def main():
dlgs = glob('*.dlg')
if len(dlgs) == 0:
sys.exit(1)
if os.path.exists('target') is False:
os.mkdir('target')
ligands = []
receptors = []
for filename in dlgs:
dlg=filename[:-4]
(lig, rec) = dlg.split('--____--')
if not lig in ligands:
ligands.append(lig)
if not rec in receptors:
receptors.append(rec)
res = [[] for i in ligands]
for i in range(len(res)):
res[i] = ['' for j in receptors]
for filename in dlgs:
dlg=filename[:-4]
(lig, rec) = dlg.split('--____--')
d = Docking()
d.readDlg(filename)
lines = d.ligMol.parser.allLines
for i in range(len(lines)):
line = lines[i]
if line.find("\n") == -1:
d.ligMol.parser.allLines[i] = line + "\n"
if not hasattr(d, 'clusterer'):
d.clusterer = Clusterer(d.ch.conformations, sort="binding_energy")
clist = [d.clusterer.data[int(i)] for i in d.clusterer.argsort]
energy = clist[0].binding_energy
res[ligands.index(lig)][receptors.index(rec)] = "%.2f" % energy
d.ligMol.parser.allLines = d.ligMol.parser.write_with_new_coords(clist[0].getCoords())
write_pdb(d.ligMol.parser.parse(), 'target/%s.pdb' % dlg)
res_file = open('target/result.txt', 'w')
print>>res_file, ",%s" % ",".join(receptors)
for i in range(len(res)):
print>>res_file, "%s,%s" % (ligands[i], ",".join(res[i]))
res_file.close()
def parse_dlg(dlgfilename, num, result):
global VERBOSE
d = Docking()
d.readDlg(dlgfilename)
if num > 1:
workdir = outdir + '/' + d.ligMol.name
if os.path.exists(workdir) is False:
os.mkdir(workdir)
if num == 1:
workdir = outdir
if num > 1:
log = {'name': d.ligMol.name, 'num': num, 'target': workdir}
if VERBOSE:
print log
#print>>result, log
lines = d.ligMol.parser.allLines
for i in range(len(lines)):
line = lines[i]
if line.find("\n") == -1:
d.ligMol.parser.allLines[i] = line + "\n"
if not hasattr(d, 'clusterer'):
d.clusterer = Clusterer(d.ch.conformations, sort='binding_energy')
clist = []
for i in d.clusterer.argsort:
clist.append(d.clusterer.data[int(i)])
energy_list = []
for i in range(0, num):
conf = clist[i]
outfile = workdir + '/' + d.ligMol.name + '_' + str(i + 1) + '.pdb'
energy = conf.binding_energy
energy_list.append("%.2f" % energy)
mylog = {'name': outfile, 'energy': energy}
if VERBOSE:
print mylog
d.ligMol.parser.allLines = d.ligMol.parser.write_with_new_coords(
conf.getCoords())
write_pdb(d.ligMol.parser.parse(), outfile)
print >> result, "%s,%s" % (d.ligMol.name, ','.join(energy_list))
verbose = True
if verbose: print 'set verbose to ', True
if o in ('-h', '--'):
usage()
sys.exit()
#read all the docking logs in current directory, one by one
dlg_list = glob.glob('./*.dlg')
dockings = []
#build a list of all atom types in all dlgs
#it is assumed that all the dockings used the same grids
ctr = 0
at_types = {}
for dlg in dlg_list:
d = Docking()
d.readDlg(dlg)
ctr += 1
print ctr, ": read ", dlg
dockings.append(d)
for a in d.ligMol.allAtoms:
at_types[a.autodock_element] = 0
if debug: print 'at_types=', at_types.keys()
d = dockings[0] #get grid info from the first docking
xcen, ycen, zcen = d.dlo_list[0].parser.center_pt
#for the output maps...
