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Pdb

biotender-max/pdb

> (1) Need to download a structure by PDB ID, (2) Search for similar structures, (3) Prepare target for binder design, (4) Extract specific chains or domains, (5) Get structure metadata. For sequence lookup, use uniprot. For binder design workflow, use binder-design.

This is a copy. The original lives at adaptyvbio/pdb.

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill pdb

The instruction itself

17 sections, as written by the author

PDB Database Access

Note: This skill uses the RCSB PDB web API directly. No Modal deployment needed - all operations run locally via HTTP requests.

Fetching Structures

By PDB ID

# Download PDB file
curl -o 1alu.pdb "https://files.rcsb.org/download/1ALU.pdb"

# Download mmCIF
curl -o 1alu.cif "https://files.rcsb.org/download/1ALU.cif"

Using Python

from Bio.PDB import PDBList

pdbl = PDBList()
pdbl.retrieve_pdb_file("1ABC", pdir="structures/", file_format="pdb")

Using RCSB API

import requests

def fetch_pdb(pdb_id: str, format: str = "pdb") -> str:
    """Fetch structure from RCSB PDB."""
    url = f"https://files.rcsb.org/download/{pdb_id}.{format}"
    response = requests.get(url)
    response.raise_for_status()
    return response.text

def fetch_fasta(pdb_id: str) -> str:
    """Fetch sequence in FASTA format."""
    url = f"https://www.rcsb.org/fasta/entry/{pdb_id}"
    return requests.get(url).text

# Example usage
pdb_content = fetch_pdb("1ALU")
with open("1ALU.pdb", "w") as f:
    f.write(pdb_content)

Structure Preparation

Selecting Chains

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

# Extract chain A
parser = PDBParser()
structure = parser.get_structure("protein", "1abc.pdb")
io = PDBIO()
io.set_structure(structure)
io.save("chain_A.pdb", ChainSelect("A"))

Trimming to Binding Region

def trim_around_residues(pdb_file, center_residues, buffer=10.0):
    """Trim structure to region around specified residues."""
    parser = PDBParser()
    structure = parser.get_structure("protein", pdb_file)

    # Get center coordinates
    center_coords = []
    for res in structure.get_residues():
        if res.id[1] in center_residues:
            center_coords.extend([a.coord for a in res.get_atoms()])

    center = np.mean(center_coords, axis=0)

    # Keep residues within buffer
    class RegionSelect(Select):
        def accept_residue(self, res):
            for atom in res.get_atoms():
                if np.linalg.norm(atom.coord - center) < buffer:
                    return True
            return False

    io = PDBIO()
    io.set_structure(structure)
    io.save("trimmed.pdb", RegionSelect())

Searching PDB

RCSB Search API

import requests

query = {
    "query": {
        "type": "terminal",
        "service": "full_text",
        "parameters": {
            "value": "EGFR kinase domain"
        }
    },
    "return_type": "entry"
}

response = requests.post(
    "https://search.rcsb.org/rcsbsearch/v2/query",
    json=query
)
results = response.json()

By Sequence Similarity

query = {
    "query": {
        "type": "terminal",
        "service": "sequence",
        "parameters": {
            "value": "MKTAYIAKQRQISFVK...",
            "evalue_cutoff": 1e-10,
            "identity_cutoff": 0.9
        }
    }
}

Structure Analysis

Get Chain Info

def get_structure_info(pdb_file):
    parser = PDBParser(QUIET=True)
    structure = parser.get_structure("protein", pdb_file)

    info = {
        "chains": [],
        "total_residues": 0
    }

    for model in structure:
        for chain in model:
            residues = list(chain.get_residues())
            info["chains"].append({
                "id": chain.id,
                "length": len(residues),
                "first_res": residues[0].id[1],
                "last_res": residues[-1].id[1]
            })
            info["total_residues"] += len(residues)

    return info

Find Interface Residues

def find_interface_residues(pdb_file, chain_a, chain_b, distance=4.0):
    """Find residues at interface between two chains."""
    parser = PDBParser(QUIET=True)
    structure = parser.get_structure("complex", pdb_file)

    interface_a = set()
    interface_b = set()

    for res_a in structure[0][chain_a].get_residues():
        for res_b in structure[0][chain_b].get_residues():
            for atom_a in res_a.get_atoms():
                for atom_b in res_b.get_atoms():
                    if atom_a - atom_b < distance:
                        interface_a.add(res_a.id[1])
                        interface_b.add(res_b.id[1])

    return interface_a, interface_b

Common Tasks for Binder Design

Target Preparation Checklist

  • Download structure: curl -o target.pdb "https://files.rcsb.org/download/XXXX.pdb"
  • Identify target chain
  • Remove waters and ligands (if needed)
  • Trim to binding region + buffer
  • Identify potential hotspots
  • Renumber if needed

Troubleshooting

Structure not found: Check PDB ID format (4 characters)

Multiple models: Select first model for design

Missing residues: Check for gaps in structure


Next: Use structure with boltzgen (recommended) or rfdiffusion for design.

How to use it

Copy the folder

Take biotender-max/pdb from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.