def getSurface( model, key ):
if verbose:
log.write("Calculating SurfaceRacer data for %s..."%key)
d = PDBDope( model )
d.addSurfaceRacer( probe=1.4 )
if verbose:
log.writeln('Done.')
result['%s_AS'%key] = model.profile('AS')
result['%s_MS'%key] = model.profile('MS')
result['%s_relAS'%key] = model.profile('relAS')
result['%s_relMS'%key] = model.profile('relMS')
## Load Trajectories - read and sort bound ligand and recepror trajectories
traj_rec_ref = Trajectory([ref_rec_file])
traj_lig_ref = Trajectory([ref_lig_file])
traj_rec, traj_rec_ref = castTraj(traj_rec, traj_rec_ref)
traj_lig, traj_lig_ref = castTraj(traj_lig, traj_lig_ref)
refCom = ProteinComplex(traj_rec_ref.ref, traj_lig_ref.ref)
traj_rec = traj_rec_ref.concat(traj_rec)
traj_lig = traj_lig_ref.concat(traj_lig)
## Add surface atom profile
flushPrint('Adding accessible surface profiles...\n')
rec_asa = PDBDope(traj_rec.getRef())
rec_asa.addASA()
lig_asa = PDBDope(traj_lig.getRef())
lig_asa.addASA()
## Atom sets to use for analysis
## Sets are(only heavy atoms):
masks_all, mask_all_names = allMasks(traj_rec, traj_lig, refCom)
## Masks restricted to surface atoms
masks_surf, mask_surf_names = surfMasks(traj_rec, traj_lig, refCom)
## pairwise rmsd calculation
rmsd_all_dic = calcAllRmsds(traj_rec, traj_lig, masks_all)
rmsd_surf_dic = calcAllRmsds(traj_rec, traj_lig, masks_surf)
def main(options):
##################
## files and names
receptorName = absfile(options['r'])
receptorCode = stripFilename(receptorName)[0:4]
ligandName = absfile(options['l'])
ligandCode = stripFilename(ligandName)[0:4]
complexName = absfile(options['c'])
rm = options['rm']
lm = options['lm']
if rm or lm:
rn = rm or '1'
ln = lm or '1'
baseName = receptorCode + '_' + rn + '-' + ligandCode + '_' + ln
else:
baseName = receptorCode + '-' + ligandCode
## hex macro name
macName = baseName + '_hex.mac'
## hex rotation matrix output name
outName_all = baseName + '_hex.out'
outName_clust = baseName + '_hex_cluster.out'
## load model dictionaries, if they exist in the same directory
## as the corresponding pdb-file and start with the same pdb-code
## and ends with '_model.dic'
try:
rec_dic = stripFilename(options['r'])[:4] + '_model.dic'
rec_path = options['r'][:options['r'].rfind('/')]
lig_dic = stripFilename(options['l'])[:4] + '_model.dic'
lig_path = options['l'][:options['l'].rfind('/')]
rec = load( absfile(rec_path + '/' + rec_dic) )
lig = load( absfile(lig_path + '/' + lig_dic) )
print 'Loading dictionaries'
if type(rec) is dict:
rec = rec[1]
if type(lig) is dict:
lig = lig[1]
## could not load dictionaty, will load pdb-file insted
except:
print 'Loading pdb files'
rec = PDBModel(receptorName)
lig = PDBModel(ligandName)
#############################
## get structural information
## add surface profiles if not there
if not rec.atoms.has_key('relASA'):
flushPrint('\nCalculating receptor surface profile')
rec_asa = PDBDope( rec )
rec_asa.addASA()
if not lig.atoms.has_key('relASA'):
flushPrint('\nCalculating ligand surface profile')
lig_asa = PDBDope( lig )
lig_asa.addASA()
## surface masks, > 95% exposed
rec_surf_mask = greater( rec.profile('relASA'), 95 )
lig_surf_mask = greater( lig.profile('relASA'), 95 )
## maximun and medisn distance from centre of mass to any surface atom
recMax, recMin = centerSurfDist( rec, rec_surf_mask )
ligMax, ligMin = centerSurfDist( lig, lig_surf_mask )
## approxinate max and min center to centre distance
maxDist = recMax + ligMax
minDist = recMin + ligMin
print '\n\nReceptor and ligand max radius are %i and %i A, respectively.'\
%( recMax, ligMax )
print 'Receptor and ligand min radius are %i and %i A, respectively.'\
%( recMin, ligMin )
