# Scientific Structural Proteomics > 構造プロテオミクス統合スキル。EMDB クライオ EM、PDBe 構造データ、 Proteins API (UniProt)、Complex Portal 複合体、DeepGO 機能予測、 EVE 変異影響評価の統合パイプライン。 - Skill: `nahisaho/scientific-structural-proteomics-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add nahisaho/scientific-structural-proteomics-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/nahisaho/scientific-structural-proteomics-2/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Integrations & APIs - Author: nahisaho (https://skillmd.com/u/nahisaho) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/nahisaho/scientific-structural-proteomics-2 --- # Scientific Structural Proteomics 6 つの構造・機能データベースを統合した タンパク質構造・機能プロファイリングパイプラインを提供する。 ## When to Use - PDB エントリの詳細構造情報 (分解能, 実験手法, 二次構造) を取得するとき - クライオ EM マップ情報を EMDB から取得するとき - UniProt タンパク質のドメイン・変異・ゲノムマッピングを調べるとき - タンパク質複合体のサブユニット構成を Complex Portal で調べるとき - DeepGO で配列ベースの GO 機能予測を行うとき - EVE で missense 変異の病原性スコアを取得するとき --- ## Quick Start ## 1. PDBe 構造データ取得 ```python import requests import pandas as pd PDBE_API = "https://www.ebi.ac.uk/pdbe/api" def get_pdbe_entry(pdb_id): """ PDBe エントリのサマリー・品質・二次構造を取得。 Parameters: pdb_id: str — PDB ID (e.g., "1cbs") ToolUniverse: pdbe_get_entry_summary(pdb_id=pdb_id) pdbe_get_entry_quality(pdb_id=pdb_id) pdbe_get_entry_experiment(pdb_id=pdb_id) pdbe_get_entry_molecules(pdb_id=pdb_id) pdbe_get_entry_secondary_structure(pdb_id=pdb_id) pdbe_get_entry_assemblies(pdb_id=pdb_id) pdbe_get_entry_publications(pdb_id=pdb_id) """ pdb = pdb_id.lower() # Summary resp_s = requests.get(f"{PDBE_API}/pdb/entry/summary/{pdb}") resp_s.raise_for_status() summary = resp_s.json().get(pdb, [{}])[0] # Quality resp_q = requests.get(f"{PDBE_API}/pdb/entry/quality/{pdb}") quality = ( resp_q.json().get(pdb, [{}])[0] if resp_q.status_code == 200 else {} ) # Experiment resp_e = requests.get(f"{PDBE_API}/pdb/entry/experiment/{pdb}") experiment = ( resp_e.json().get(pdb, [{}])[0] if resp_e.status_code == 200 else {} ) entry = { "pdb_id": pdb, "title": summary.get("title", ""), "method": experiment.get("experimental_method", ""), "resolution": experiment.get("resolution", ""), "release_date": summary.get("release_date", ""), "r_factor": quality.get("r_factor", ""), "r_free": quality.get("r_free", ""), } print(f"PDBe {pdb}: {entry['method']} @ {entry['resolution']}Å") return entry, summary, quality ``` ## 2. EMDB クライオ EM 構造 ```python EMDB_API = "https://www.ebi.ac.uk/emdb/api" def get_emdb_structure(emdb_id): """ EMDB エントリの 3D EM マップ情報を取得。 Parameters: emdb_id: str — EMDB ID (e.g., "EMD-1234") ToolUniverse: EMDB_get_structure(emdb_id=emdb_id) EMDB_get_map_info(emdb_id=emdb_id) EMDB_get_sample_info(emdb_id=emdb_id) EMDB_get_imaging_info(emdb_id=emdb_id) EMDB_get_validation(emdb_id=emdb_id) EMDB_get_publications(emdb_id=emdb_id) EMDB_search_structures(query=query) """ url = f"{EMDB_API}/entry/{emdb_id}" resp = requests.get(url) resp.raise_for_status() data = resp.json() admin = data.get("admin", {}) map_info = data.get("map", {}) entry = { "emdb_id": emdb_id, "title": admin.get("title", ""), "resolution": map_info.get("resolution", {}).get("value", ""), "contour_level": map_info.get("contour_level", {}).get("value", ""), "deposition_date": admin.get("deposition_date", ""), } print(f"EMDB {emdb_id}: {entry['resolution']}Å resolution") return entry, data ``` ## 3. Proteins API (UniProt) ドメイン・変異 ```python PROTEINS_API = "https://www.ebi.ac.uk/proteins/api" def get_protein_features(uniprot_id): """ Proteins API からタンパク質のドメイン・変異・修飾情報を取得。 Parameters: uniprot_id: str — UniProt accession (e.g., "P04637") ToolUniverse: proteins_api_get_protein(accession=uniprot_id) proteins_api_get_features(accession=uniprot_id) proteins_api_get_variants(accession=uniprot_id) proteins_api_get_xrefs(accession=uniprot_id) proteins_api_get_genome_mappings(accession=uniprot_id) """ headers = {"Accept": "application/json"} # Protein info resp_p = requests.get( f"{PROTEINS_API}/proteins/{uniprot_id}", headers=headers ) resp_p.raise_for_status() protein = resp_p.json() # Features resp_f = requests.get( f"{PROTEINS_API}/features/{uniprot_id}", headers=headers ) features = resp_f.json() if resp_f.status_code == 200 else {} feature_list = features.get("features", []) domains = [f for f in feature_list if f.get("type") == "DOMAIN"] variants = [f for f in feature_list if f.get("type") == "VARIANT"] print(f"Proteins API {uniprot_id}: " f"{len(domains)} domains, {len(variants)} variants") return protein, feature_list ``` ## 4. Complex Portal 複合体 ```python def get_complex_portal(complex_id): """ Complex Portal からタンパク質複合体の詳細を取得。 