/
prokaryote_schema.py
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/
prokaryote_schema.py
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""" Schema to represent a knowledge base to build models of prokaryotes
:Author: Balazs Szigeti <balazs.szigeti@mssm.edu>
:Author: Jonathan Karr <jonrkarr@gmail.com>
:Author: Bilal Shaikh <bilal.shaikh@columbia.edu>
:Author: Arthur Goldberg <Arthur.Goldberg@mssm.edu>
:Author: Yin Hoon Chew <yinhoon.chew@mssm.edu>
:Date: 2018-09-10
:Copyright: 2018, Karr Lab
:License: MIT
"""
from wc_utils.util import chem
import obj_model
from wc_kb import core
#####################
#####################
# Species types
class RnaSpeciesType(core.PolymerSpeciesType):
""" Knowledge of an RNA species
Attributes:
transcription_units (:obj:`list` of :obj:`TranscriptionUnitLocus`): transcription units
type (:obj:`RnaType`): type
Related attributes:
proteins (:obj:`list` of :obj:`ProteinSpeciesType`): protein(s)
"""
transcription_units = obj_model.ManyToManyAttribute(
'TranscriptionUnitLocus', related_name='rna')
type = obj_model.EnumAttribute(core.RnaType)
class Meta(obj_model.Model.Meta):
attribute_order = ('id', 'name', 'type', 'transcription_units', 'circular',
'double_stranded', 'half_life', 'comments', 'references', 'database_references')
def get_seq(self):
""" Get the sequence
Returns:
:obj:`Bio.Seq.Seq`: sequence
"""
tu_start = self.transcription_units[0].start
tu_end = self.transcription_units[0].end
dna_seq = self.transcription_units[0].polymer.get_subseq(
start=tu_start, end=tu_end)
return dna_seq.transcribe()
def get_empirical_formula(self):
""" Get the empirical formula for an RNA transcript with
* 5' monophosphate
* Deprotonated phosphate oxygens
:math:`N_A * AMP + N_C * CMP + N_G * GMP + N_U * UMP - (L-1) * OH`
Returns:
:obj:`chem.EmpiricalFormula`: empirical formula
"""
seq = self.get_seq()
n_a = seq.count('A')
n_c = seq.count('C')
n_g = seq.count('G')
n_u = seq.count('U')
l = len(seq)
formula = chem.EmpiricalFormula()
formula.C = 10 * n_a + 9 * n_c + 10 * n_g + 9 * n_u
formula.H = 12 * n_a + 12 * n_c + 12 * n_g + 11 * n_u - (l - 1)
formula.N = 5 * n_a + 3 * n_c + 5 * n_g + 2 * n_u
formula.O = 7 * n_a + 8 * n_c + 8 * n_g + 9 * n_u - (l - 1)
formula.P = n_a + n_c + n_g + n_u
return formula
def get_charge(self):
""" Get the charge for a transcript with
* 5' monophosphate
* Deprotonated phosphate oxygens
:math:`-L - 1`
Returns:
:obj:`int`: charge
"""
return -self.get_len() - 1
def get_mol_wt(self):
""" Get the molecular weight for a transcript with
* 5' monophosphate
* Deprotonated phosphate oxygens
Returns:
:obj:`float`: molecular weight (Da)
"""
return self.get_empirical_formula().get_molecular_weight()
class ProteinSpeciesType(core.PolymerSpeciesType):
""" Knowledge of a protein monomer
Attributes:
gene (:obj:`GeneLocus`): gene
rna (:obj:`RnaSpeciesType`): rna
"""
gene = obj_model.ManyToOneAttribute('GeneLocus', related_name='proteins')
rna = obj_model.ManyToOneAttribute(
'RnaSpeciesType', related_name='proteins')
class Meta(obj_model.Model.Meta):
attribute_order = ('id', 'name', 'gene', 'rna', 'circular', 'double_stranded',
'half_life', 'comments', 'references', 'database_references')
def get_seq(self, cds=True):
""" Get the sequence
Returns:
:obj:`Bio.Seq.Seq`: sequence
"""
table = self.cell.knowledge_base.translation_table
seq = self.gene.get_seq().translate(table=table, cds=cds)
return seq
def get_empirical_formula(self, cds=True):
""" Get the empirical formula
Returns:
:obj:`chem.EmpiricalFormula`: empirical formula
"""
seq = self.get_seq(cds=cds)
l = len(seq)
n_a = seq.count('A') # Ala: Alanine (C3 H7 N O2)
n_r = seq.count('R') # Arg: Arginine (C6 H14 N4 O2)
n_n = seq.count('N') # Asn: Asparagine (C4 H8 N2 O3)
n_d = seq.count('D') # Asp: Aspartic acid (C4 H7 N O4)
n_c = seq.count('C') # Cys: Cysteine (C3 H7 N O2 S)
n_q = seq.count('Q') # Gln: Glutamine (C5 H10 N2 O3)
n_e = seq.count('E') # Glu: Glutamic acid (C5 H9 N O4)
n_g = seq.count('G') # Gly: Glycine (C2 H5 N O2)
n_h = seq.count('H') # His: Histidine (C6 H9 N3 O2)
n_i = seq.count('I') # Ile: Isoleucine (C6 H13 N O2)
