experimental_sequence_aln = experimental_sequence_aln[
0:len(uniprot_sequence)]
experimental_sequence_aln_conflicts = experimental_sequence_aln_conflicts[
0:len(uniprot_sequence)]
#print ''.join(experimental_sequence_aln_conflicts)
# Now add the various sequence data to kinDB
experimental_sequence_aln = ''.join(experimental_sequence_aln)
experimental_sequence_aln_conflicts = ''.join(
experimental_sequence_aln_conflicts)
#print k, pdbid, chainid, len(experimental_sequence), len(observed_sequence)
#print k, pdbid, chainid, experimental_sequence_aln
exp = etree.SubElement(chain_node, 'experimental')
etree.SubElement(
exp, 'sequence').text = '\n' + seqwrap(experimental_sequence)
exp.set('length', str(len(experimental_sequence)))
etree.SubElement(exp, 'sequence_aln'
).text = '\n' + seqwrap(experimental_sequence_aln)
etree.SubElement(
exp, 'sequence_aln_conflicts'
).text = '\n' + seqwrap(experimental_sequence_aln_conflicts)
obs = etree.SubElement(chain_node, 'observed')
etree.SubElement(
obs, 'sequence').text = '\n' + seqwrap(observed_sequence)
#if pdbid == '2W1C':
#if pdbid == '3LAU':
#if pdbid == '1O6L':
if pdbid == '3O50':
#sys.exit()
pk_description = x.get('description')
pk_begin = int( x.find('./location/begin').attrib['position'] )
pk_end = int( x.find('./location/end').attrib['position'] )
pk_length = pk_end - pk_begin + 1
#PK_domain = deepcopy(x)
PK_domain = etree.Element('pk_domain')
PK_domain.set('description', pk_description)
PK_domain.set('begin', str(pk_begin))
PK_domain.set('end', str(pk_end))
PK_domain.set('length', str(pk_length))
PK_domain.set('id', str(x_iter))
PK_domain.set('kinDB_id', (entry_name + '_' + AC + '_PK' + str(x_iter)))
#location = PK_domain.find('./location')
#etree.SubElement(location, 'length').text = str(pk_length)
domain_sequence = seqwrap(sequence[pk_begin-1:pk_end])
etree.SubElement(PK_domain, 'sequence').text = '\n' + domain_sequence
kinase_uniprot.append(PK_domain)
# = References to other DBs =
# NCBI Gene
GeneIDs = [x.get('id') for x in uniprot_kinases[k].findall('./dbReference[@type="GeneID"]')]
# XXX: exceptions for kinases which have no GeneIDs annotated; LMTK3 RefSeq status is PROVISIONAL; RIPK4 presumably RefSeq sequence is not an exact match; SIK3 RefSeq status is VALIDATED
# Will add these manually, since we are mainly using GeneID to collect publications currently
if entry_name == 'LMTK3_HUMAN':
GeneIDs = ['114783']
if entry_name == 'RIPK4_HUMAN':
GeneIDs = ['54101']
if entry_name == 'SIK3_HUMAN':
GeneIDs = ['23387']
if len(GeneIDs) > 0:
# =================================
# Output templates.fa and templates-resnums.txt
# =================================
templates_filtered = templates.xpath('template[not(@DELETE_ME="")]')
with open(templates_fa_filename, 'w') as templates_fa_file:
with open(templates_resnums_filename, 'w') as templates_resnums_file:
for t in range(ntemplates_filtered):
template = templates_filtered[t]
template_id = template.get('template_id')
chainid = template.get('pk_chainid_pdb')
sequence = template.get('pk_domain_observed_resnames')
resnums = template.get('pk_domain_observed_uniprot_resnums')
template_header = '>' + template_id + '\n'
template_fa_string = template_header + seqwrap(sequence)
template_resnums_string = template_header + resnums + '\n'
templates_fa_file.write(template_fa_string)
templates_resnums_file.write(template_resnums_string)
# =================================
# Some stats
# =================================
template_ACs = [x.get('uniprotAC') for x in templates_filtered]
nkinases_with_pk_pdb = len(set(template_ACs))
print 'Total number of pdb chains:', npdb_chains
print '(Number of templates created before filtering: ' + str(ntemplates) + ')'
print 'Total number of templates created:', ntemplates_filtered
print 'Number of kinases with at least one template:', nkinases_with_pk_pdb
for pk_domain in pk_domains:
target_id = pk_domain.get('kinDB_id')
pk_domain_sequence = sequnwrap(pk_domain.findtext('sequence'))
len_pk_domain = int(pk_domain.get('length'))
# XXX XXX XXX IMPORTANT: overriding Abl1 sequence so that it includes all of helix I (up to residue 513). Eventually will come up with a better automated method for determining domain boundaries
if target_id == 'ABL1_HUMAN_P00519_PK0':
pk_domain_sequence = sequnwrap(pk_domain.getparent().findtext('sequence'))[241:513]
len_pk_domain = len(pk_domain_sequence)