Parameters: complex_id: str — Complex Portal ID (e.g., "CPX-1") ToolUniverse: ComplexPortal_get_complex(complex_id=complex_id) ComplexPortal_search_complexes(query=query) """ url = ( f"https://www.ebi.ac.uk/intact/complex-ws/complex/{complex_id}" ) resp = requests.get(url, headers={"Accept": "application/json"}) resp.raise_for_status() data = resp.json() participants = data.get("participants", []) subunits = [] for p in participants: interactor = p.get("interactor", {}) subunits.append({ "identifier": interactor.get("identifier", ""), "name": interactor.get("name", ""), "stoichiometry": p.get("stoichiometry", ""), }) print(f"Complex Portal {complex_id}: " f"{data.get('name', '?')}, {len(subunits)} subunits") return data, subunits ``` ## 5. DeepGO 機能予測 & EVE 変異評価 ```python def predict_deepgo_function(sequence): """ DeepGO でタンパク質配列から GO 機能予測。 ToolUniverse: DeepGO_predict_function(sequence=sequence) """ url = "https://deepgo.cbrc.kaust.edu.sa/deepgo/api/create" resp = requests.post(url, json={"data_format": "fasta", "data": sequence}) resp.raise_for_status() data = resp.json() predictions = data.get("predictions", []) print(f"DeepGO: {len(predictions)} GO term predictions") return predictions def get_eve_variant_score(gene_name, variant=None): """ EVE (Evolutionary model of Variant Effect) による missense 変異の病原性スコアを取得。 ToolUniverse: EVE_get_gene_info(gene_name=gene_name) EVE_get_variant_score(gene_name=gene_name, variant=variant) """ url = f"https://evemodel.org/api/proteins/{gene_name}" if variant: url += f"/variants/{variant}" resp = requests.get(url) resp.raise_for_status() data = resp.json() if variant: score = data.get("eve_score", None) classification = data.get("eve_class", "") print(f"EVE {gene_name} {variant}: score={score}, class={classification}") else: print(f"EVE {gene_name}: found") return data ``` ## References ### Output Files | ファイル | 形式 | |---|---| | `results/pdbe_entry.json` | JSON | | `results/emdb_structure.json` | JSON | | `results/protein_features.json` | JSON | | `results/complex_portal.json` | JSON | | `results/deepgo_predictions.json` | JSON | | `results/eve_scores.json` | JSON | ### 利用可能ツール | カテゴリ | 主要ツール | 用途 | |---|---|---| | PDBe | `pdbe_get_entry_summary` | エントリサマリー | | PDBe | `pdbe_get_entry_quality` | 構造品質 | | PDBe | `pdbe_get_entry_experiment` | 実験手法 | | PDBe | `pdbe_get_entry_molecules` | 分子情報 | | PDBe | `pdbe_get_entry_secondary_structure` | 二次構造 | | PDBe | `pdbe_get_entry_assemblies` | 生物学的集合体 | | PDBe | `pdbe_get_entry_publications` | 文献 | | PDBe | `pdbe_get_entry_related_publications` | 関連文献 | | PDBe | `pdbe_get_entry_observed_residues_ratio` | 観察残基 | | PDBe | `pdbe_get_entry_status` | ステータス | | EMDB | `EMDB_get_structure` | EM 構造 | | EMDB | `EMDB_get_map_info` | マップ情報 | | EMDB | `EMDB_get_sample_info` | サンプル情報 | | EMDB | `EMDB_get_imaging_info` | イメージング | | EMDB | `EMDB_get_validation` | バリデーション | | EMDB | `EMDB_get_publications` | 文献 | | EMDB | `EMDB_search_structures` | EM 構造検索 | | Proteins API | `proteins_api_get_protein` | タンパク質情報 | | Proteins API | `proteins_api_get_features` | ドメイン・特徴 | | Proteins API | `proteins_api_get_variants` | 変異 | | Proteins API | `proteins_api_get_xrefs` | 外部参照 | | Proteins API | `proteins_api_get_genome_mappings` | ゲノムマッピング | | Proteins API | `proteins_api_get_epitopes` | エピトープ | | Proteins API | `proteins_api_get_proteomics` | プロテオミクス | | Proteins API | `proteins_api_get_publications` | 文献 | | Proteins API | `proteins_api_get_comments` | コメント | | Proteins API | `proteins_api_search` | 検索 | | Complex Portal | `ComplexPortal_get_complex` | 複合体詳細 | | Complex Portal | `ComplexPortal_search_complexes` | 複合体検索 | | DeepGO | `DeepGO_predict_function` | GO 機能予測 | | EVE | `EVE_get_gene_info` | 遺伝子情報 | | EVE | `EVE_get_variant_score` | 変異スコア | ### 参照スキル | スキル | 関連 | |---|---| | `scientific-protein-structure-analysis` | タンパク質構造 | | `scientific-proteomics-mass-spectrometry` | プロテオミクス | | `scientific-protein-interaction-network` | PPI | | `scientific-molecular-docking` | ドッキング | | `scientific-variant-interpretation` | 変異解釈 | ### 依存パッケージ `requests`, `pandas`