本文へ移動
cccskills
無料GitHub で公開

query-interpro

Query InterPro for protein domains and families. Use when user asks about protein domains, functional sites, protein families, domain architecture, or motifs. Triggers on "interpro", "protein domain", "domain architecture", "protein family", "functional site", "motif".

インストール方法を見る

含まれるファイル(1)

  • SKILL.md2.7 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。

InterPro Protein Domain Database

Query the InterPro REST API for protein domains, families, and functional sites.

When to Use

  • User asks about domains in a protein
  • User wants to know what family a protein belongs to
  • User asks about functional sites or motifs
  • User wants domain architecture visualization

How to Execute

import requests
import json

BASE_URL = "https://www.ebi.ac.uk/interpro/api"

# 1. Get protein annotation (domains/families for a UniProt ID)
def get_protein_domains(uniprot_id):
    url = f"{BASE_URL}/protein/uniprot/{uniprot_id}"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 2. Get InterPro entry details
def get_interpro_entry(interpro_id):
    url = f"{BASE_URL}/entry/interpro/{interpro_id}"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 3. Search InterPro by text
def search_interpro(query, max_results=10):
    url = f"{BASE_URL}/entry/interpro"
    params = {"search": query, "page_size": max_results}
    r = requests.get(url, params=params, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 4. Get domain matches for a protein
def get_domain_matches(uniprot_id):
    url = f"{BASE_URL}/protein/uniprot/{uniprot_id}/entry/interpro"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# Example: TP53 domains
domains = get_domain_matches("P04637")
for result in domains.get("results", []):
    meta = result.get("metadata", {})
    name = meta.get("name", "N/A")
    ipr_type = meta.get("type", "N/A")
    accession = meta.get("accession", "N/A")
    proteins = result.get("proteins", [])
    if proteins:
        locations = proteins[0].get("entry_protein_locations", [])
        for loc in locations:
            for frag in loc.get("fragments", []):
                start = frag.get("start", "?")
                end = frag.get("end", "?")
                print(f"{accession} ({ipr_type}): {name} [{start}-{end}]")

Entry Types

  • domain — Structural/functional domain
  • family — Protein family
  • homologous_superfamily — Distant homologs
  • repeat — Repeated motif
  • site — Active/binding site

Follow-up Suggestions

  • "Want me to compare domains across species?"
  • "Should I map these domains onto the 3D structure?"
  • "Want me to find other proteins with the same domain?"

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

Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

alphafold

無料

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-qc.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

AlphaFold2 / AlphaFold-Multimer structure prediction for validation and confidence scoring. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm2-sequence-scoring. For QC thresholds, use protein-design-qc.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Workflow for event-level and isoform-level splicing analysis with sashimi-ready outputs and splice QC.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

atac-seq

無料

ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

bindcraft

無料

End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.

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。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

BioTender-max のスキルをすべて見る

このスキルの問題を報告する