Bio Restriction Enzyme Selection

Find Non-Cutters for Insert

from Bio.Restriction import Analysis, CommOnly

# Find enzymes that don't cut your insert
insert_seq = record.seq
analysis = Analysis(CommOnly, insert_seq)

non_cutters = analysis.only_dont_cut()
print('Enzymes that do not cut the insert:')
for enzyme in non_cutters:
    print(f'  {enzyme}')

Find Compatible Enzyme Pairs

from Bio.Restriction import EcoRI, BamHI, BglII, XhoI, SalI

# Check if enzymes produce compatible overhangs
def find_compatible_enzymes(enzyme):
    '''Find enzymes with same overhang'''
    compatible = enzyme.compatible_end()
    print(f'{enzyme} is compatible with: {compatible}')

find_compatible_enzymes(BamHI)  # Compatible with BglII
find_compatible_enzymes(XhoI)   # Compatible with SalI

Filter by Overhang Type

from Bio.Restriction import CommOnly, Analysis

analysis = Analysis(CommOnly, seq)
cutters = analysis.only_cut()

# Filter by overhang type
blunt_cutters = [e for e in cutters if e.is_blunt()]
five_prime = [e for e in cutters if e.is_5overhang()]
three_prime = [e for e in cutters if e.is_3overhang()]

print(f'Blunt cutters: {len(blunt_cutters)}')
print(f'5\' overhang: {len(five_prime)}')
print(f'3\' overhang: {len(three_prime)}')

Filter by Recognition Site Length

from Bio.Restriction import AllEnzymes, CommOnly

# 6-cutters (most common for cloning)
six_cutters = [e for e in CommOnly if len(e.site) == 6]

# 8-cutters (rare cutters, good for large constructs)
eight_cutters = [e for e in CommOnly if len(e.site) == 8]

# 4-cutters (frequent cutters)
four_cutters = [e for e in CommOnly if len(e.site) == 4]

print(f'4-cutters: {len(four_cutters)}')
print(f'6-cutters: {len(six_cutters)}')
print(f'8-cutters: {len(eight_cutters)}')

Find Enzymes with Specific Overhang

from Bio.Restriction import CommOnly

def find_by_overhang(overhang_seq):
    '''Find enzymes that produce a specific overhang'''
    matching = []
    for enzyme in CommOnly:
        if hasattr(enzyme, 'ovhgseq') and enzyme.ovhgseq == overhang_seq:
            matching.append(enzyme)
    return matching

# Find enzymes with AATT overhang (like EcoRI)
aatt_enzymes = find_by_overhang('AATT')
print(f'Enzymes with AATT overhang: {aatt_enzymes}')

Find Unique Cutters in Multiple Sequences

from Bio import SeqIO
from Bio.Restriction import Analysis, CommOnly

records = list(SeqIO.parse('sequences.fasta', 'fasta'))

# Find enzymes that cut once in each sequence
common_once_cutters = None

for record in records:
    analysis = Analysis(CommOnly, record.seq)
    once = set(analysis.once_cutters().keys())

    if common_once_cutters is None:
        common_once_cutters = once
    else:
        common_once_cutters &= once

print('Enzymes that cut once in all sequences:')
for enzyme in common_once_cutters:
    print(f'  {enzyme}')

Select Enzymes for Directional Cloning

from Bio.Restriction import Analysis, CommOnly

def find_cloning_pairs(vector_seq, insert_seq):
    '''Find enzyme pairs for directional cloning'''

    # Analyze both sequences
    vec_analysis = Analysis(CommOnly, vector_seq)
    ins_analysis = Analysis(CommOnly, insert_seq)

    # Enzymes that cut vector once
    vec_once = set(vec_analysis.once_cutters().keys())

    # Enzymes that don't cut insert
    ins_non = set(ins_analysis.only_dont_cut())

    # Candidates: cut vector once, don't cut insert
    candidates = vec_once & ins_non

    # Group by overhang type for pairs
    five_prime = [e for e in candidates if e.is_5overhang()]
    three_prime = [e for e in candidates if e.is_3overhang()]
    blunt = [e for e in candidates if e.is_blunt()]

    print(f'Candidate enzymes: {len(candidates)}')
    print(f"  5' overhang: {[str(e) for e in five_prime[:5]]}")
    print(f"  3' overhang: {[str(e) for e in three_prime[:5]]}")
    print(f"  Blunt: {[str(e) for e in blunt[:5]]}")

    return candidates

# Usage
# candidates = find_cloning_pairs(vector_seq, insert_seq)

Check Commercial Availability

from Bio.Restriction import CommOnly, AllEnzymes, EcoRI

# Check if enzyme is commercially available
def is_commercial(enzyme):
    return enzyme in CommOnly

print(f'EcoRI commercial: {is_commercial(EcoRI)}')

