본문으로 건너뛰기
cccskills
무료GitHub에 공개

bio-pdb-structure-io

Read, inspect, download, and write protein structure files with Biopython Bio.PDB. Check chains, residues, atoms, and experimental metadata, convert between PDB and mmCIF formats, or save selected parts of a structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, or writing structures to various formats.

설치 방법 보기

이럴 때 유용합니다

  • Inspect protein structure files and experimental metadata
  • Download multiple structures from RCSB PDB
  • Convert between PDB and mmCIF
  • Save selected chains, residues, or atoms

포함된 파일(5)

  • SKILL.md7.5 KB
  • examples/download_structure.py469 B
  • examples/extract_chain.py552 B
  • examples/parse_pdb.py658 B
  • usage-guide.md2.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Version Compatibility

Reference examples tested with: BioPython 1.83+, scanpy 1.10+

Before using code patterns, verify installed versions match. If versions differ:

  • Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Structure I/O

"Read a PDB file" → Parse protein structure files (PDB, mmCIF, MMTF), download from RCSB PDB, and write structures to various formats.

  • Python: Bio.PDB.PDBParser().get_structure('id', 'file.pdb'), Bio.PDB.MMCIFParser()

Parse, download, and write protein structure files in PDB, mmCIF, and MMTF formats.

Required Imports

from Bio.PDB import PDBParser, MMCIFParser, PDBIO, MMCIFIO, PDBList
from Bio.PDB.MMCIF2Dict import MMCIF2Dict

Supported Formats

FormatParserWriterDescription
PDBPDBParserPDBIOLegacy format, limited to 99999 atoms
mmCIFMMCIFParserMMCIFIOModern standard, full metadata
MMTFMMTFParser-Compact binary (read-only in Biopython)
BinaryCIFBinaryCIFParser-Compact binary, RCSB recommended

Parsing PDB Files

from Bio.PDB import PDBParser

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

print(f'Structure ID: {structure.id}')
print(f'Number of models: {len(list(structure.get_models()))}')
print(f'Number of chains: {len(list(structure.get_chains()))}')
print(f'Number of residues: {len(list(structure.get_residues()))}')
print(f'Number of atoms: {len(list(structure.get_atoms()))}')

Parsing mmCIF Files

from Bio.PDB import MMCIFParser

parser = MMCIFParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.cif')

# mmCIF is the modern standard - use for new workflows
print(f'Structure: {structure.id}')

Parsing MMTF Files

from Bio.PDB.MMTFParser import MMTFParser

parser = MMTFParser()
structure = parser.get_structure('1abc.mmtf')

Parsing BinaryCIF Files

from Bio.PDB import BinaryCIFParser

parser = BinaryCIFParser()
structure = parser.get_structure('1abc', '1abc.bcif')

Downloading from RCSB PDB

from Bio.PDB import PDBList

pdbl = PDBList()

# Download single structure (mmCIF by default)
file_path = pdbl.retrieve_pdb_file('1ABC', pdir='.', file_format='mmCif')
print(f'Downloaded: {file_path}')

# Download as PDB format
file_path = pdbl.retrieve_pdb_file('1ABC', pdir='.', file_format='pdb')

# Download biological assembly
file_path = pdbl.retrieve_pdb_file('1ABC', pdir='.', file_format='mmCif', assembly_num=1)

# Get list of all PDB entries
all_entries = pdbl.get_all_entries()
print(f'Total PDB entries: {len(all_entries)}')

# Get obsolete entries
obsolete = pdbl.get_all_obsolete()

Batch Downloading

from Bio.PDB import PDBList

pdbl = PDBList()
pdb_ids = ['1ABC', '2XYZ', '3DEF']

for pdb_id in pdb_ids:
    file_path = pdbl.retrieve_pdb_file(pdb_id, pdir='structures/', file_format='mmCif')
    print(f'Downloaded: {pdb_id}')

Writing PDB Files

from Bio.PDB import PDBParser, PDBIO

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

io = PDBIO()
io.set_structure(structure)
io.save('output.pdb')

Writing mmCIF Files

from Bio.PDB import MMCIFParser, MMCIFIO

parser = MMCIFParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.cif')

io = MMCIFIO()
io.set_structure(structure)
io.save('output.cif')

Selective Output with Select Class

from Bio.PDB import PDBParser, PDBIO, Select

class ChainSelect(Select):
    def __init__(self, chain_id):
        self.chain_id = chain_id

    def accept_chain(self, chain):
        return chain.id == self.chain_id

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

io = PDBIO()
io.set_structure(structure)
io.save('chain_A.pdb', ChainSelect('A'))

Select Class Methods

from Bio.PDB import Select

class CustomSelect(Select):
    def accept_model(self, model):
        return model.id == 0  # Only first model

    def accept_chain(self, chain):
        return chain.id in ['A', 'B']  # Only chains A and B

    def accept_residue(self, residue):
        return residue.id[0] == ' '  # Exclude hetero residues

    def accept_atom(self, atom):
        return atom.element != 'H'  # Exclude hydrogens

