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.\"
.IX Title "CONCAVITY 1"
.TH CONCAVITY 1 "2020-12-02" "0.1.1" "User Commands"
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.SH "NAME"
concavity \- predictor of protein ligand binding sites from structure and conservation
.SH "SYNOPSIS"
.IX Header "SYNOPSIS"
concavity [options] \s-1PDBFILE OUTPUT_NAME\s0
.SH "DESCRIPTION"
.IX Header "DESCRIPTION"
ConCavity predicts protein ligand binding sites by combining evolutionary
sequence conservation and 3D structure.
.PP
ConCavity takes as input a \s-1PDB\s0 format protein structure \fB\s-1PDBFILE\s0\fR and optionally
files that characterize the evolutionary sequence conservation of the chains
in the structure file.
.PP
The following result files are produced by default:
.IP "\(bu" 4
Residue ligand binding predictions for each chain (*.scores).
.IP "\(bu" 4
Residue ligand binding predictions in a \s-1PDB\s0 format file (residue scores placed in the temp. factor field, *_residue.pdb).
.IP "\(bu" 4
Pocket prediction locations in a \s-1DX\s0 format file (*.dx).
.IP "\(bu" 4
PyMOL script to visualize the predictions (*.pml).
.PP
To visualize the predictions in PyMol (it if is installed on your
system), load the script by typing \*(L"pymol 1G6C_test1.pml\*(R" at the
prompt or by loading it through the pymol interface.
.PP
The \s-1PDB\s0 and \s-1DX\s0 files can be input into other molecular viewers if
preferred. Several additional output formats are available; see
below. Note that the residue numbering in the .scores files may not
match that of the \s-1PDB\s0 file.
.PP
The ConCavity approach proceeds in three conceptual steps: grid
creation, pocket extraction, and residue mapping (see Methods in
paper). First, the structural and evolutionary properties of the
protein are used to create a regular 3D grid surrounding the protein
in which the score associated with each grid point represents an
estimated likelihood that it overlaps a bound ligand atom. Second,
groups of contiguous, high-scoring grid points are clustered to
extract pockets that adhere to given shape and size
constraints. Finally, every protein residue is scored with an estimate
of how likely it is to bind to a ligand based on its proximity to
extracted pockets.
.PP
Each of the algorithms described for these steps is implemented in
concavity. See the examples.
.SH "REFERENCES"
.IX Header "REFERENCES"
.IP "Capra \s-1JA,\s0 Laskowski \s-1RA,\s0 Thornton \s-1JM,\s0 Singh M, and Funkhouser \s-1TA\s0(2009) Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure. PLoS Comput Biol, 5(12)." 4
.IX Item "Capra JA, Laskowski RA, Thornton JM, Singh M, and Funkhouser TA(2009) Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure. PLoS Comput Biol, 5(12)."
.SH "OPTIONS"
.IX Header "OPTIONS"
\&\fB\s-1PDBFILE\s0\fR is a protein structure file in \s-1PDB\s0 format. \fB\s-1OUTPUT_NAME\s0\fR becomes part of the output file names and may not contain \*(L"/\*(R". Output is written to the current directory.
.SS "Input"
.IX Subsection "Input"
.IP "\fB\-conservation\fR \fI\s-1PATH\s0\fR" 4
.IX Item "-conservation PATH"
If the \*(L"\-conservation\*(R" option is not given, then conservation
information is not considered. Note that there are separate
conservation files for each protein chain in the structure, and the
input to the \-conservation option is the prefix of these files.
Pre-computed conservation files available for almost the entire \s-1PQS\s0 on
the ConCavity web site. If you'd like to compute sequence
conservation values for your own alignments, we recommend the \s-1JSD\s0
algorithm: ,
available as \fBscore_conservation\fR\|(1) from the conservation-code package.
