def InitWalls(pdbid: str) -> TunnelWalls:
"""Initiate walls for a particular structure. This consumes a dataframe given that a choice of tunnel is present"""
def get_tunnels_dataframe(csvpath: str) -> pd.DataFrame:
tunnel_instance = pd.read_csv(csvpath)
xyzr = tunnel_instance[['Distance', 'FreeRadius', 'X', 'Y', 'Z']]
return xyzr
TUNNELS = os.getenv("TUNNELS")
log = Log(os.getenv('TUNNEL_LOG'))
struct = log.get_struct(pdbid)
taxid = str(int(struct['taxid'].values[0]))
choice = int(struct['moletunnel'].values[0])
tunnelfile = "tunnel_{}.csv".format(choice)
if choice < 1:
"""See docs for disambiguation. Either mole hasn't succeeded or there is something blockign the tunnel."""
print("Choice under 1.")
return
tunnelcsv = get_tunnels_dataframe(
os.path.join(TUNNELS, taxid, pdbid, 'csv', tunnelfile))
tw = TunnelWalls(pdbid, fetchStructure(pdbid), tunnelcsv)
tw.consumeMoleDataframe(10)
return tw
def added_ptcs():
for struct in _300852:
x = residues_average( get_ptc_residues(fetchStructure(struct),struct,[ 2055 , 2056 , 2451 , 2452 , 2507 , 2506 ]) )
if len(x)>0:
cord = list( map(lambda x: str(x), x) )
cord = ",".join(cord)
log.update_struct(struct,dowrite=True,**{"PTC_average":str(cord)})
else:continue
def calc_constriction_site(pdbid: str):
"""Here the assumption is that the constriction site is unique and so is then the KDTree min then."""
pdbid = pdbid.upper()
chainL22: str = log.get_struct(pdbid)['uL22'].values[0]
chainL4: str = log.get_struct(pdbid)['uL4'].values[0]
if ',' in chainL22: chainL22 = chainL22.split(',')[0]
if ',' in chainL4: chainL4 = chainL4.split(',')[0]
struct = fetchStructure(pdbid)[0]
L4: Chain = struct[chainL4]
L22: Chain = struct[chainL22]
l4res = [*L4.get_atoms()]
l22res = [*L22.get_atoms()]
kdtreeonl4 = KDTree([*map(lambda x: x.get_coord(), l4res)])
kdtreeonl22 = KDTree([*map(lambda x: x.get_coord(), l22res)])
nbridin22: Atom = None
nbridin4: Atom = None
atom: Atom
distances_indexes = kdtreeonl4.query(
[*map(lambda x: x.get_coord(), l22res)])
dist = 99999999
for x in zip([*distances_indexes[0]], [*distances_indexes[1]]):
if x[0] < dist:
dist = x[0]
nbridin4 = x[1]
distances_indexes = kdtreeonl22.query(
[*map(lambda x: x.get_coord(), l4res)])
dist = 99999999
for x in zip([*distances_indexes[0]], [*distances_indexes[1]]):
if x[0] < dist:
dist = x[0]
nbridin22 = x[1]
l4atomcord = l4res[nbridin4].get_coord()
l22atomcord = l22res[nbridin22].get_coord()
centerline = np.mean([l4atomcord, l22atomcord], axis=0)
residueInL4: Residue = l4res[nbridin4].get_parent()
residueInL22: Residue = l22res[nbridin22].get_parent()
print(
"""{} {} in chain {}({}) is closest to {} {} in chain{}({}).\n Centerline:{}"""
.format(residueInL22.get_resname(),
residueInL22.get_id()[1], chainL22, 'uL22',
residueInL4.get_resname(),
residueInL4.get_id()[1], chainL4, 'uL4', centerline))
return {"uL22": residueInL22, "uL4": residueInL4, "centerline": centerline}
def added_ptcs():
for struct in _9606:
x = get_ptc_residues(fetchStructure(struct), struct, ['4452'])
if len(x) > 0:
cord = list(map(lambda x: str(x), get_CA_or(x[0]).get_coord()))
cord = ",".join(cord)
log.update_struct(struct,
dowrite=True,
**{"PTC_average": str(cord)})
else:
continue
from ciftools.Structure import fetchStructure
from ciftools.scripts.splitStruct import fetchChain
from typing import List
from Bio.PDB.Residue import Residue
from pymol import cmd
from ciftools.TunnelScripts.TunnelLog import Log
RADIUS = os.getenv('SCOOP_RADIUS')
TUNNELS = os.getenv('TUNNELS')
STATIC_ROOT = os.getenv('STATIC_ROOT')
pdbid = sys.argv[1].upper()
log = Log(os.getenv('TUNNEL_LOG'))
struct = fetchStructure(pdbid)
record = log.get_struct(pdbid)
species = str( int( record.taxid.values[0] ) )
structpath = os.path.join(STATIC_ROOT,pdbid,"{}.cif".format(pdbid))
scoopsavepath = os.path.join(TUNNELS,species,pdbid,'{}_{}Ascoop.pdb'.format(pdbid,RADIUS))
if not os.path.exists(os.path.dirname( scoopsavepath )):
os.makedirs(os.path.dirname( scoopsavepath ))
cmd.load(structpath)
x = cmd.select(f'resi 2504')
cmd.select(f'br. {pdbid} w. {RADIUS} of \'sele\'')
cmd.save( scoopsavepath, 'sele' )
print("Saved to {}".format(scoopsavepath))
def fetchChain(pdbid: str, strandid: str) -> Chain:
pdbid = pdbid.upper()
struct = fetchStructure(pdbid)
chain: Chain = struct[0][strandid]
return chain