## molecular separation and search range to be used in the docking
molSep = ( maxDist + minDist ) / 2
molRange = 2 * ( maxDist - molSep )
print 'A molecular separation of %i A and a search range of +-%i will be used.'\
%( molSep, molRange )
## determine docking mode to use
macroDocking = 0
if recMax > 30 and ligMax > 30:
print '\nWARNING! Both the receptor and ligand radius is greater than 30 A.\n'
if recMax > 30:
print '\nReceptor has a radius that exceeds 30 A -> Macro docking will be used'
macroDocking = 1
#####################
## write macro file
macOpen= open(macName, 'w')
macOpen.write('# ------------------- ' + macName + ' -----------------------\n')
macOpen.write(' \n')
macOpen.write('open_receptor '+receptorName+'\n')
macOpen.write('open_ligand '+ligandName+'\n')
if complexName[-4:] == '.pdb':
macOpen.write('open_complex '+complexName+'\n')
macOpen.write('\n')
head = """
# -------------- general settings ----------------
disc_cache 1 # disc cache on (0 off)
docking_sort_mode 1 # Sort solutions by cluster (0 by energy)
docking_cluster_mode 1 # Display all clusters (0 display best)
docking_cluster_threshold 2.00
# docking_cluster_bumps number
# ------------ molecule orientation --------------
molecule_separation %(separation)i
commit_view """%({'separation': round(molSep)} )
macro ="""
# -------------- macro docking -------------------
macro_min_coverage 25
macro_sphere_radius 15
macro_docking_separation 25
activate_macro_model"""
tail = """
# -------------- docking setup -------------------
docking_search_mode 0 # full rotational search
receptor_range_angle 180 # 0, 15, 30, 45, 60, 75, 90, 180
docking_receptor_samples 720 # 362, 492, 642, 720, 980, 1280
ligand_range_angle 180
docking_ligand_samples 720
twist_range_angle 360 # 0, 15, 30, 60, 90, 180, 360
docking_alpha_samples 128 # 64, 128, 256
r12_step 0.500000 # 0.1, 0.2, 0.25, 0.5, 0.75, 1, 1.5, 2
r12_range %(range)i
docking_radial_filter 0 # Radial Envelope Filter - None
# docking_radial_filter 0 # Radial Envelope Filter - Re-entrant
# docking_radial_filter 0 # Radial Envelope Filter - Starlike
grid_size 0.600 # 0.4, 0.5, 0.6, 0.75, 1.0
# docking_electrostatics 0 # use only surface complimentarity
docking_electrostatics 1 # use electrostatic term for scoring clusters
docking_main_scan 16 #
docking_main_search 26
max_docking_solutions %(nr_sol)i # number of solutions to save
# -------------- post-processing ----------------
docking_refine 0 # None
# docking_refine 1 # Backbone Bumps and volumes
# docking_refine 2 # MM energies
# docking_refine 3 # MM minimization
# ---------------- run docking ------------------
activate_docking
save_docking %(output_clust)s
# save_range 1 512 ./ dock .pdb
# ------------ also save all solutions ----------
docking_sort_mode 0 # Sort solutions by energy (1 by cluster)
save_docking %(output_all)s""" \
%({'range':round(molRange), 'output_all':outName_all,
'nr_sol':int(options['sol']), 'output_clust':outName_clust} )
macOpen.writelines( head )
## select certain models
if rm or lm:
macOpen.write('\n')
macOpen.write('\n# -------------- select models -------------------\n')
if rm:
select_rec_model = 'dock_receptor_model %s'%rm
macOpen.write( select_rec_model + '\n')
if lm:
select_lig_model = 'dock_ligand_model %s'%lm
macOpen.write( select_lig_model + '\n')
## macro docking will not work with multiple models, if both are added to
## the hex macro file - macrodocking will be skipped during the docking run
if macroDocking:
macOpen.writelines( macro )
macOpen.writelines( tail )
macOpen.close()
def createHexInp(recPdb,
recModel,
ligPdb,
ligModel,
comPdb=None,
outFile=None,
macDock=None,
silent=0,
sol=512):
"""
Prepare a Hex macro file for the docking of the receptor(s)
against ligand(s).