# Set target name.
target_ids.append(target_id)
# Write alignment file entry.
contents += ">%s\n" % target_id
contents += seqwrap(pk_domain_sequence)
if verbose:
print "%24s : %s" % (target_id, pk_domain_sequence)
# Mutants
mutants = kinDB[k].findall('mutants/mutant')
for mutant in mutants:
# XXX Skipping these for now - don't have a stable system for assigning IDs yet
continue
mut_pk_domain_id = mutant.get('pk_domain_id')
mutated_full_sequence = list( sequnwrap( kuniprot.find('sequence').text ) )
pk_domain_begin = int( kuniprot.find('pk_domain[@id="%s"]' % mut_pk_domain_id).get('begin') )
pk_domain_end = int( kuniprot.find('pk_domain[@id="%s"]' % mut_pk_domain_id).get('end') )
# XXX IMPORTANT: override Abl1 sequence
if target_id == 'ABL1_HUMAN_P00519_PK0':
if __name__ == '__main__':
krange = range(nkinases)
pool = Pool()
results = pool.map(gather_pdb, krange)
#results = map(gather_pdb, krange) # serial version, for debugging
for k in krange:
pdb_nodes = kinDB[k].findall('pk_pdb')
for p in range(len(pdb_nodes)):
chain_nodes = pdb_nodes[p].findall('chain')
for c in range(len(chain_nodes)):
DELETE_ME = results[k][p][c][6]
if DELETE_ME:
chain_nodes[c].set('DELETE_ME','')
exp = etree.SubElement(chain_nodes[c], 'experimental')
etree.SubElement(exp, 'sequence').text = '\n' + seqwrap(results[k][p][c][0])
exp.set('length', str(len(results[k][p][c][0])))
#etree.SubElement(exp, 'sequence_aln').text = '\n' + seqwrap(results[k][p][c][1]) # NOTE: this is no longer added to the database
etree.SubElement(exp, 'sequence_aln_conflicts').text = '\n' + seqwrap(results[k][p][c][2])
obs = etree.SubElement(chain_nodes[c], 'observed')
etree.SubElement(obs, 'sequence_aln_exp').text = '\n' + seqwrap(results[k][p][c][3])
etree.SubElement(obs, 'sequence_aln').text = '\n' + seqwrap(results[k][p][c][4])
etree.SubElement(obs, 'ss_aln').text = '\n' + seqwrap(results[k][p][c][5])
# Expression data
expression_data = results[k][p][-1]
if verbose: print expression_data
expression_data_node = etree.Element('expression_data')
for e in expression_data.keys():
expression_data_node.set(e, expression_data[e])
pdb_nodes[p].insert(0, expression_data_node)
target_id = pk_domain.get('kinDB_id')
pk_domain_sequence = sequnwrap(pk_domain.findtext('sequence'))
len_pk_domain = int(pk_domain.get('length'))
# XXX XXX XXX IMPORTANT: overriding Abl1 sequence so that it includes all of helix I (up to residue 513). Eventually will come up with a better automated method for determining domain boundaries
if target_id == 'ABL1_HUMAN_P00519_PK0':
pk_domain_sequence = sequnwrap(
pk_domain.getparent().findtext('sequence'))[241:513]
len_pk_domain = len(pk_domain_sequence)