# List all commercial enzymes
print(f'Total commercial enzymes: {len(CommOnly)}')

Find Isoschizomers

from Bio.Restriction import EcoRI, HpaII

# Isoschizomers: same recognition, may have different cuts
isoschizomers = EcoRI.isoschizomers()
print(f'EcoRI isoschizomers: {isoschizomers}')

# Neoschizomers: same recognition, different cut position
neoschizomers = HpaII.neoschizomers()
print(f'HpaII neoschizomers: {neoschizomers}')

Check Methylation Sensitivity

Some enzymes are blocked by DNA methylation (Dam, Dcm in E. coli). Important when digesting genomic DNA from bacteria.

from Bio.Restriction import DpnI, DpnII, Sau3AI, MboI

# Check if enzyme is sensitive to methylation
def check_methylation(enzyme):
    dam = enzyme.is_dam_methylable()
    dcm = enzyme.is_dcm_methylable()
    print(f'{enzyme}: Dam={dam}, Dcm={dcm}')

check_methylation(DpnI)   # Requires Dam methylation to cut
check_methylation(DpnII)  # Blocked by Dam methylation
check_methylation(Sau3AI) # Not affected by Dam
check_methylation(MboI)   # Blocked by Dam methylation

from Bio.Restriction import CommOnly, Analysis

# Find enzymes not affected by common methylation
def find_methylation_insensitive(seq):
    analysis = Analysis(CommOnly, seq)
    cutters = analysis.only_cut()

    insensitive = [e for e in cutters
                   if not e.is_dam_methylable() and not e.is_dcm_methylable()]

    print(f'Methylation-insensitive cutters: {len(insensitive)}')
    return insensitive

# Usage for genomic DNA from E. coli
# insensitive = find_methylation_insensitive(seq)

Type IIS Enzymes for Golden Gate Cloning

Type IIS enzymes cut outside their recognition site, enabling scarless assembly.

from Bio.Restriction import BsaI, BbsI, BsmBI, SapI

# Type IIS enzymes cut outside recognition sequence
# BsaI: GGTCTC(N)1 - cuts 1bp after recognition
# BsmBI: CGTCTC(N)1

def type_iis_info(enzyme):
    print(f'{enzyme}:')
    print(f'  Recognition: {enzyme.site}')
    print(f'  Overhang: {enzyme.ovhg} bp ({enzyme.ovhgseq if enzyme.ovhgseq else "variable"})')
    print(f'  Cuts outside: {enzyme.fst3cut}, {enzyme.fst5cut}')

type_iis_info(BsaI)
type_iis_info(BsmBI)

from Bio.Restriction import BsaI, BsmBI
from Bio.Seq import Seq

# Golden Gate assembly: design parts with compatible overhangs
# BsaI creates 4-bp overhangs that can be designed for specific fusion

def find_golden_gate_sites(seq, enzyme=BsaI):
    '''Find Type IIS sites and their overhang positions'''
    sites = enzyme.search(seq)

    if not sites:
        print(f'No {enzyme} sites found - sequence is Golden Gate compatible')
        return []

    print(f'{enzyme} sites found at: {sites}')
    print('These sites must be removed for Golden Gate cloning')
    return sites

# Check if insert is free of BsaI sites
insert_seq = Seq('ATGCGATCGATCGATCG')
find_golden_gate_sites(insert_seq, BsaI)

# Common Type IIS enzymes for Golden Gate/modular cloning
from Bio.Restriction import BsaI, BsmBI, BbsI, SapI, BtgZI

golden_gate_enzymes = [BsaI, BsmBI, BbsI, SapI, BtgZI]

for enzyme in golden_gate_enzymes:
    print(f'{enzyme}: site={enzyme.site}, overhang={enzyme.ovhg}bp')

Enzyme Properties Reference

from Bio.Restriction import EcoRI

# Get all properties
print(f'Site: {EcoRI.site}')
print(f'Cut: {EcoRI.fst3cut}, {EcoRI.fst5cut}')
print(f'Overhang: {EcoRI.ovhg} ({EcoRI.ovhgseq})')
print(f'Blunt: {EcoRI.is_blunt()}')
print(f'5\' overhang: {EcoRI.is_5overhang()}')
print(f'3\' overhang: {EcoRI.is_3overhang()}')
print(f'Ambiguous: {EcoRI.is_ambiguous()}')
print(f'Defined: {EcoRI.is_defined()}')

Related Skills

• restriction-sites - Find where selected enzymes cut
• restriction-mapping - Map selected enzyme sites
• fragment-analysis - Predict fragments from selected enzymes