@param recPdb: hex-formatted PDB
@type recPdb: str
@param recModel: hex-formatted PDB
@type recModel: str
@param ligPdb: PDBModel, get distances from this one
@type ligPdb: PDBModel
@param ligModel: PDBModel, getdistances from this one
@type ligModel: PDBModel
@param comPdb: reference PDB
@type comPdb: str
@param outFile: base of file name for mac and out
@type outFile: str
@param macDock: None -> hex decides (from the size of the molecule),
1 -> force macroDock, 0-> force off (default: None)
@type macDock: None|1|0
@param silent: don't print distances and macro warnings (default: 0)
@type silent: 0|1
@param sol: number of solutions that HEx should save (default: 512)
@type sol: int
@return: HEX macro file name, HEX out generated bu the macro,
macro docking status
@rtype: str, str, boolean
"""
## files and names
recCode = t.stripFilename(recPdb)[0:4]
ligCode = t.stripFilename(ligPdb)[0:4]
outFile = outFile or recCode + '-' + ligCode
## hex macro name
macName = t.absfile(outFile + '_hex.mac')
## hex rotation matrix output name
outName_all = t.absfile(outFile + '_hex.out')
outName_clust = t.absfile(outFile + '_hex_cluster.out')
## add surface profiles if not there
if not recModel.atoms.has_key('relAS'):
#t.flushPrint('\nCalculating receptor surface profile')
rec_asa = PDBDope(recModel)
rec_asa.addSurfaceRacer()
if not ligModel.atoms.has_key('relAS'):
#t.flushPrint('\nCalculating ligand surface profile')
lig_asa = PDBDope(ligModel)
lig_asa.addSurfaceRacer()
## surface masks, > 95% exposed
rec_surf_mask = N.greater(recModel.profile('relAS'), 95)
lig_surf_mask = N.greater(ligModel.profile('relAS'), 95)
## maximun and medisn distance from centre of mass to any surface atom
recMax, recMin = centerSurfDist(recModel, rec_surf_mask)
ligMax, ligMin = centerSurfDist(ligModel, lig_surf_mask)
## approxinate max and min center to centre distance
maxDist = recMax + ligMax
minDist = recMin + ligMin
## molecular separation and search range to be used in the docking
molSep = (maxDist + minDist) / 2
molRange = 2 * (maxDist - molSep)
if not silent:
print 'Docking setup: %s\nRecMax: %.1f RecMin: %.1f\nLigMax: %.1f LigMin: %.1f\nMaxDist: %.1f MinDist: %.1f\nmolecular_separation: %.1f r12_range: %.1f\n' % (
outFile, recMax, recMin, ligMax, ligMin, maxDist, minDist, molSep,
molRange)
if recMax > 30 and ligMax > 30 and not silent:
print '\nWARNING! Both the receptor and ligand radius is ',
print 'greater than 30A.\n'
## determine docking mode to use
macroDocking = 0
if macDock == None:
if recMax > 35 and not silent:
print '\nReceptor has a radius that exceeds 35A ',
print '-> Macro docking will be used'
macroDocking = 1
else:
macroDocking = macDock
#####################
## write macro file
macOpen = open(macName, 'w')
macOpen.write('# -- ' + macName + ' --\n')
macOpen.write(' \n')
macOpen.write('open_receptor ' + t.absfile(recPdb) + '\n')
macOpen.write('open_ligand ' + t.absfile(ligPdb) + '\n')
if comPdb and comPdb[-4:] == '.pdb':
macOpen.write('open_complex ' + comPdb + '\n')
macOpen.write('\n')
head = """
# -------------- general settings ----------------
disc_cache 1 # disc cache on (0 off)
docking_sort_mode 1 # Sort solutions by cluster (0 by energy)
