle centers, using this user-specified
value as a cutoff. Example:
--triangle_center_proximity_cutoff_distance 50.0
--memory_optimization_factor: When the tessellated triangles are very
large and consequently contain many individual lipids, the
extensive pairwise distance comparisons required can result in
memory errors. This parameter tells lipid Wrapper to divide the
list of atoms being compared into smaller chunks. The pairwise
distance comparison is performed piecewise on each chunk-chunk
pair and so uses less memory, albeit at the expensive of speed.
Only increase the value of this parameter if you run into memory
errors. Example: --memory_optimization_factor 1
Additional options
==================
--number_of_processors: Using multiple processors can significantly
increase the speed of the LipidWrapper algorithm. Example:
--number_of_processors 8
--show_grid_points: Aside from producing PDB coordinates for lipid
atoms, additional coordinates will be appended to the bottom of
the output containing "atoms" named "X" that specify the
location of the surface mesh points. Example: --show_grid_points
TRUE
--create_triangle_tcl_file: A separate file named "triangles.tcl" will
be generated containing a tcl script that can be run in VMD to
visualize the mesh surface. Example: --create_triangle_tcl_file
TRUE
--output_directory: If an output directory is specified, all
LipidWrapper output files, as well as additional files
representing the intermediate steps required to build the final
bilayer, will be saved in that directory. Example:
--output_directory ./my_output/
--use_disk_instead_of_memory: For very large systems, storing the
growing model in memory can be problematic. If this parameter is
set to TRUE, the growing model will be stored on the hard disk
instead. However, expect longer execution times if this
parameter is set to TRUE. Example: --use_disk_instead_of_memory
TRUE
--compress_output: Depending on the user options selected,
LipidWrapper output can require a lot of disk space. If this
parameter is set to TRUE, the output will be automatically
compressed using the gzip algorithm (Lempel-Ziv coding LZ77).
The files can be uncompressed with the UNIX gunzip utility, or
similar Windows-based packages. Example: --compress_output TRUE
Example
=======
python lipidwrapper.py --surface_equation "z = 250*numpy.sin(x*x/60000
+y*y/60000) * (-numpy.sqrt(x*x+y*y)/(560 * numpy.sqrt(2)) + 1)"
--min_x 500 --max_x 1000 --min_y 500 --max_y 1000 --step_x 25
--step_y 25 --lipid_pdb_filename lipid.pdb
--lipid_headgroup_marker "_P,CHL1_O3" --delete_clashing_lipids
TRUE --clash_cutoff 1.0 --fill_holes TRUE
--fill_hole_exhaustiveness 10 > lipid_model.pdb