# Set target name.
target_ids.append(target_id)
# Write alignment file entry.
contents += ">%s\n" % target_id
contents += seqwrap(pk_domain_sequence)
if verbose:
print "%24s : %s" % (target_id, pk_domain_sequence)
# Mutants
mutants = kinDB[k].findall('mutants/mutant')
for mutant in mutants:
# XXX Skipping these for now - don't have a stable system for assigning IDs yet
continue
mut_pk_domain_id = mutant.get('pk_domain_id')
mutated_full_sequence = list(
sequnwrap(kuniprot.find('sequence').text))
pk_domain_begin = int(
kuniprot.find('pk_domain[@id="%s"]' %
mut_pk_domain_id).get('begin'))
i += 1
# In cases such as 3LAU and 1O6L, additional sequence at end makes experimental_sequence_aln longer than uniprot_sequence by 1
if len(experimental_sequence_aln) != len(uniprot_sequence):
experimental_sequence_aln = experimental_sequence_aln[0 : len(uniprot_sequence)]
experimental_sequence_aln_conflicts = experimental_sequence_aln_conflicts[0 : len(uniprot_sequence)]
# print ''.join(experimental_sequence_aln_conflicts)
# Now add the various sequence data to kinDB
experimental_sequence_aln = "".join(experimental_sequence_aln)
experimental_sequence_aln_conflicts = "".join(experimental_sequence_aln_conflicts)
# print k, pdbid, chainid, len(experimental_sequence), len(observed_sequence)
# print k, pdbid, chainid, experimental_sequence_aln
exp = etree.SubElement(chain_node, "experimental")
etree.SubElement(exp, "sequence").text = "\n" + seqwrap(experimental_sequence)
exp.set("length", str(len(experimental_sequence)))
etree.SubElement(exp, "sequence_aln").text = "\n" + seqwrap(experimental_sequence_aln)
etree.SubElement(exp, "sequence_aln_conflicts").text = "\n" + seqwrap(experimental_sequence_aln_conflicts)
obs = etree.SubElement(chain_node, "observed")
etree.SubElement(obs, "sequence").text = "\n" + seqwrap(observed_sequence)
# if pdbid == '2W1C':
# if pdbid == '3LAU':
# if pdbid == '1O6L':
if pdbid == "3O50":
# sys.exit()
pass
# Only add if the chain matches that in the kinDB
# =================================
# Output templates.fa and templates-resnums.txt
# =================================
templates_filtered = templates.xpath('template[not(@DELETE_ME="")]')
with open(templates_fa_filename, 'w') as templates_fa_file:
with open(templates_resnums_filename, 'w') as templates_resnums_file:
for t in range(ntemplates_filtered):
template = templates_filtered[t]
template_id = template.get('template_id')
chainid = template.get('pk_chainid_pdb')
sequence = template.get('pk_domain_observed_resnames')
resnums = template.get('pk_domain_observed_uniprot_resnums')
template_header = '>' + template_id + '\n'
template_fa_string = template_header + seqwrap(sequence)
template_resnums_string = template_header + resnums + '\n'
templates_fa_file.write(template_fa_string)
templates_resnums_file.write(template_resnums_string)
# =================================
# Some stats
# =================================
template_ACs = [ x.get('uniprotAC') for x in templates_filtered ]
nkinases_with_pk_pdb = len(set(template_ACs ))
print 'Total number of pdb chains:', npdb_chains
print '(Number of templates created before filtering: ' + str(ntemplates) + ')'
print 'Total number of templates created:', ntemplates_filtered
print 'Number of kinases with at least one template:', nkinases_with_pk_pdb