docking_cluster_mode 1 # Display all clusters (0 display best)
docking_cluster_threshold 2.00
# docking_cluster_bumps number
# ------------ molecule orientation --------------
molecule_separation %(separation)i
commit_view """ % ({
'separation': round(molSep)
})
macro = """
# -------------- macro docking -------------------
macro_min_coverage 25
macro_sphere_radius 15
macro_docking_separation 25
activate_macro_model"""
tail = """
# -------------- docking setup -------------------
docking_search_mode 0 # full rotational search
receptor_range_angle 180 # 0, 15, 30, 45, 60, 75, 90, 180
docking_receptor_samples 720 # 362, 492, 642, 720, 980, 1280
ligand_range_angle 180
docking_ligand_samples 720
twist_range_angle 360 # 0, 15, 30, 60, 90, 180, 360
docking_alpha_samples 128 # 64, 128, 256
r12_step 0.500000 # 0.1, 0.2, 0.25, 0.5, 0.75, 1, 1.5, 2
r12_range %(range)i
docking_radial_filter 0 # Radial Envelope Filter - None
grid_size 0.600 # 0.4, 0.5, 0.6, 0.75, 1.0
# docking_electrostatics 0 # use only surface complimentarity
docking_electrostatics 1 # use electrostatic term for scoring clusters
docking_main_scan 16 #
docking_main_search 26
max_docking_solutions %(nr_sol)i # number of solutions to save
# -------------- post-processing ----------------
docking_refine 0 # None
# docking_refine 1 # Backbone Bumps
# docking_refine 2 # MM energies
# docking_refine 3 # MM minimization
# ---------------- run docking ------------------
activate_docking
# save_docking %(output_clust)s
# save_range 1 512 ./ dock .pdb
# ------------ also save all solutions ----------
docking_sort_mode 0 # Sort solutions by energy (1 by cluster)
save_docking %(output_all)s""" \
%({'range':round(molRange), 'output_all':outName_all,
'nr_sol':int(sol), 'output_clust':outName_clust} )
macOpen.writelines(head)
## macro docking will not work with multiple models, if both are added to
## the hex macro file - macrodocking will be skipped during the docking run
if macroDocking:
macOpen.writelines(macro)
macOpen.writelines(tail)
macOpen.close()
return macName, outName_all, macroDocking
traj.fit(prof='rms2avg')
f_global = traj.getFluct_global()
f_local = traj.getFluct_local()
ref = traj.getRef()
## disconnect ref from its source
ref.disconnect()
ref.atoms.set('fluct_global',
f_global,
comment='fluctuation around average position in A')
ref.atoms.set('fluct_local',
f_local,
comment='fluctuation after fitting to each residue backbone')
try:
doper = PDBDope(ref)
flushPrint('adding accessible surface profiles...')
doper.addSurfaceRacer()
except Exception, why:
errWriteln("Couldn't add surface area profiles, ProfileError: ", why)
dump(traj, options['o'])
traj.fit( prof='rms2avg', ref=traj.ref )
traj.fit( prof='rms2avg' )
f_global = traj.getFluct_global()
f_local = traj.getFluct_local()
ref = traj.getRef()
## disconnect ref from its source
ref.disconnect()
ref.atoms.set( 'fluct_global', f_global,
comment='fluctuation around average position in A' )
ref.atoms.set( 'fluct_local', f_local,
comment='fluctuation after fitting to each residue backbone')
try:
doper = PDBDope( ref )
flushPrint('adding accessible surface profiles...')
