agentsclimarketplace

Bio restriction sites

Skill FridrichMethod/awesome-skills/skills/bio-restriction-sites

Find restriction enzyme cut sites in DNA sequences using Biopython Bio.Restriction. Search with single enzymes, batches of enzymes, or commercially available enzyme sets. Returns cut positions for linear or circular DNA. Use when finding restriction enzyme cut sites in sequences.From its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill bio-restriction-sites

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.4 KB, ~1.4k tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

Finding Restriction Sites

Core Pattern

from Bio import SeqIO
from Bio.Restriction import EcoRI, BamHI, HindIII, RestrictionBatch, Analysis

record = SeqIO.read('sequence.fasta', 'fasta')
seq = record.seq

# Single enzyme
sites = EcoRI.search(seq)  # Returns list of cut positions

Search with Single Enzyme

from Bio.Restriction import EcoRI

sites = EcoRI.search(seq)
print(f'EcoRI cuts at positions: {sites}')
print(f'Number of sites: {len(sites)}')

# Check if enzyme cuts
if EcoRI.search(seq):
    print('EcoRI cuts this sequence')
else:
    print('EcoRI does not cut')

Search with Multiple Enzymes

from Bio.Restriction import RestrictionBatch, EcoRI, BamHI, HindIII, XhoI

batch = RestrictionBatch([EcoRI, BamHI, HindIII, XhoI])

# Method 1: batch.search()
results = batch.search(seq)
for enzyme, sites in results.items():
    if sites:
        print(f'{enzyme}: {sites}')

# Method 2: Analysis class
analysis = Analysis(batch, seq)
results = analysis.full()

Use Built-in Enzyme Collections

from Bio.Restriction import AllEnzymes, CommOnly

# All known enzymes (800+)
analysis = Analysis(AllEnzymes, seq)

# Commercially available only
analysis = Analysis(CommOnly, seq)

# Get results
results = analysis.full()
for enzyme, sites in results.items():
    if sites:
        print(f'{enzyme}: {sites}')

Linear vs Circular DNA

from Bio.Restriction import EcoRI, Analysis, RestrictionBatch

# Linear DNA (default)
sites_linear = EcoRI.search(seq, linear=True)

# Circular DNA (plasmid)
sites_circular = EcoRI.search(seq, linear=False)

# With Analysis class
batch = RestrictionBatch([EcoRI, BamHI])
analysis = Analysis(batch, seq, linear=False)  # Circular

Filter Results

from Bio.Restriction import Analysis, CommOnly

analysis = Analysis(CommOnly, seq)

# Only enzymes that cut
analysis.print_that_cut()

# Only enzymes that don't cut (non-cutters)
analysis.print_that_dont_cut()

# Enzymes that cut once
analysis.print_once_cutters()

# Enzymes that cut twice
analysis.print_twice_cutters()

# Get as dictionary
cutters = analysis.only_cut()
non_cutters = analysis.only_dont_cut()
once_cutters = analysis.once_cutters()
twice_cutters = analysis.twice_cutters()

Get Enzyme Information

from Bio.Restriction import EcoRI

# Recognition sequence
print(f'Site: {EcoRI.site}')           # GAATTC
print(f'Esite: {EcoRI.esite}')         # Recognition with cut position

# Cut characteristics
print(f'Overhang: {EcoRI.ovhg}')       # 4 (positive = 5' overhang)
print(f'Blunt: {EcoRI.is_blunt()}')    # False
print(f'5\' overhang: {EcoRI.is_5overhang()}')  # True
print(f'3\' overhang: {EcoRI.is_3overhang()}')  # False

# Overhang sequence
print(f'Overhang seq: {EcoRI.ovhgseq}')  # AATT

# Isoschizomers (same recognition, different cut)
print(f'Isoschizomers: {EcoRI.isoschizomers()}')

# Compatible enzymes (same overhang)
print(f'Compatible: {EcoRI.compatible_end()}')

Common Cloning Enzymes

from Bio.Restriction import (
    EcoRI, BamHI, HindIII, XhoI, SalI, NotI, XbaI, SpeI,
    NcoI, NdeI, BglII, PstI, KpnI, SacI, EcoRV, SmaI
)

common_enzymes = RestrictionBatch([
    EcoRI, BamHI, HindIII, XhoI, SalI, NotI, XbaI,
    NcoI, NdeI, BglII, PstI, KpnI, SacI, EcoRV, SmaI
])

analysis = Analysis(common_enzymes, seq)
results = analysis.full()

Access Enzymes by Name

from Bio.Restriction import AllEnzymes

# Get enzyme by string name
ecori = AllEnzymes.get('EcoRI')
sites = ecori.search(seq)

# Check if enzyme exists
if 'EcoRI' in AllEnzymes:
    print('EcoRI is in database')

Search Multiple Sequences

from Bio import SeqIO
from Bio.Restriction import RestrictionBatch, EcoRI, BamHI

batch = RestrictionBatch([EcoRI, BamHI])

for record in SeqIO.parse('sequences.fasta', 'fasta'):
    analysis = Analysis(batch, record.seq)
    results = analysis.full()
    print(f'{record.id}:')
    for enzyme, sites in results.items():
        if sites:
            print(f'  {enzyme}: {sites}')

Notes

  • Positions are 1-based - first base is position 1
  • Cut position - where enzyme cuts (between bases)
  • Linear default - set linear=False for circular DNA
  • Case insensitive - recognition matches regardless of case
  • Ambiguous bases - some enzymes recognize N, R, Y, etc.

Related Skills

  • restriction-mapping - Visualize cut positions on sequence
  • enzyme-selection - Choose enzymes by criteria
  • fragment-analysis - Analyze resulting fragments
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 3 files

5.9 KB alongside SKILL.md, 2 of them executable

examples/

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.