🆕 Plot Similarities in a Monomer Set
Problem
You want to plot similarities in a monomer set in either OEChem TK’s built-in monomer sets
or a custom monomer set defined in a json file.
Ingredients
|
Difficulty Level
🌶️ 🌶️
Download
Source Code
monomers2plot
#!/usr/bin/env python3
# (C) 2026 Cadence Design Systems, Inc. (Cadence)
# All rights reserved.
# TERMS FOR USE OF SAMPLE CODE The software below ("Sample Code") is
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# subject to these terms. Cadence claims no rights to Customer's
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# current license or subscription to the applicable Cadence offering.
# THE SAMPLE CODE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED. OPENEYE DISCLAIMS ALL WARRANTIES, INCLUDING, BUT
# NOT LIMITED TO, WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
# PARTICULAR PURPOSE AND NONINFRINGEMENT. In no event shall Cadence be
# liable for any damages or liability in connection with the Sample Code
# or its use.
"""Generate plot showing monomer similarity."""
import argparse
import json
import os
import pathlib
import sys
import numpy as np
import rich.console
from bokeh.models import ColumnDataSource, HoverTool, LabelSet
from bokeh.plotting import figure, output_file, save, show
from openeye import oechem, oedepict, oegrapheme, oegraphsim
from rich.progress import BarColumn, Progress, TextColumn
from rich_argparse import HelpPreviewAction, RichHelpFormatter
from sklearn.decomposition import PCA
__SCRIPT_NAME__ = pathlib.Path(__file__).absolute().stem
__SCRIPT_DESC__ = "Plot similarity of monomers."
__SCRIPT_TOOLKITS__ = ["oechem", "oedepict", "oegrapheme", "oegraphsim"]
__SCRIPT_KEYWORDS__ = [
"monomer",
"peptide",
"peptide-informatics",
"similarity",
"visualization",
]
__SCRIPT_CATEGORIES__ = ["peptide-informatics"]
def parse_options() -> argparse.Namespace:
"""Parse main options."""
parser = argparse.ArgumentParser(
add_help=True,
formatter_class=RichHelpFormatter,
description="[yellow]" + __SCRIPT_DESC__ + "[/yellow]",
)
monomers_group = parser.add_argument_group("Monomer set options")
_add_monomer_collection(monomers_group)
image_group = parser.add_argument_group("Output options")
image_group.add_argument(
"--html",
type=str,
required=False,
metavar="HTML-FILE",
help="output HTML file (required: %(required)s) -- if no output is provided the image will be displayed in the browser",
)
image_group.add_argument(
"--width",
type=int,
default=900,
help="width of output image (default: %(default)s)",
)
image_group.add_argument(
"--height",
type=int,
default=900,
help="height of output image (default: %(default)s)",
)
parser.add_argument("--help-image", action=HelpPreviewAction)
parser.add_argument(
"--save-console-svg",
default=False,
action="store_true",
help=f"run command and capture console output in {__SCRIPT_NAME__}.svg file",
)
return parser.parse_args()
def main() -> int:
"""Console script for monomer explorer."""
args = parse_options()
console = rich.console.Console(record=args.save_console_svg)
monomers = _get_monomer_collection(args)
code_set = args.code_set or monomers.GetPrimaryCodeSet()
monomer_pred = oechem.OEAndMonomer(
oechem.OEHasPolymerType(oechem.OEPolymerType_Peptide),
oechem.OEIsInMonomerCodeSet(code_set),
)
num_peptide_monomers = oechem.OECount(monomers, monomer_pred)
fp_type = oegraphsim.OEGetFPType(oegraphsim.OEFPType_Tree)
monomer_list: list[oechem.OEMonomer] = list(monomers.GetMonomers(monomer_pred))
similarity_bits: np.ndarray = np.empty(shape=(num_peptide_monomers, 4096))
svg_images: list[str] = []
with Progress(
TextColumn("{task.description}"),
BarColumn(bar_width=60),
TextColumn("{task.percentage:3.1f}%"),
transient=True,
console=console,
) as progress:
monomer_prep = progress.add_task(
"[blue]Preparing monomers", total=num_peptide_monomers
)
for idx, monomer in enumerate(monomers.GetMonomers(monomer_pred)):
image, fingerprint = _generate_monomer_image_and_fingerprint(
monomer, fp_type
)
svg_images.append(image)
bits = [
1 if fingerprint.IsBitOn(b) else 0 for b in range(fingerprint.GetSize())
]
similarity_bits[idx] = np.array(bits)
progress.update(monomer_prep, advance=1)
# # prepare coordinates for monomer plot
coords = PCA(n_components=2, random_state=0).fit_transform(similarity_bits)
coords_x = [x for x, _ in coords]
coords_y = [y for _, y in coords]
data = {
"x": coords_x,
"y": coords_y,
"code": [m.GetCode(code_set) for m in monomer_list],
"color": [
(
"#1E7614"
if oechem.OEIsStandardMonomer(m.GetCanonicalSmiles())
else "#3b3b3b"
)
for m in monomer_list
],
"marker": [
"square" if oechem.OEIsStandardMonomer(m.GetCanonicalSmiles()) else "circle"
for m in monomer_list
],
"size": [
20 if oechem.OEIsStandardMonomer(m.GetCanonicalSmiles()) else 5
for m in monomer_list
],
"label": [
(
m.GetCode(code_set)
if oechem.OEIsStandardMonomer(m.GetCanonicalSmiles())
else ""
)
for m in monomer_list
],
"svg_image": svg_images,
}
source = ColumnDataSource(data=data)
tooltips = """
<div>
<div>