doper.addSurfaceRacer()
except Exception, why:
errWriteln("Couldn't add surface area profiles, ProfileError: ", why)
dump( traj, options['o'] )
def main(options):
##################
## files and names
receptorName = absfile(options['r'])
receptorCode = stripFilename(receptorName)[0:4]
ligandName = absfile(options['l'])
ligandCode = stripFilename(ligandName)[0:4]
complexName = absfile(options['c'])
rm = options['rm']
lm = options['lm']
if rm or lm:
rn = rm or '1'
ln = lm or '1'
baseName = receptorCode + '_' + rn + '-' + ligandCode + '_' + ln
else:
baseName = receptorCode + '-' + ligandCode
## hex macro name
macName = baseName + '_hex.mac'
## hex rotation matrix output name
outName_all = baseName + '_hex.out'
outName_clust = baseName + '_hex_cluster.out'
## load model dictionaries, if they exist in the same directory
## as the corresponding pdb-file and start with the same pdb-code
## and ends with '_model.dic'
try:
rec_dic = stripFilename(options['r'])[:4] + '_model.dic'
rec_path = options['r'][:options['r'].rfind('/')]
lig_dic = stripFilename(options['l'])[:4] + '_model.dic'
lig_path = options['l'][:options['l'].rfind('/')]
rec = load(absfile(rec_path + '/' + rec_dic))
lig = load(absfile(lig_path + '/' + lig_dic))
print 'Loading dictionaries'
if type(rec) is dict:
rec = rec[1]
if type(lig) is dict:
lig = lig[1]
## could not load dictionaty, will load pdb-file insted
except:
print 'Loading pdb files'
rec = PDBModel(receptorName)
lig = PDBModel(ligandName)
#############################
## get structural information
## add surface profiles if not there
if not rec.atoms.has_key('relASA'):
flushPrint('\nCalculating receptor surface profile')
rec_asa = PDBDope(rec)
rec_asa.addASA()
if not lig.atoms.has_key('relASA'):
flushPrint('\nCalculating ligand surface profile')
lig_asa = PDBDope(lig)
lig_asa.addASA()
## surface masks, > 95% exposed
rec_surf_mask = greater(rec.profile('relASA'), 95)
lig_surf_mask = greater(lig.profile('relASA'), 95)
## maximun and medisn distance from centre of mass to any surface atom
recMax, recMin = centerSurfDist(rec, rec_surf_mask)
ligMax, ligMin = centerSurfDist(lig, lig_surf_mask)
## approxinate max and min center to centre distance
maxDist = recMax + ligMax
minDist = recMin + ligMin
print '\n\nReceptor and ligand max radius are %i and %i A, respectively.'\
%( recMax, ligMax )
print 'Receptor and ligand min radius are %i and %i A, respectively.'\
%( recMin, ligMin )
## molecular separation and search range to be used in the docking
molSep = (maxDist + minDist) / 2
molRange = 2 * (maxDist - molSep)
print 'A molecular separation of %i A and a search range of +-%i will be used.'\
%( molSep, molRange )
## determine docking mode to use
macroDocking = 0
if recMax > 30 and ligMax > 30:
print '\nWARNING! Both the receptor and ligand radius is greater than 30 A.\n'
if recMax > 30:
print '\nReceptor has a radius that exceeds 30 A -> Macro docking will be used'
macroDocking = 1
#####################
## write macro file
macOpen = open(macName, 'w')
macOpen.write('# ------------------- ' + macName +
' -----------------------\n')
macOpen.write(' \n')
macOpen.write('open_receptor ' + receptorName + '\n')
macOpen.write('open_ligand ' + ligandName + '\n')
if complexName[-4:] == '.pdb':
macOpen.write('open_complex ' + complexName + '\n')
