<jupyter_start><jupyter_text>Python for Bioinformatics-----------------------------![title](https://s3.amazonaws.com/py4bio/tapabiosmall.png)This Jupyter notebook is intented to be used alongside the book [Python for Bioinformatics](http://py3.us/) Chapter 23: DNA Mutations with Restrictions-------------     **Note:** The code in this chapter needs Biopython 1.69. It was not included in the first print of the book because this Biopython version was not available. The full source code in the [GitHub repository](https://github.com/Serulab/Py4Bio). This version is adapted to work in Jupyter Notebook.<jupyter_code>!pip install biopython
'''Given a DNA sequence of a polypeptide, this program
generates alternative DNA sequences that code for the same
polypeptide but that can be sorted out by DNA restriction.
Requires Biopython >= 1.69
Author: <NAME> (<EMAIL>)'''

from Bio import Seq
from Bio.Alphabet import IUPAC
from Bio import Restriction
from Bio.Data import CodonTable
from jinja2 import Template

TABLE_ID = 1
ALLOWED_MUTATIONS = 2

mutation_tpl = """Original Sequence: {{dna_input}}
Peptide: {{ori_pep}}

Restriction map for original sequence:

{{ori_map}}

=========================
{% for item in bakpeps_out %}

Original sequence enzymes: {{oname}}

{{item.graph}}

Proposed sequence enzymes: {{item.pames}}
Enzimes only in original sequence: {{item.o}}
Enzimes only in proposed sequence: {{item.p}}
=========================
{% endfor %}"""

def backtrans(ori_pep, table_id=1):
    """
    Function to make backtranslation (from peptide to DNA)
    This function needs the peptide sequence and the code of
    translation table. Code number is the same as posted in:
    http://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi
    """
    def recurs(order, pos):
        for letter in bt[order[pos]]:
            if pos == len(order) - 1:
                yield letter
                continue
            for prox in recurs(order, pos+1):
                yield (letter + prox)

    def combine(order):
        ordened = set()
        for frase in recurs(order, 0):
            ordened.add(frase)
        return ordened

    t = CodonTable.generic_by_id[table_id]
    bt = dict()
    for a1 in "ATCG" :
        for a2 in "ATCG" :
            for a3 in "ATCG" :
                codon = a1 + a2 + a3
                try:
                    amino = t.forward_table[codon]
                except KeyError:
                    assert codon in t.stop_codons
                    continue
                try:
                    bt[amino].append(codon)
                except KeyError:
                    bt[amino] = [codon]
    return list(combine(ori_pep))

def seqcomp(s1, s2):
    """
    Compares 2 sequences and returns a value with
    how many differents elements they have.
    """
    p = len(s1)
    for x,y in zip(s1, s2): # Walk through 2 sequences.
        if x==y:
            p -= 1
    return p

input_dna = input('Enter DNA sequennce: ').upper()
dna = Seq.Seq(input_dna, IUPAC.unambiguous_dna)
# Translate DNA sequence.
ori_pep = dna.translate()
# Get all backtranslations.
bakpeps = backtrans(ori_pep, TABLE_ID)
# Make a restriction analysis for the orignal sequence.
analysis = Restriction.Analysis(Restriction.CommOnly, dna)
analysis.print_as('map')
ori_map = analysis.format_output()
# Store the enzymes that cut in the original sequence.
enz = list(analysis.with_sites().keys())
# Get a string out of the enzyme list, for printing.
oname = str(enz)[1:-1]
enz = set(enz)
bakpeps_out = []
for bakpep in bakpeps:
    tmp_d = {}
    if bakpep not in input_dna:
        # Make a restriction analysis for each sequence.
        analysis = Restriction.Analysis(Restriction.CommOnly,
                Seq.Seq(bakpep, IUPAC.unambiguous_dna))
        # Store the enzymes that cut in this sequence.
        enz_tmp = list(analysis.with_sites().keys())
        enz_tmp = set(enz_tmp)
        # Get the number of mutations in backpep sequence.
        y = seqcomp(input_dna, bakpep)
        if enz_tmp != enz and enz and y <= ALLOWED_MUTATIONS:
            analysis.print_as('map')
            tmp_d['pames'] = str(enz_tmp)[1:-1]
            tmp_d['graph'] = analysis.format_output()
            tmp_d['ori_seq'] = str(list(enz.difference(
                                        enz_tmp)))[1:-1]
            tmp_d['proposed_seq'] = str(list(
                        enz_tmp.difference(enz)))[1:-1]
            bakpeps_out.append(tmp_d)
template = Template(mutation_tpl)
render = template.render(dna_input=input_dna,
                         ori_pep=ori_pep,
                         ori_map=ori_map,
                         oname=oname,
                         bakpeps_out=bakpeps_out)
print(render)<jupyter_output>Enter DNA sequennce: atacgctgtcatgca
Original Sequence: ATACGCTGTCATGCA
Peptide: IRCHA

Restriction map for original sequence:

   4 AbaSI
   |                                                        
   |     10 FatI
   |     |                                                  
   |     |11 CviAII
   |     ||                                                 
   |     ||12 FaiI
   |     |||                                                
   |     ||| 14 Hin1II NlaIII FaeI HpyCH4V Hsp92II
   |     ||| |                                              
ATACGCTGTCATGCA
|||||||||||||||
TATGCGACAGTACGT
1                           15


   Enzymes which do not cut the sequence.

FspEI     AccII     AciI      AfaI      AluBI     AluI      AoxI      AspLEI    
BfaI      BfuCI     Bsh1236I  BshFI     BsiSI     BsnI      Bsp143I   BspACI    
BspANI    BspFNI    BssMI     BstFNI    BstHHI    BstKTI    BstMBI    BstUI     
BsuRI     CfoI      Csp6I     CviJI     CviKI_1   CviQI     DpnI      DpnII     
F[...]
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