def clusterWaters(self): #pose, clust_tolerance=2.0, desolvEntropy=0):
# cluster waters
# XXX
# energy from the cluster?
# once 3 waters are reclustered (3->1)
# two desolvEntropy penalties should be issued?
# XXX
unclustered_waters = self.pose[
'water_bridge'][:] # XXX NOT SURE IT"S NECESSARY
# cluster waters
water_clusters = hf.clusterAtoms(unclustered_waters,
tol=self.clust_tol)
# calculate clustering energy
self.pose['water_cluster_penalty'] = []
remove_from_text = []
for pop in water_clusters:
if len(pop) > 1:
this_cluster_centroid = hf.avgCoord(pop)
this_cluster_penalty = -self.desolvEntropy * (len(pop) - 1)
this_cluster_energy = 0
this_cluster_contacts = []
closest_to_centroid = None
closest_dist = 999999
for w in pop:
# get the w_index + w_score
idx = self.pose['water_bridge'].index(w)
this_cluster_energy += self.pose['water_bridge_scores'][
idx]
remove_from_text.append(w)
# find water closest to centroid (to be conserved)
# get the distance from the cluster average
centr_dist = hf.quickdist(hf.atomCoord(w),
this_cluster_centroid,
sq=False)
a = [hf.makePdb(coord=this_cluster_centroid)]
#writeList('centroid.pdb', a)
if centr_dist <= closest_dist:
closest_dist = centr_dist
closest_to_centroid = w
del self.pose['water_bridge'][idx]
del self.pose['water_bridge_scores'][idx]
# update contacts
for a in self.pose['water_bridge_contacts'][idx]:
if not a in this_cluster_contacts:
this_cluster_contacts.append(a)
del self.pose['water_bridge_contacts'][idx]
# update PDBQT text
# XXX DEBUGGINGH
#print type(remove_from_text), remove_from_text[0]
#writeList('REMOVING_WATERS.pdb', remove_from_text)
#writeList('current_ligand.pdbqt', pose['text'])
for w in remove_from_text:
if not w == closest_to_centroid:
try:
text_idx = self.pose['text'].index(w)
del self.pose['text'][text_idx]
except:
pass
# use the closest to be updated with clustering coords
closest_index = self.pose['text'].index(closest_to_centroid)
water = self.pose['text'][closest_index]
coord_text = "%8.3f%8.3f%8.3f" % (this_cluster_centroid[0],
this_cluster_centroid[1],
this_cluster_centroid[2])
cluster_water = water[0:30] + coord_text + water[
54:] # XXX ugly, but it works...
self.pose['text'][closest_index] = cluster_water
# update water_bridge list+score, water_cluster_penalty list
self.pose['water_bridge'].append(cluster_water)
self.pose['water_bridge_scores'].append(this_cluster_energy)
self.pose['water_cluster_penalty'].append(this_cluster_penalty)
self.pose['water_bridge_contacts'].append(
this_cluster_contacts)
if self.debug:
print "CLUSTER SIZE", len(pop)
print "CLUSTER ENRG", this_cluster_energy
print "CLUSTER PENL", this_cluster_penalty
#print "CLUSTER FINL", clust_energy+clust_penalty
print "=============="
def findStacking(set1, set2 = None):
"""
INPUT(set1, set2): scan the sets to find p- and t-stackings
INPUT(set1): scan the set to find self-stackings (p-, t-)
P-STACKING
---c---
|
A V
|
---c---
"""
DEBUG = 0
MAXDIST_TSTACK = 5.0 # centroids distance (T-stacking)Angstroms
MAXDIST_PSTACK = 4.2 # centroids distance (P-stacking) Angstroms
MAXDIST_PSTACK = MAXDIST_PSTACK**2
MAXDIST_TSTACK = MAXDIST_TSTACK**2
#MAXDIST = 5.0 # Angstroms
#MAXDIST = MAXDIST**2
PTOL = 29.9 # P-stacking plane angle tolerance (degr) TODO test values on a wide set!
TTOL = 14.9 # T-stacking plane angle tolerance (degr) TODO test values on a wide set!