macOpen.write('\n')
head = """
# -------------- general settings ----------------
disc_cache 1 # disc cache on (0 off)
docking_sort_mode 1 # Sort solutions by cluster (0 by energy)
docking_cluster_mode 1 # Display all clusters (0 display best)
docking_cluster_threshold 2.00
# docking_cluster_bumps number
# ------------ molecule orientation --------------
molecule_separation %(separation)i
commit_view """ % ({
'separation': round(molSep)
})
macro = """
# -------------- macro docking -------------------
macro_min_coverage 25
macro_sphere_radius 15
macro_docking_separation 25
activate_macro_model"""
tail = """
# -------------- docking setup -------------------
docking_search_mode 0 # full rotational search
receptor_range_angle 180 # 0, 15, 30, 45, 60, 75, 90, 180
docking_receptor_samples 720 # 362, 492, 642, 720, 980, 1280
ligand_range_angle 180
docking_ligand_samples 720
twist_range_angle 360 # 0, 15, 30, 60, 90, 180, 360
docking_alpha_samples 128 # 64, 128, 256
r12_step 0.500000 # 0.1, 0.2, 0.25, 0.5, 0.75, 1, 1.5, 2
r12_range %(range)i
docking_radial_filter 0 # Radial Envelope Filter - None
# docking_radial_filter 0 # Radial Envelope Filter - Re-entrant
# docking_radial_filter 0 # Radial Envelope Filter - Starlike
grid_size 0.600 # 0.4, 0.5, 0.6, 0.75, 1.0
# docking_electrostatics 0 # use only surface complimentarity
docking_electrostatics 1 # use electrostatic term for scoring clusters
docking_main_scan 16 #
docking_main_search 26
max_docking_solutions %(nr_sol)i # number of solutions to save
# -------------- post-processing ----------------
docking_refine 0 # None
# docking_refine 1 # Backbone Bumps and volumes
# docking_refine 2 # MM energies
# docking_refine 3 # MM minimization
# ---------------- run docking ------------------
activate_docking
save_docking %(output_clust)s
# save_range 1 512 ./ dock .pdb
# ------------ also save all solutions ----------
docking_sort_mode 0 # Sort solutions by energy (1 by cluster)
save_docking %(output_all)s""" \
%({'range':round(molRange), 'output_all':outName_all,
'nr_sol':int(options['sol']), 'output_clust':outName_clust} )
macOpen.writelines(head)
## select certain models
if rm or lm:
macOpen.write('\n')
macOpen.write('\n# -------------- select models -------------------\n')
if rm:
select_rec_model = 'dock_receptor_model %s' % rm
macOpen.write(select_rec_model + '\n')
if lm:
select_lig_model = 'dock_ligand_model %s' % lm
macOpen.write(select_lig_model + '\n')
## macro docking will not work with multiple models, if both are added to
## the hex macro file - macrodocking will be skipped during the docking run
if macroDocking:
macOpen.writelines(macro)
macOpen.writelines(tail)
macOpen.close()
return pm
if __name__ == '__main__':
from Biskit import PDBDope
from Biskit.tools import *
from Biskit.Dock import Complex
print "Loading"
m_com = load(testRoot() + '/com/ref.complex').model()
rec = m_com.takeChains([0])
lig = m_com.takeChains([1])
## add molecular surface to components
doper = PDBDope(rec)
doper.addSurfaceRacer(probe=1.4)
surf_rec = rec.profile2mask('MS', 0.0001, 101)
doper = PDBDope(lig)
doper.addSurfaceRacer(probe=1.4)
surf_lig = lig.profile2mask('MS', 0.0001, 101)
## kick out non-surface
rec = rec.compress(surf_rec)
lig = lig.compress(surf_lig)
com = Complex(rec, lig)