<span style="font-size: 20px;">Code: @code</span>
</div>
<img style="float: left; margin: 5px 5px 5px 5px; width:250px;">
@svg_image{safe}
</img>
</div>
"""
fig = figure(
title=f"{num_peptide_monomers} peptide monomers in '{code_set}' code set",
width=args.width,
height=args.height,
margin=(50, 50, 50, 50),
)
fig.scatter(
x="x",
y="y",
fill_color="color",
line_color=None,
marker="marker",
size="size",
fill_alpha=0.5,
source=source,
)
labels = LabelSet(
x="x",
y="y",
text="label",
text_align="center",
text_font_size="16pt",
x_offset=0,
y_offset=6,
source=source,
)
fig.add_layout(labels, place="above")
fig.add_tools(HoverTool(tooltips=tooltips))
if not args.html or pathlib.Path(args.html).suffix.lower() != ".html":
show(fig)
else:
console.print(f"[blue]Saving plot to {args.html} ...[/blue]")
output_file(args.html, title="Monomer Similarity", mode="inline")
save(fig, args.html)
return os.EX_OK
def _generate_monomer_image_and_fingerprint(
monomer: oechem.OEMonomer, fp_type: oegraphsim.OEFPTypeBase
) -> tuple[str, oegraphsim.OEFingerPrint]:
mol: oechem.OEMolBase = oechem.OEGraphMol()
oechem.OESmilesToMol(mol, monomer.GetCanonicalSmiles())
fingerprint: oegraphsim.OEFingerPrint = oegraphsim.OEFingerPrint()
oegraphsim.OEMakeFP(fingerprint, mol, fp_type)
image = oedepict.OEImage(600, 600)
oegrapheme.OEDrawMonomer(image, monomer)
svg = oedepict.OEWriteImageToString("svg", image).decode("utf-8")
return svg, fingerprint
class MonomerSetParameter: # noqa: PLW1641
"""Utility class to handle both built-in and user defined monomer sets."""
def __init__(self) -> None: # noqa: D107
self._monomer_sets = ["Standard", "OpenEye", "JSON-FILENAME"]
def __repr__(self) -> str: # noqa: D105
return ",".join(self._monomer_sets)
def __eq__(self, param: object) -> bool: # noqa: D105
if not isinstance(param, str):
return False
if param in ["Standard", "OpenEye"]:
return True
console = rich.console.Console()
monomer_set_filepath = pathlib.Path(param)
if (
not monomer_set_filepath.exists()
or monomer_set_filepath.suffix.lower() != ".json"
):
console.print(f"[red]Invalid monomer set file '{param}' ![/red]")
return False
try:
with monomer_set_filepath.open("r") as json_file:
json.load(json_file)
except json.JSONDecodeError as e:
console.print(f"[red]Invalid monomer set file '{param}' ![/red]")
console.print(f"[red]Error decoding JSON: {e} ![/red]")
return False
return True
def _add_monomer_collection(arg_group: argparse._ArgumentGroup) -> None:
arg_group.add_argument(
"-m",
"--monomers",
type=str,
default="Standard",
choices=[MonomerSetParameter()],
help="built-in monomer-set type or json file of monomers",
)
arg_group.add_argument(
"--code-set",
type=str,
metavar="CODE-SET",
required=False,
default=None,
help="code-set, if not specified primary code-set is used",
)
def _get_monomer_collection(args: argparse.Namespace) -> oechem.OEMonomerSet:
monomers = oechem.OEMonomerSet()
match args.monomers:
case "Standard":
oechem.OELoadStandardMonomerSet(monomers)
case "OpenEye":
oechem.OELoadOpenEyeMonomerSet(monomers)
case _:
oechem.OEReadMonomerSet(monomers, args.monomers)
return monomers
setattr(main, "__SCRIPT_NAME__", __SCRIPT_NAME__)
setattr(main, "__SCRIPT_DESC__", __SCRIPT_DESC__)
setattr(main, "__SCRIPT_TOOLKITS__", __SCRIPT_TOOLKITS__)
setattr(main, "__SCRIPT_KEYWORDS__", __SCRIPT_KEYWORDS__)
setattr(main, "__SCRIPT_CATEGORIES__", __SCRIPT_CATEGORIES__)
if __name__ == "__main__":
sys.exit(main())
Discussion
The monomers2plot script uses the GraphSim TK toolkit to generate a fingerprint for each monomer in a given set. The bits of the fingerprints are then used in scikit-learn’s PCA (Principal component analysis) function to generate 2D coordinates that are then used in the plot generated with bokeh.
Usage
See Download section to download the script.
> monomers2plot --help
By default, the monomers2plot script loads OEChem TK’s
built-in Standard monomer set.
> monomers2plot --html monomers.html
The command above will generate the following plot shown at the top of this page.
- --monomers OpenEye
- --code-set CODE_SET
OEChem TK’s built-in OpenEye monomer-set can be loaded with the --monomers OpenEye
parameter.
> monomers2plot --monomers OpenEye --html monomers.html
Since the OpenEye monomer set contains multiple code-sets (OpenEye - default, Standard, PDB, ChEMBL), the
--code-set parameter can be used to generate different versions of the HELM string.
> monomers2plot --monomers OpenEye --code-set ChEMBL --html monomers.html
- --monomers JSON-MONOMER-FILE
The following example shows how to output a custom monomer set
defined in a json file
(custom-monomers.json)
> monomers2plot --monomers custom-monomers.json --html monomers.html
See also in OEChem TK manual
API
OEMonomer class
OEMonomerSet class
OEReadMonomerSet, OELoadStandardMonomerSet, and OELoadOpenEyeMonomerSet functions
See also in GraphSim TK manual
Theory
Fingerprint Generation chapter
API
OEFingerPrint class
OEMakeFP function
See also in OEGrapheme TK manual
API
OEDrawMonomer function