PLANE_DIST_TSTACK = 2.5
t_accepted = []
p_accepted = []
if not set2:
set2 = set1
for g1 in set1.keys():
R1 = set1[g1]
for g2 in set2.keys():
if not g1 == g2: # this is for intramolecular stackings (set1 = set2)
R2 = set2[g2]
if not ([g1,g2] in p_accepted) and not ([g2,g1] in p_accepted):
if (not [g1,g2] in t_accepted) and not ([g2,g1] in t_accepted):
d = hf.quickdist(R1['centroid'], R2['centroid'])
if d <= MAXDIST_TSTACK:
#print "GOOD DIST: %2.3f" % sqrt(d),
pdist = abs(hf.dot( R1['normal'][0], (R1['centroid']-R2['centroid']) ))
pangle = abs(hf.vecAngle( R1['plane'], R2['plane']))
#print "DISTANCE: %2.2f <"% math.sqrt(d), math.sqrt(MAXDIST_TSTACK)
#print "PTOL", PTOL
#print "PDIST:", pdist
#print "PANGLE:", pangle
#print "======"
#print "PANGLE-180", pangle-180
#print abs(pangle-180)<=PTOL or (pangle-PTOL)<=0
#print "PAANGLE-180 < PTOL", abs(pangle-180)<=PTOL
#print "PANGLE-PTOL", pangle-PTOL
#print "PANGLE-PTOL < 0", (pangle-PTOL)<=0
#print "\n\n"
if d <= MAXDIST_PSTACK and ((abs(pangle-180)<=PTOL) or ((pangle-PTOL)<=0)):
p_accepted.append([ g1, g2])
if DEBUG:
print " ==> P-stacking",
print "%s--%s plane angle: %2.1f | pdist: %2.2f\n\n" % (g1, g2, pangle, pdist),
elif (( abs(pangle-90) <= TTOL) or ( abs(pangle-270)<=TTOL) ) and pdist < PLANE_DIST_TSTACK:
t_accepted.append([ g1, g2])
print "XXX"
if DEBUG:
print "== > T-stacking",
print "%s--%s plane angle: %2.1f " % (g1, g2, pangle),
if ( abs(pangle-90) <= TTOL):
print "ANGLE:",abs(pangle-90), "<", TTOL
if ( abs(pangle-270)<=TTOL):
print "ANGLE:", abs(pangle-270), "<", TTOL
print "PLANE:",pdist, "<", PLANE_DIST_TSTACK
return p_accepted, t_accepted
def clusterWaters(self): #pose, clust_tolerance=2.0, desolvEntropy=0):
# cluster waters
# XXX
# energy from the cluster?
# once 3 waters are reclustered (3->1)
# two desolvEntropy penalties should be issued?
# XXX
unclustered_waters = self.pose['water_bridge'][:] # XXX NOT SURE IT"S NECESSARY
# cluster waters
water_clusters = hf.clusterAtoms(unclustered_waters, tol=self.clust_tol)
# calculate clustering energy
self.pose['water_cluster_penalty'] = []
remove_from_text = []
for pop in water_clusters:
if len(pop)>1:
this_cluster_centroid = hf.avgCoord(pop)
this_cluster_penalty = -self.desolvEntropy * (len(pop)-1)
this_cluster_energy = 0
this_cluster_contacts = []
closest_to_centroid = None
closest_dist = 999999
for w in pop:
# get the w_index + w_score
idx = self.pose['water_bridge'].index(w)
this_cluster_energy += self.pose['water_bridge_scores'][idx]
remove_from_text.append(w)
# find water closest to centroid (to be conserved)
# get the distance from the cluster average
centr_dist = hf.quickdist( hf.atomCoord(w), this_cluster_centroid, sq = False)
a = [ hf.makePdb(coord=this_cluster_centroid) ]
#writeList('centroid.pdb', a)
if centr_dist <= closest_dist:
closest_dist = centr_dist
closest_to_centroid = w
del self.pose['water_bridge'][idx]
del self.pose['water_bridge_scores'][idx]
# update contacts
for a in self.pose['water_bridge_contacts'][idx]:
if not a in this_cluster_contacts:
this_cluster_contacts.append(a)
del self.pose['water_bridge_contacts'][idx]
# update PDBQT text
# XXX DEBUGGINGH
#print type(remove_from_text), remove_from_text[0]
#writeList('REMOVING_WATERS.pdb', remove_from_text)
#writeList('current_ligand.pdbqt', pose['text'])
for w in remove_from_text:
if not w == closest_to_centroid:
try:
text_idx = self.pose['text'].index(w)
del self.pose['text'][text_idx]
except:
pass
# use the closest to be updated with clustering coords
closest_index = self.pose['text'].index(closest_to_centroid)
water = self.pose['text'][closest_index]
coord_text = "%8.3f%8.3f%8.3f" % (this_cluster_centroid[0],
this_cluster_centroid[1],
this_cluster_centroid[2])
cluster_water = water[0:30]+coord_text+water[54:] # XXX ugly, but it works...
self.pose['text'][closest_index] = cluster_water
# update water_bridge list+score, water_cluster_penalty list
self.pose['water_bridge'].append(cluster_water)
self.pose['water_bridge_scores'].append(this_cluster_energy)
self.pose['water_cluster_penalty'].append(this_cluster_penalty)
self.pose['water_bridge_contacts'].append(this_cluster_contacts)
if self.debug:
print "CLUSTER SIZE", len(pop)
print "CLUSTER ENRG", this_cluster_energy
print "CLUSTER PENL", this_cluster_penalty
#print "CLUSTER FINL", clust_energy+clust_penalty
print "=============="