# nxgrid=nygrid=nzgrid=npts ??is this required??
nxpts = nypts = nzpts = int(num_pts) / 2 * 2 + 1 #ensure an odd integer
npts = (nxpts, nypts, nzpts)
macroStem = d.dlo_list[0].macroStem
# build list of all atom types
all_types = at_types.keys()
dlg_file = a
if verbose: print 'set dlg_file to ', a
if o in ('-t', '--t'):
rms_tolerance = float(a)
if verbose: print 'set rms_tolerance to ', a
if o in ('-v', '--v'):
verbose = True
if verbose: print 'set verbose to ', True
if o in ('-h', '--'):
usage()
sys.exit()
dlg_list = glob.glob(dlg_file)
d = Docking()
for dlg in dlg_list:
d.readDlg(dlg)
d.clusterer.rmsTool = RMSDCalculator(d.ligMol.allAtoms.coords[:])
d.clusterer.make_clustering(rms_tolerance)
clustering = d.clusterer.clustering_dict[rms_tolerance]
largest = clustering[0]
for clust in clustering:
if len(clust)>len(largest):
largest = clust
#update the coordinates with those of conf with lowest energy in this largest cluster
d.ch.set_conformation(largest[0])
parser = d.ligMol.parser
lines = []
#have to add newline character to lines read from dlg
for l in parser.allLines:
l+= '\n'
lines.append(l)
#sample line to use:
#ZINC00057384_x1hpv/ZINC00057384_x1hpv, 20, 4, 10, -9.0900....
#skip the header line
if line.find('lowestEnergy') > -1:
#lowestEnergy dlgfn #runs #cl #LEC LE rmsd largestCl_dlgfn ...
continue
#write line from summary_filename
ostr = "REMARK %s" % line
optr.write(ostr)
#find the docking log filename
ll = line.split()
fn = ll[0].strip()[:-1]
dlgFN = path_to_dockings + "/" + fn + ".dlg"
#create a docking
d = Docking()
d.readDlg(dlgFN)
#set ligand to lowest energy conformation LE
cluD = d.clusterer.clustering_dict
rms_tol = list(cluD.keys())[0]
LE = cluD[rms_tol][0][0]
d.ch.set_conformation(LE)
#get coordinates of LE conformation
crds = d.ligMol.allAtoms.coords[:]
#use the parser to get newlines to output
lines_to_print = d.ligMol.parser.write_with_new_coords(crds)
#edit these lines, adding new line + changing the RES field to current count
for nl in lines_to_print:
if nl[-1] != "\n":
nl += "\n"
if atom_records_only:
if nl.find("ATOM") != 0 and nl.find("HETA") != 0:
if outputfilename == 'summary_of_results':
outputfilename = outputfilename + '_' + str(rms_tolerance)
if build_hydrogen_bonds is True and receptor_filename is None:
print 'to build hydrogen bonds, receptor filename must be specified'
sys.exit()
if report_energy_breakdown is True and receptor_filename is None:
print 'to report energy breakdown, receptor filename must be specified'
sys.exit()
if not docking_logfile:
print 'summarize_docking: docking_logfile must be specified.'
usage()
sys.exit()
#read the docking log
d = Docking()
d.readDlg(docking_logfile)
if receptor_filename is not None:
receptor_filename = receptor_filename
#setup rmsd tool
coords = d.ligMol.allAtoms.coords[:]
refCoords = None
if rms_reference is not None:
file = rms_reference
ref = Read(file)
if not len(ref):
print "unable to read ", rms_reference
else:
ref = ref[0]
coords = ref.allAtoms.coords
refCoords = coords[:]
d.clusterer.rmsTool = RMSDCalculator(coords)
include_best_docking_info)
if o in ('-h', '--'):
usage()
sys.exit()
if not dlgfilename:
print('write_lowest_energy_ligand: dlgfilename must be specified.')
usage()
sys.exit()
#what about nucleic acids???
rms_tolerance = 5.0
d = Docking()
if not multiple:
d.readDlg(dlgfilename)
else:
fl = glob.glob("*.dlg")
for n in fl:
d.readDlg(n)
if verbose: print('read ', dlgfilename)
if multiple:
coords = d.ligMol.allAtoms.coords[:]
d.clusterer.rmsTool = RMSDCalculator(coords)
d.clusterer.make_clustering(rms_tolerance)
key0 = list(d.clusterer.clustering_dict.keys())[0]
conf0 = d.clusterer.clustering_dict[key0][0][0]
#figure out its dlg filename
for dlo in d.dlo_list:
if conf0 in dlo.conformations:
conf0_filename = dlo.parser.filename
if not directory:
msg = 'Both reference directory and directory must be specified!\n'
elif not directory:
msg += 'directory must be specified!'
