Back to list
GPTomics

bio-pdb-structure-modification

by GPTomics

a set of SKILLS.md for doing bioinformatics with agents like claude code

65🍴 17📅 Jan 24, 2026

SKILL.md


name: bio-pdb-structure-modification description: Modify protein structures using Biopython Bio.PDB. Use when transforming coordinates, removing atoms or residues, adding new entities, modifying B-factors and occupancies, or building structures programmatically. tool_type: python primary_tool: Bio.PDB

Structure Modification

Transform coordinates, remove/add entities, modify properties, and build structures programmatically.

Required Imports

from Bio.PDB import PDBParser, PDBIO, StructureBuilder
from Bio.PDB.Structure import Structure
from Bio.PDB.Model import Model
from Bio.PDB.Chain import Chain
from Bio.PDB.Residue import Residue
from Bio.PDB.Atom import Atom
import numpy as np

Transforming Coordinates

from Bio.PDB import PDBParser, PDBIO
import numpy as np

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

# Translate all atoms
translation = np.array([10.0, 0.0, 0.0])
for atom in structure.get_atoms():
    atom.coord = atom.coord + translation

# Save transformed structure
io = PDBIO()
io.set_structure(structure)
io.save('translated.pdb')

Rotation Around Axis

from Bio.PDB import PDBParser
from Bio.PDB.vectors import rotaxis
import numpy as np

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

# Rotate around Z axis by 90 degrees
angle = np.radians(90)
axis = np.array([0, 0, 1])

# Get center of mass for rotation origin
coords = np.array([a.coord for a in structure.get_atoms()])
center = coords.mean(axis=0)

# Rotation matrix
cos_a = np.cos(angle)
sin_a = np.sin(angle)
rot_matrix = np.array([
    [cos_a, -sin_a, 0],
    [sin_a, cos_a, 0],
    [0, 0, 1]
])

# Apply rotation around center
for atom in structure.get_atoms():
    atom.coord = np.dot(rot_matrix, atom.coord - center) + center

Applying Transformation Matrix

from Bio.PDB import PDBParser
import numpy as np

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

# 4x4 transformation matrix (rotation + translation)
# From superimposition or external source
transform = np.array([
    [1.0, 0.0, 0.0, 10.0],
    [0.0, 1.0, 0.0, 5.0],
    [0.0, 0.0, 1.0, 0.0],
    [0.0, 0.0, 0.0, 1.0]
])

rotation = transform[:3, :3]
translation = transform[:3, 3]

for atom in structure.get_atoms():
    atom.coord = np.dot(rotation, atom.coord) + translation

Center Structure at Origin

from Bio.PDB import PDBParser
import numpy as np

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

# Calculate center
coords = np.array([a.coord for a in structure.get_atoms()])
center = coords.mean(axis=0)

# Translate to origin
for atom in structure.get_atoms():
    atom.coord = atom.coord - center

Removing Atoms

from Bio.PDB import PDBParser, PDBIO

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

# Remove hydrogens
for residue in structure.get_residues():
    atoms_to_remove = [a.id for a in residue if a.element == 'H']
    for atom_id in atoms_to_remove:
        residue.detach_child(atom_id)

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

Removing Residues

from Bio.PDB import PDBParser, PDBIO

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

# Remove water molecules
for model in structure:
    for chain in model:
        residues_to_remove = [r.id for r in chain if r.id[0] == 'W']
        for res_id in residues_to_remove:
            chain.detach_child(res_id)

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

Removing a Chain

from Bio.PDB import PDBParser, PDBIO

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

# Remove chain B
model = structure[0]
if model.has_id('B'):
    model.detach_child('B')

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

Modifying B-factors

from Bio.PDB import PDBParser, PDBIO

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

# Set all B-factors to same value
for atom in structure.get_atoms():
    atom.bfactor = 20.0

# Or set based on residue property (e.g., conservation score)
conservation_scores = {100: 9.0, 101: 5.0, 102: 3.0}  # resnum -> score
for residue in structure.get_residues():
    resnum = residue.id[1]
    score = conservation_scores.get(resnum, 5.0)
    for atom in residue:
        atom.bfactor = score * 10  # Scale to B-factor range

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

Modifying Occupancy

from Bio.PDB import PDBParser, PDBIO

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

# Set occupancy for specific chain
for atom in structure[0]['A'].get_atoms():
    atom.occupancy = 0.5

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

Renumbering Residues

from Bio.PDB import PDBParser, PDBIO

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

chain = structure[0]['A']

# Renumber sequentially starting from 1
new_residues = []
for i, residue in enumerate(chain, start=1):
    hetfield, _, icode = residue.id
    new_id = (hetfield, i, icode)
    residue.id = new_id
    new_residues.append(residue)

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

Changing Chain ID

from Bio.PDB import PDBParser, PDBIO

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

# Rename chain A to X
model = structure[0]
chain = model['A']
chain.id = 'X'

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

Building Structure from Scratch

from Bio.PDB.Structure import Structure
from Bio.PDB.Model import Model
from Bio.PDB.Chain import Chain
from Bio.PDB.Residue import Residue
from Bio.PDB.Atom import Atom
from Bio.PDB import PDBIO
import numpy as np

