本文へ移動
cccskills
無料GitHub で公開

pymol

Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.

インストール方法を見る

含まれるファイル(4)

  • SKILL.md6.5 KB
  • references/citation.bib143 B
  • references/PYMOL_REFERENCE.md5.3 KB
  • references/RECIPES.md11.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

PyMOL

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If .licenses/pymol_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the license at https://www.pymol.org/, then (2) create the file recording the notification text and timestamp.

Overview

All PyMOL commands run on the host via uv with OSMesa software rendering — no GPU, display, or X server is needed. Structure files must be downloaded to the host before running PyMOL.

Do NOT use when:

  • The user wants to run AlphaFold predictions.
  • The user wants docking or molecular dynamics simulations.
  • The user only has a sequence and no structure file — fetch the structure first. Check if any other installed skills can retrieve structures from the PDB or AlphaFold Database before proceeding.

Setup (Agent Instructions)

Ensure that uv is installed on the host system. The PyMOL scripts use PEP 0723 headers to declare their dependencies, and uv run will automatically handle installing them (including pymol-open-source-whl) when the script is executed.

Core Rules

  • Output paths must be absolute or relative to the user's project root. Always run PyMOL scripts from the user's project directory.
  • Software rendering only. Use cmd.png() for output. Never use cmd.draw() or cmd.ray() with hardware acceleration — OSMesa does not support it. Set environment variable PYOPENGL_PLATFORM=osmesa for headless rendering.
  • Always save a .pse session file alongside any PNG output. This lets the user open the session in their local PyMOL for further inspection.
  • Always call cmd.quit() at the end of every PyMOL script. Omitting it causes the process to stop responding.
  • Init boilerplate is mandatory. Every PyMOL script must begin with the initialization sequence. from pymol import cmd must come after finish_launching(), not before.
  • See references/PYMOL_REFERENCE.md for selection syntax, common commands, and gotchas.
  • Pre-Flight File Check: Before writing the PyMOL script or running it, you MUST verify that the requested structure file actually exists on the host machine.
  • Verify Structure Load: After loading a structure with cmd.load(), always verify it succeeded by checking cmd.count_atoms("all"). If the result is 0, print an error to stdout and call cmd.quit() immediately.
  • Auto-detect Alpha-Carbon Trace: For a cartoon representation your PyMOL scripts should automatically detect if the structure is an alpha-carbon trace (cmd.count_atoms("name CA") == cmd.count_atoms("all")), then you MUST follow the Alpha carbon trace cartoon recipe.
  • Notification: If this skill is used, ensure this is mentioned in the output.

Quick Start

  • Ensure structure files are downloaded to a directory in the user's project.
  • Write a PyMOL Python script (e.g., render.py) with the required init boilerplate and PEP 0723 header.
  • Run it via uv run: bash uv run render.py

Minimal example script (render.py)

# /// script
# requires-python = ">=3.10, <3.13"
# dependencies = [
#     "pymol-open-source-whl",
# ]
# ///

import os
import sys

# Set environment variable for headless rendering
os.environ["PYOPENGL_PLATFORM"] = "osmesa"

import pymol # pytype: disable=import-error
pymol.pymol_argv = ["pymol", "-cq"]
pymol.finish_launching()

from pymol import cmd # pytype: disable=import-error

cmd.load("AF-P00520-F1-model_v4.cif", "structure")
cmd.show("cartoon")
cmd.color("green", "ss h")
cmd.color("yellow", "ss s")
cmd.color("gray", "ss l+''")
cmd.orient()
cmd.set("ray_opaque_background", 1)
cmd.png("output/render.png", width=1200, height=900, dpi=150)
cmd.save("output/session.pse")
cmd.quit()

Common Recipes

See references/RECIPES.md for complete, copy-paste ready recipes. Available recipes:

  • Cartoon with secondary structure coloring — basic helix/sheet/loop coloring
  • Alpha carbon trace cartoon — force cartoon representation for CA-only structures
  • B-factor (pLDDT) coloring — continuous spectrum coloring by B-factor
  • AlphaFold pLDDT coloring — canonical threshold-based confidence colors
  • Highlight specific residues — show active site or key residues as sticks
  • Surface rendering — transparent surface over cartoon
  • Electrostatic surface rendering — vacuum electrostatics (qualitative)
  • Multi-chain complex colors — automatic per-chain coloring
  • B-factor putty analysis — tube width proportional to flexibility
  • Cavity and pocket visualization — surface cavity detection with ligand focus
  • Multi-structure batch rendering — render a directory of structures
  • Measure distance between residues — CA–CA distance with labels
  • Zoom into binding pocket — simple pocket focus
  • Protein-ligand interaction — ligand isolation, styled rendering, polar contacts
  • Two-structure superposition with RMSD — align/cealign with auto-fallback
  • In silico mutagenesis — mutate residues with the mutagenesis wizard
  • Load and modify an existing session — re-open a .pse file

Interpreting Output

  • The output/ directory contains PNG images and a .pse session file.
  • Any measurements or metrics (distances, RMSD, atom counts) are printed to stdout by the PyMOL script. Report these values to the user.
  • Present PNG images to the user and describe the visualization.
  • Tell the user they can open the .pse file in their local PyMOL to further explore, rotate, or modify the visualization.
  • If the user wants modifications, load the saved .pse in a new script and re-run.
  • Large sessions with surfaces can exceed the --max_output_mb limit (default 500 MB). Increase it with --max_output_mb=1000 if needed.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

Constructs deep-links and URLs for the AlphaGenome Atlas website. Supports generating single-variant exploration links (1-based chr:pos:ref>alt), genomic locus views (1-based closed chr:start-end), candidate summary tables, and AlphaGenome reference vs. alternate predictions. Use whenever visualizing, exploring, charting, or linking genetic variants and genomic loci on the AlphaGenome Atlas, or when asked to inspect, view, or link predictions for a genomic variant.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue/cell-type ontologies (UBERON/CL) or analyzing variants in chr:pos:ref>alt format.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

Score, annotate, and analyze the functional impact of genetic variants using AlphaGenome Variant Impact (AVI) scores. Query variants in chr:pos:ref>alt format, annotate VCF/tabular callsets, perform saturation mutagenesis window scans (1-based closed chr:start-end), and extract GENCODE v46 GTF gene/exon/junction coordinates all via the AlphaGenome Atlas API.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility/inclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.

日本語の概要は準備中です。原文の説明を表示しています。

google-deepmind/science-skills3,2402026年10月10日 更新

google-deepmind のスキルをすべて見る

このスキルの問題を報告する