if not refdirectory or not directory:
print(msg)
usage()
sys.exit()
#process docking in reference directory
#read all the docking logs in reference directory as one Docking
ref_dlg_list = glob.glob(refdirectory + '/*.dlg')
ref_d = Docking()
for dlg in ref_dlg_list:
ref_d.readDlg(dlg)
#setup rmsd tool
coords = ref_d.ligMol.allAtoms.coords[:]
ref_d.clusterer.rmsTool = RMSDCalculator(coords)
ref_d.clusterer.make_clustering(rms_tolerance)
clust0 = ref_d.clusterer.clustering_dict[rms_tolerance][0]
c = clust0[0] #lowest energy overall in reference docking
ref_d.ch.set_conformation(c)
ref_LE_coords = ref_d.ligMol.allAtoms.coords[:]
ref_largest = clust0
for clust in ref_d.clusterer.clustering_dict[rms_tolerance]:
if verbose: print("current largest cluster len= ", len(clust))
if len(clust) > len(ref_largest):
if verbose: print("resetting largest clust: now len=", len(clust))
ref_largest = clust
ref_d.ch.set_conformation(ref_largest[0])
if o in ('-h', '--'):
usage()
sys.exit()
if not docking_filename:
print 'write_all_complexes: docking_filename must be specified.'
usage()
sys.exit()
if not receptor_filename:
print 'write_all_complexes: receptor_filename must be specified.'
usage()
sys.exit()
d = Docking()
d.readDlg(docking_filename)
receptor_stem = os.path.splitext(os.path.basename(receptor_filename))[0]
print "receptor_stem =", receptor_stem
rptr = open(receptor_filename)
receptor_lines = rptr.readlines()
rptr.close()
if write_best_only:
if not hasattr(d, 'clusterer'):
print docking_filename, ' has no clustering... unable to write complex of best result'
sys.exit()
rms = d.clusterer.clustering_dict.keys()[0]
confs = [d.clusterer.clustering_dict[rms][0][0]]
else:
confs = d.ch.conformations
usage()
sys.exit()
if not docking_filename:
print 'write_all_complexes: docking_filename must be specified.'
usage()
sys.exit()
if not receptor_filename:
print 'write_all_complexes: receptor_filename must be specified.'
usage()
sys.exit()
d = Docking()
d.readDlg(docking_filename)
receptor_stem = os.path.splitext(os.path.basename(receptor_filename))[0]
print "receptor_stem =", receptor_stem
rptr = open(receptor_filename)
receptor_lines = rptr.readlines()
rptr.close()
if write_best_only:
if not hasattr(d, 'clusterer'):
print docking_filename, ' has no clustering... unable to write complex of best result'
sys.exit()
rms = d.clusterer.clustering_dict.keys()[0]
confs = [d.clusterer.clustering_dict[rms][0][0]]
else:
confs = d.ch.conformations
if not refdirectory:
print 'compute_rms_between_methods: refdirectory must be specified.'
usage()
sys.exit()
if not directory:
print 'compute_rms_between_methods: directory must be specified.'
usage()
sys.exit()
#process docking in reference directory
#read all the docking logs in reference directory as one Docking
ref_dlg_list = glob.glob(refdirectory + '/*.dlg')
ref_d = Docking()
for dlg in ref_dlg_list:
ref_d.readDlg(dlg)
#setup rmsd tool
coords = ref_d.ligMol.allAtoms.coords[:]
ref_d.clusterer.rmsTool = RMSDCalculator(coords)
ref_d.clusterer.make_clustering(rms_tolerance)
clust0 = ref_d.clusterer.clustering_dict[rms_tolerance][0]
c = clust0[0] #lowest energy overall in reference docking
ref_d.ch.set_conformation(c)
ref_LE_coords = ref_d.ligMol.allAtoms.coords[:]
ref_largest = clust0
for clust in ref_d.clusterer.clustering_dict[rms_tolerance]:
if verbose: print "current largest cluster len= ", len(clust)
if len(clust)>len(ref_largest):
if verbose: print "resetting largest clust: now len=", len(clust)
ref_largest = clust
ref_d.ch.set_conformation(ref_largest[0])
if outputfilename=='summary_of_results':
outputfilename = outputfilename + '_' + str(rms_tolerance)
if build_hydrogen_bonds is True and receptor_filename is None:
print 'to build hydrogen bonds, receptor filename must be specified'
sys.exit()
if report_energy_breakdown is True and receptor_filename is None:
print 'to report energy breakdown, receptor filename must be specified'
sys.exit()
if not docking_logfile:
print 'summarize_docking: docking_logfile must be specified.'