n_l = seq.count('L') # Leu: Leucine (C6 H13 N O2)
n_k = seq.count('K') # Lys: Lysine (C6 H14 N2 O2)
n_m = seq.count('M') # Met: Methionine (C5 H11 N O2 S)
n_f = seq.count('F') # Phe: Phenylalanine (C9 H11 N O2)
n_p = seq.count('P') # Pro: Proline (C5 H9 N O2)
n_s = seq.count('S') # Ser: Serine (C3 H7 N O3)
n_t = seq.count('T') # Thr: Threonine (C4 H9 N O3)
n_w = seq.count('W') # Trp: Tryptophan (C11 H12 N2 O2)
n_y = seq.count('Y') # Tyr: Tyrosine (C9 H11 N O3)
n_v = seq.count('V') # Val: Valine (C5 H11 N O2)
formula = chem.EmpiricalFormula()
formula.C = 3 * n_a + 6 * n_r + 4 * n_n + 4 * n_d + 3 * n_c + \
5 * n_q + 5 * n_e + 2 * n_g + 6 * n_h + 6 * n_i + \
6 * n_l + 6 * n_k + 5 * n_m + 9 * n_f + 5 * n_p + \
3 * n_s + 4 * n_t + 11 * n_w + 9 * n_y + 5 * n_v
formula.H = 7 * n_a + 14 * n_r + 8 * n_n + 7 * n_d + 7 * n_c + \
10 * n_q + 9 * n_e + 5 * n_g + 9 * n_h + 13 * n_i + \
13 * n_l + 14 * n_k + 11 * n_m + 11 * n_f + 9 * n_p + \
7 * n_s + 9 * n_t + 12 * n_w + 11 * n_y + 11 * n_v - 2 * (l - 1)
formula.N = 1 * n_a + 4 * n_r + 2 * n_n + 1 * n_d + 1 * n_c + \
2 * n_q + 1 * n_e + 1 * n_g + 3 * n_h + 1 * n_i + \
1 * n_l + 2 * n_k + 1 * n_m + 1 * n_f + 1 * n_p + \
1 * n_s + 1 * n_t + 2 * n_w + 1 * n_y + 1 * n_v
formula.O = 2 * n_a + 2 * n_r + 3 * n_n + 4 * n_d + 2 * n_c + \
3 * n_q + 4 * n_e + 2 * n_g + 2 * n_h + 2 * n_i + \
2 * n_l + 2 * n_k + 2 * n_m + 2 * n_f + 2 * n_p + \
3 * n_s + 3 * n_t + 2 * n_w + 3 * n_y + 2 * n_v - (l - 1)
formula.S = n_c + n_m
return formula
def get_charge(self, cds=True):
""" Get the charge at physiological pH
Returns:
:obj:`int`: charge
"""
seq = self.get_seq(cds=cds)
n_r = seq.count('R')
n_h = seq.count('H')
n_k = seq.count('K')
n_d = seq.count('D')
n_e = seq.count('E')
return (n_r + n_h + n_k) - (n_d + n_e)
def get_mol_wt(self, cds=True):
""" Get the molecular weight
Returns:
:obj:`float`: molecular weight
"""
return self.get_empirical_formula(cds=cds).get_molecular_weight()
#####################
#####################
# Locus types
class PromoterLocus(core.PolymerLocus):
""" Knowledge of a promoter for a transcription unit
Attributes:
pribnow_start (:obj:`int`): Pribnow box start coordinate
pribnow_end (:obj:`int`): Pribnow box end coordinate
up_35_start (:obj:`int`): -35 promoter start coordinate
up_35_end (:obj:`int`): -35 promoter end coordinate
Related attributes:
transcription_units (:obj:`list` of :obj:`TranscriptionUnitLocus`)
"""
pribnow_start = obj_model.IntegerAttribute()
pribnow_end = obj_model.IntegerAttribute()
up_35_start = obj_model.IntegerAttribute()
up_35_end = obj_model.IntegerAttribute()
class Meta(obj_model.Model.Meta):
attribute_order = ('id', 'polymer', 'name', 'pribnow_start', 'pribnow_end',
'strand', 'start', 'end', 'comments', 'references', 'database_references')
class TranscriptionUnitLocus(core.PolymerLocus):
""" Knowledge about an open reading frame
Attributes:
promoter (:obj:`PromoterLocus`): promoter controlling the TU
genes (:obj:`list` of :obj:`GeneLocus`): genes
"""
promoter = obj_model.ManyToOneAttribute(
'PromoterLocus', related_name='transcription_units')
genes = obj_model.ManyToManyAttribute(
'GeneLocus', related_name='transcription_units')
class Meta(obj_model.Model.Meta):
attribute_order = ('id', 'polymer', 'name', 'strand', 'promoter', 'start', 'end',
'genes', 'comments', 'references', 'database_references')
def get_3_prime(self):
""" Get the 3' coordinate
Returns:
:obj:`int`: 3' coordinate
"""
if self.strand == core.PolymerStrand.positive:
return self.end
else:
return self.start
def get_5_prime(self):
""" Get the 5' coordinate
Returns:
:obj:`int`: 5' coordinate
"""
if self.strand == core.PolymerStrand.positive:
return self.start
else:
return self.end
class GeneLocus(core.PolymerLocus):
""" Knowledge of a gene
Attributes:
symbol (:obj:`str`): symbol
Related attributes:
proteins (:obj:`list` of :obj:`ProteinSpeciesType`): protein
"""
symbol = obj_model.StringAttribute()
type = obj_model.EnumAttribute(core.GeneType)
class Meta(obj_model.Model.Meta):
attribute_order = ('id', 'polymer', 'name', 'symbol', 'type', 'strand', 'start',
'end', 'comments', 'references', 'database_references')