# Create hierarchy
structure = Structure('new_struct')
model = Model(0)
chain = Chain('A')
residue = Residue((' ', 1, ' '), 'ALA', '')

# Add atoms
ca = Atom('CA', np.array([0.0, 0.0, 0.0]), 20.0, 1.0, ' ', 'CA', 1, 'C')
cb = Atom('CB', np.array([1.5, 0.0, 0.0]), 20.0, 1.0, ' ', 'CB', 2, 'C')

residue.add(ca)
residue.add(cb)
chain.add(residue)
model.add(chain)
structure.add(model)

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

Using StructureBuilder

from Bio.PDB import StructureBuilder, PDBIO
import numpy as np

sb = StructureBuilder.StructureBuilder()
sb.init_structure('built')
sb.init_model(0)
sb.init_chain('A')
sb.init_seg(' ')

# Add residue with atoms
sb.init_residue('ALA', ' ', 1, ' ')
sb.init_atom('N', np.array([-1.0, 0.0, 0.0]), 20.0, 1.0, ' ', 'N', 1, 'N')
sb.init_atom('CA', np.array([0.0, 0.0, 0.0]), 20.0, 1.0, ' ', 'CA', 2, 'C')
sb.init_atom('C', np.array([1.0, 0.0, 0.0]), 20.0, 1.0, ' ', 'C', 3, 'C')
sb.init_atom('O', np.array([1.5, 1.0, 0.0]), 20.0, 1.0, ' ', 'O', 4, 'O')

sb.init_residue('GLY', ' ', 2, ' ')
sb.init_atom('N', np.array([1.5, -1.0, 0.0]), 20.0, 1.0, ' ', 'N', 5, 'N')
sb.init_atom('CA', np.array([2.5, -1.0, 0.0]), 20.0, 1.0, ' ', 'CA', 6, 'C')
sb.init_atom('C', np.array([3.5, -1.0, 0.0]), 20.0, 1.0, ' ', 'C', 7, 'C')
sb.init_atom('O', np.array([4.0, 0.0, 0.0]), 20.0, 1.0, ' ', 'O', 8, 'O')

structure = sb.get_structure()

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

Adding a Residue to Existing Chain

from Bio.PDB import PDBParser, PDBIO
from Bio.PDB.Residue import Residue
from Bio.PDB.Atom import Atom
import numpy as np

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

chain = structure[0]['A']

# Create new residue
new_residue = Residue((' ', 999, ' '), 'ALA', '')
ca = Atom('CA', np.array([50.0, 50.0, 50.0]), 20.0, 1.0, ' ', 'CA', 9999, 'C')
new_residue.add(ca)

# Add to chain
chain.add(new_residue)

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

Copying a Chain

from Bio.PDB import PDBParser, PDBIO
from Bio.PDB.Chain import Chain
from Bio.PDB.Residue import Residue
from Bio.PDB.Atom import Atom
import copy

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

# Deep copy chain A as chain B
original_chain = structure[0]['A']
new_chain = Chain('B')

for residue in original_chain:
    new_residue = Residue(residue.id, residue.resname, residue.segid)
    for atom in residue:
        new_atom = Atom(
            atom.name, atom.coord.copy(), atom.bfactor, atom.occupancy,
            atom.altloc, atom.fullname, atom.serial_number, atom.element
        )
        new_residue.add(new_atom)
    new_chain.add(new_residue)

structure[0].add(new_chain)

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

Extract and Save Specific Residues

from Bio.PDB import PDBParser, PDBIO
from Bio.PDB.Structure import Structure
from Bio.PDB.Model import Model
from Bio.PDB.Chain import Chain

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

# Extract residues 50-100
new_structure = Structure('subset')
new_model = Model(0)
new_chain = Chain('A')

for residue in structure[0]['A']:
    if 50 <= residue.id[1] <= 100 and residue.id[0] == ' ':
        new_chain.add(residue.copy())

new_model.add(new_chain)
new_structure.add(new_model)

io = PDBIO()
io.set_structure(new_structure)
io.save('residues_50_100.pdb')

Merge Two Structures

from Bio.PDB import PDBParser, PDBIO

parser = PDBParser(QUIET=True)
struct1 = parser.get_structure('s1', 'structure1.pdb')
struct2 = parser.get_structure('s2', 'structure2.pdb')

# Add chains from struct2 to struct1 (rename to avoid conflicts)
for chain in struct2[0]:
    new_id = chr(ord(chain.id) + 10)  # Offset chain ID
    chain.id = new_id
    struct1[0].add(chain)

io = PDBIO()
io.set_structure(struct1)
io.save('merged.pdb')
  • structure-io - Parse and write structure files
  • structure-navigation - Access chains, residues, atoms
  • geometric-analysis - Calculate distances, angles, RMSD
  • sequence-manipulation - Generate sequences from modified structures

Score

Total Score

65/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

Reviews

💬

Reviews coming soon