.SS "Grid Creation"
.IX Subsection "Grid Creation"
.IP "\fB\-grid_method\fR \fIligsite|surfnet|pocketfinder|custom\fR" 4
.IX Item "-grid_method ligsite|surfnet|pocketfinder|custom"
.PD 0
.IP "\fB\-resolution\fR \fIint\fR \fIint\fR \fIint\fR" 4
.IX Item "-resolution int int int"
.PD
Set the grid resolution.
.IP "\fB\-spacing\fR \fIfloat\fR" 4
.IX Item "-spacing float"
Set the grid spacing.
.SS "Pocket Extraction"
.IX Subsection "Pocket Extraction"
.IP "\fB\-extraction_method\fR \fIsearch|topn|custom\fR" 4
.IX Item "-extraction_method search|topn|custom"
.PD 0
.IP "\fB\-extraction_threshold_range_cutoff\fR \fI\s-1FLOAT\s0\fR" 4
.IX Item "-extraction_threshold_range_cutoff FLOAT"
.PD
Stop the iterative \fIsearch\fR method when the diameter of the binary search window is less than \fB\-extraction_threshold_range_cutoff\fR * upper_threshold. Recommended value: \fI1e\-6\fR. Default: \fI0\fR.
.SS "Residue Mapping"
.IX Subsection "Residue Mapping"
.IP "\fB\-res_map_method\fR \fIblur|dist|dist\-thresh|custom\fR" 4
.IX Item "-res_map_method blur|dist|dist-thresh|custom"
.PP
Each of these algorithms is described in the text, and each has a
number of additional parameters that change their behavior. The
\&\*(L"custom\*(R" option allows you to set the values of all parameters for
each step yourself. The presets (e.g. ligsite, search, blur) may
override values you set on the command line, so use \*(L"custom\*(R" to have
complete control.
.SS "Output"
.IX Subsection "Output"
There are also several output format options. Pocket
prediction grid values can be output in the following formats:
.IP "\fB\-print_grid_dx\fR \fI0|1\fR" 4
.IX Item "-print_grid_dx 0|1"
\&\s-1DX\s0 format. This is \fI1\fR by default.
.IP "\fB\-print_grid_pdb\fR \fI0|1\fR" 4
.IX Item "-print_grid_pdb 0|1"
\&\s-1PDB\s0 format. The residue predictions are output as a \s-1PDB\s0 file with the residue
scores mapped to the temp. factor field and pocket numbers to the
residue sequence field.
.IP "\fB\-print_grid_txt\fR \fI0|1\fR" 4
.IX Item "-print_grid_txt 0|1"
Raw text.
.IP "\fB\-v\fR" 4
.IX Item "-v"
Verbose mode.
.SH "EXAMPLES"
.IX Header "EXAMPLES"
Note: you may have to copy and uncompress the example data files before running the following examples.
.IP "1." 4
This will run concavity with default values (equivalent to ConCavity^L
in the paper) on the structure 1G6C.pdb and consider the conservation
values found in conservation_data/. This set of predictions will be
called \*(L"test1\*(R". This produces the following default result files in the current directory:
.Sp
.Vb 1
\& concavity \-conservation /usr/share/doc/concavity/examples/conservation_data/1G6C /usr/share/doc/concavity/examples/1G6C.pdb test1
.Ve
.IP "2." 4
For example to score the structure 1G6C.pdb with
ConCavity_Pocketfinder, Search, and Blur, you'd type:
.Sp
.Vb 1
\& concavity \-conservation /usr/share/doc/concavity/examples/conservation_data/1G6C \-grid_method pocketfinder \-extraction_method search \-res_map_method blur /usr/share/doc/concavity/examples/1G6C.pdb cc\-pocketfinder_search_blur
.Ve
.SH "NOTES"
.IX Header "NOTES"
The authors primarily use PyMol and Chimera for visualization, but the range of
output formats means you should be able to import the data into most
structural analysis program. Let us know if there are other output
formats you'd like to see.
.SH "SEE ALSO"
.IX Header "SEE ALSO"
.IP "Concavity Homepage " 4
.IX Item "Concavity Homepage "
.PD 0
.IP "\fBscore_conservation\fR\|(1)" 4
.IX Item "score_conservation"