Extracting Header Information

from Bio.PDB import PDBParser

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

header = structure.header
print(f"Name: {header.get('name', 'Unknown')}")
print(f"Resolution: {header.get('resolution', 'N/A')}")
print(f"Structure method: {header.get('structure_method', 'Unknown')}")
print(f"Deposition date: {header.get('deposition_date', 'Unknown')}")

mmCIF Metadata with MMCIF2Dict

from Bio.PDB.MMCIF2Dict import MMCIF2Dict

mmcif_dict = MMCIF2Dict('1abc.cif')

# Access any mmCIF field
print(f"Entry ID: {mmcif_dict['_entry.id']}")
print(f"Resolution: {mmcif_dict.get('_refine.ls_d_res_high', ['N/A'])[0]}")
print(f"Method: {mmcif_dict.get('_exptl.method', ['Unknown'])[0]}")

# List all available fields
print(f"Available fields: {len(mmcif_dict.keys())}")

Quick Structure Inspection

from Bio.PDB import PDBParser

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

print(f'Models: {[m.id for m in structure]}')
for model in structure:
    print(f'  Model {model.id}:')
    for chain in model:
        residues = list(chain.get_residues())
        atoms = list(chain.get_atoms())
        print(f'    Chain {chain.id}: {len(residues)} residues, {len(atoms)} atoms')

Format Conversion

from Bio.PDB import PDBParser, MMCIFParser, PDBIO, MMCIFIO

# PDB to mmCIF
parser = PDBParser(QUIET=True)
structure = parser.get_structure('prot', 'protein.pdb')
io = MMCIFIO()
io.set_structure(structure)
io.save('protein.cif')

# mmCIF to PDB
parser = MMCIFParser(QUIET=True)
structure = parser.get_structure('prot', 'protein.cif')
io = PDBIO()
io.set_structure(structure)
io.save('protein.pdb')

Writing PQR Files

from Bio.PDB import PDBParser, PDBIO

parser = PDBParser(QUIET=True)
structure = parser.get_structure('1abc', '1abc.pdb')

# PQR format includes charge and radius instead of occupancy and B-factor
io = PDBIO(is_pqr=True)
io.set_structure(structure)
io.save('output.pqr')

Handling Parser Warnings

from Bio.PDB import PDBParser
import warnings

# Suppress warnings
parser = PDBParser(QUIET=True)

# Or capture warnings
parser = PDBParser(QUIET=False)
with warnings.catch_warnings(record=True) as w:
    warnings.simplefilter('always')
    structure = parser.get_structure('1abc', '1abc.pdb')
    if w:
        print(f'Warnings: {len(w)}')
        for warning in w:
            print(f'  {warning.message}')

Related Skills

  • structure-navigation - Traverse SMCRA hierarchy to access chains, residues, atoms
  • geometric-analysis - Measure distances, angles, and superimpose structures
  • structure-modification - Modify coordinates and properties before writing
  • database-access/entrez-fetch - Fetch structure metadata from NCBI/UniProt

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

adaptyv

무료

Support protein design with cloud laboratory testing for binding, expression, thermal stability, and enzyme activity. Covers sequence optimization, submitting experiments through the Adaptyv API, checking progress, and downloading experimental results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Validate designed proteins with laboratory assays
  • Screen and redesign sequences for better solubility
  • Submit protein testing experiments through an API
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Build flexible daily plans that account for ADHD-related difficulties with time estimation and getting started. Narrow priorities to three tasks, add transition buffers, and choose small next actions that match the energy available that day.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Choosing three priorities for today
  • Planning a schedule with transition buffers
  • Finding a small first step when starting feels difficult
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

aeon

무료

Build Python workflows for data recorded over time, including classification, forecasting, anomaly detection, and pattern search. Using aeon, the skill guides preprocessing, algorithm selection, feature extraction, and evaluation through interfaces compatible with scikit-learn.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Classify time series by their patterns
  • Forecast future values from historical data
  • Detect anomalies and change points
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Use a browser to research topics, extract page information, fill forms, and test websites. Guides agents through identifying page controls, interacting with web apps, saving screenshots or PDFs, and reusing saved login sessions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Researching topics and reading web articles
  • Filling and submitting online forms
  • Extracting page text and links
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

Combine health measurements, exercise, sleep, nutrition, and mental health records to examine trends, unusual changes, and estimated risks. The skill produces personalized suggestions and text or interactive HTML reports using local data without external API calls.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Review health records together in a comprehensive report
  • Explore links between sleep, mood, exercise, and weight
  • Summarize estimated disease and nutrition risks
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

alphafold

무료

Predict structures for designed protein sequences and protein complexes with AlphaFold2 or ColabFold. Inspect structure files and confidence scores to assess folding and chain interfaces, with guidance for local runs, Modal execution, and common prediction errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Check predicted folding of a designed protein sequence
  • Predict a binder–target protein complex
  • Review structure and interface confidence scores
FreedomIntelligence/OpenClaw-Medical-Skills3.1천2026년 7월 21일 업데이트

FreedomIntelligence의 스킬 모두 보기

이 스킬의 문제 신고