Delegate independent tasks to specialized agents working concurrently with isolated context.
Enzyme Selection
bio-restriction-enzyme-selection
Select restriction enzymes by criteria using Biopython Bio.Restriction. Find enzymes that cut once, don't cut, produce specific overhangs, are commercially available, or have compatible ends for cloning. Use when selecting restriction enzymes for cloning or analysis.
SKILL.md
Full skill instructions
Enzyme Selection
Find Enzymes by Cut Frequency
from Bio import SeqIO
from Bio.Restriction import Analysis, CommOnly, AllEnzymes
record = SeqIO.read('sequence.fasta', 'fasta')
seq = record.seq
analysis = Analysis(CommOnly, seq)
# Enzymes that cut exactly once (good for linearization)
once_cutters = analysis.once_cutters()
# Enzymes that cut exactly twice (good for excision)
twice_cutters = analysis.twice_cutters()
# Enzymes that don't cut (good for cloning insert)
non_cutters = analysis.only_dont_cut()
# All enzymes that cut (any number of times)
all_cutters = analysis.only_cut()
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
More Other skills
brand-guidelines
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
theme-factory
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
internal-comms
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Fundamental design principles for writing maintainable, testable Python code.
responsive-design
Modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first strategies.
Generate Playwright tests from scenarios using interactive browser exploration and validation.
Automated website exploration and test case generation using Playwright.
Modern React state management with Redux Toolkit, Zustand, Jotai, and React Query for every state category.
gdpr-data-handling
GDPR-compliant data handling with consent management, data subject rights, and privacy controls.
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
refactor-plan
Detailed multi-file refactor planning with safety checks and rollback guidance.