usage()
sys.exit()
#read the docking log
d = Docking()
d.readDlg(docking_logfile)
if receptor_filename is not None:
receptor_filename = receptor_filename
#setup rmsd tool
coords = d.ligMol.allAtoms.coords[:]
refCoords = None
if rms_reference is not None:
file = rms_reference
ref = Read(file)
if not len(ref):
print "unable to read ", rms_reference
else:
ref = ref[0]
coords = ref.allAtoms.coords
refCoords = coords[:]
d.clusterer.rmsTool = RMSDCalculator(coords)
outputfilename = a
if verbose: print 'set outputfilename to ', a
if o in ('-h', '--'):
usage()
sys.exit()
if not dlgfilename:
print 'write_lowest_energy_ligand: dlgfilename must be specified.'
usage()
sys.exit()
#what about nucleic acids???
d = Docking()
d.readDlg(dlgfilename)
if verbose: print 'read ', dlgfilename
key0 = d.clusterer.clustering_dict.keys()[0]
conf0 = d.clusterer.clustering_dict[key0][0][0]
d.ch.set_conformation(conf0)
parser = d.ligMol.parser
lines = []
#have to add newline character to lines read from dlg
for l in parser.allLines:
l+= '\n'
lines.append(l)
parser.allLines = lines
coords = d.ligMol.allAtoms.coords
if outputfilename is None:
outputfilename = d.ligMol.name + '_BE.pdbqt'
usage()
sys.exit()
if not dlg_filename:
print(
'compute_interatomic_distance_per_pose: autodock dlg filename must be specified: eg: "ind.dlg"'
)
usage()
sys.exit()
if outputfilename is None:
outputfilename = "rec_dockedLIG_" + dlg_filename + "_dists.txt"
#process docking in reference directory
d = Docking()
d.readDlg(dlg_filename)
lig = d.ligMol
#determine the receptor molecule to read in
rec_file = ratom_name.split(":")[0] + ".pdbqt"
msg = rec_file + " not found"
assert os.path.exists(rec_file), msg
recs = Read(rec_file)
rec = recs[0]
# locate the receptor atom
css = CompoundStringSelector()
rec_ats = css.select(recs, ratom_name)[0]
msg = ratom_name + " did not match exactly 1 atom in " + rec_file
assert len(rec_ats) == 1, msg
rec_at = rec_ats[0]
rec_at_coords = rec_at.coords
if verbose:
#sample line to use:
#ZINC00057384_x1hpv/ZINC00057384_x1hpv, 20, 4, 10, -9.0900....
#skip the header line
if line.find('lowestEnergy')>-1:
#lowestEnergy dlgfn #runs #cl #LEC LE rmsd largestCl_dlgfn ...
continue
#write line from summary_filename
ostr = "REMARK %s"%line
optr.write(ostr)
#find the docking log filename
ll = line.split()
fn = ll[0].strip()[:-1]
dlgFN = path_to_dockings + "/" + fn +".dlg"
#create a docking
d = Docking()
d.readDlg(dlgFN)
#set ligand to lowest energy conformation LE
cluD = d.clusterer.clustering_dict
rms_tol = cluD.keys()[0]
LE = cluD[rms_tol][0][0]
d.ch.set_conformation(LE)
#get coordinates of LE conformation
crds = d.ligMol.allAtoms.coords[:]
#use the parser to get newlines to output
lines_to_print = d.ligMol.parser.write_with_new_coords(crds)
#edit these lines, adding new line + changing the RES field to current count
for nl in lines_to_print:
if nl[-1]!="\n":
nl += "\n"
if atom_records_only:
if nl.find("ATOM")!=0 and nl.find("HETA")!=0: