print smarts
pat = Smarts.compile(smarts)
assert pat.match(m)
smiles = []
file = open("F:\\Chemical Libraries\\Libraries to Purchase\\Nat_425.sdf")
reader = MDL.mdlin(file)
mol = reader.next()
print "reading natural products"
i = 0
while mol:
fp = Fingerprint.generateFingerprint(mol)
smile = mol.cansmiles()
mol = removeTerminalAtoms(mol)
smiles.append(
(len(mol.atoms), len(mol.bonds), smile, mol.arbsmarts(), i, fp))
i += 1
mol = reader.next()
search = smiles
search.sort()
smiles = []
print "processing"
dict = {}
from bsddb3 import dbshelve
from frowns import Smiles, Smarts, Fingerprint
# ################################################################
# load database (this only needs to be done once
# you can comment this out at a later data
# ################################################################
# this is a persistent disk cache
cache = dbshelve.open("FOO.shelve")
molecules = ["CCCN", "c1ccccc1CCN", "C#C(N)CCc1ccccc1CCc1ccccc1"]
for m in molecules:
mol = Smiles.smilin(m)
fp = Fingerprint.generateFingerprint(mol)
# cache the fingerprint using the canonical smiles
# as the key and the fingerprint object as the value
# shelves can store any picklable object!
cache[mol.cansmiles()] = fp
cache.close()
# ##################################################################
# Iterate through database to see which molecules we need to
# do a full substructure search on
# ##################################################################
cache = dbshelve.open("FOO.shelve", 'r')
query = "CCCN" # this should reject molecule #2 above
testFP = Fingerprint.generateFingerprint(Smiles.smilin(query))
from bsddb3 import dbshelve
from frowns import Smiles, Smarts, Fingerprint
# ################################################################
# load database (this only needs to be done once
# you can comment this out at a later data
# ################################################################
# this is a persistent disk cache
cache = dbshelve.open("FOO.shelve")
molecules = ["CCCN", "c1ccccc1CCN", "C#C(N)CCc1ccccc1CCc1ccccc1"]
for m in molecules:
mol = Smiles.smilin(m)
fp = Fingerprint.generateFingerprint(mol)
# cache the fingerprint using the canonical smiles
# as the key and the fingerprint object as the value
# shelves can store any picklable object!
cache[mol.cansmiles()] = fp
cache.close()
# ##################################################################
# Iterate through database to see which molecules we need to
# do a full substructure search on
# ##################################################################
cache = dbshelve.open("FOO.shelve", 'r')
query = "CCCN" # this should reject molecule #2 above
testFP = Fingerprint.generateFingerprint(Smiles.smilin(query))
print smarts
pat = Smarts.compile(smarts)
assert pat.match(m)
smiles = []
file = open("F:\\Chemical Libraries\\Libraries to Purchase\\Nat_425.sdf")
reader = MDL.mdlin(file)
mol = reader.next()
print "reading natural products"
i = 0
while mol:
fp = Fingerprint.generateFingerprint(mol)
smile = mol.cansmiles()
mol = removeTerminalAtoms(mol)
smiles.append((len(mol.atoms), len(mol.bonds), smile, mol.arbsmarts(), i, fp))
i += 1
mol = reader.next()
search = smiles
search.sort()
smiles = []
print "processing"
dict = {}