## get interface patch
cont = com.atomContacts(cutoff=6.0)
return pm
if __name__ == '__main__':
from Biskit import PDBDope
from Biskit.tools import *
from Biskit.Dock import Complex
print "Loading"
## m_com = load( testRoot() + '/com_wet/dry_com.model' )
m_com = load( testRoot() + '/com/ref.complex').model()
m_com._resIndex = None ## HACK, something wrong with legacy _resIndex
doper = PDBDope( m_com )
doper.addSurfaceRacer()
mask = m_com.profile2mask( 'relAS', 5, 101 )
m = m_com.compress( mask )
## get patches and put them into Pymoler for display
print "Patching"
pm = test( m )
## show real interface patch
com = Complex( m_com.takeChains([0]), m_com.takeChains([1]))
cont = com.atomContacts()
rec_i = N.flatnonzero( N.sum( cont, 1 ) )
lig_i = N.flatnonzero( N.sum( cont, 0 ) )
if __name__ == '__main__':
from Biskit import PDBDope
from Biskit.tools import *
from Biskit.Dock import Complex
print "Loading"
m_com = load( testRoot() + '/com/ref.complex' ).model()
rec = m_com.takeChains([0])
lig = m_com.takeChains([1])
## add molecular surface to components
doper = PDBDope( rec )
doper.addSurfaceRacer( probe=1.4 )
surf_rec = rec.profile2mask( 'MS', 0.0001, 101 )
doper = PDBDope( lig )
doper.addSurfaceRacer( probe=1.4 )
surf_lig = lig.profile2mask( 'MS', 0.0001, 101 )
## kick out non-surface
rec = rec.compress( surf_rec )
lig = lig.compress( surf_lig )
com = Complex( rec, lig )
## get interface patch
cont = com.atomContacts( cutoff=6.0 )
def test_Complex(self):
"""Dock.Complex test"""
lig = PCRModel( t.testRoot() + "/com/1BGS.psf",
t.testRoot() + "/com/lig.model")
rec = PCRModel( t.testRoot() + "/com/1BGS.psf",
t.testRoot() + "/com/rec.model")
rec = rec.compress( rec.maskHeavy() )
lig = lig.compress( lig.maskHeavy() )
c = Complex(rec, lig)
c.info['soln'] = 1
cont = c.atomContacts( 6.0 )
contProfile_lig = N.sum( cont )
contProfile_rec = N.sum( cont, 1 )
try:
dope = PDBDope( c.rec_model )
dope.addSurfaceRacer( probe=1.4 )
rec_surf = c.rec_model.profile2mask( 'MS', 0.0000001, 1000 )
dope = PDBDope( c.lig_model )
dope.addSurfaceRacer( probe=1.4 )
lig_surf = c.lig_model.profile2mask( 'MS', 0.0000001, 1000 )
except:
pass
if self.local:
from Biskit import Pymoler
self.pm = Pymoler()
self.pm.addPdb( c.rec(), 'rec' )
self.pm.addPdb( c.lig(), 'lig' )
self.pm.colorAtoms( 'rec', contProfile_rec )
self.pm.colorAtoms( 'lig', contProfile_lig )
rec_sphere = c.rec().clone()
rec_sphere.xyz = mathUtils.projectOnSphere( rec_sphere.xyz )
lig_sphere = c.lig().clone()
lig_sphere.xyz = mathUtils.projectOnSphere( lig_sphere.xyz )
self.pm.addPdb( rec_sphere, 'rec_sphere' )
self.pm.addPdb( lig_sphere, 'lig_sphere' )
self.pm.colorAtoms( 'rec_sphere', contProfile_rec )
self.pm.colorAtoms( 'lig_sphere', contProfile_lig )
self.pm.add( 'hide all')
self.pm.add( 'color grey, (b=0)' )
self.pm.add( 'show stick, (rec or lig)' )
self.pm.add( 'show surf, rec_sphere')
self.pm.add( 'zoom all' )
self.pm.show()
globals().update( locals() )
self.assertEqual( N.sum(contProfile_lig) + N.sum(contProfile_rec),
2462 )
def conservationScore( self, cons_type='cons_ent', ranNr=150,
log=StdLog(), verbose=1 ):
"""
Score of conserved residue pairs in the interaction surface.
Optionally, normalized by radom surface contacts.
@param cons_type: precalculated conservation profile name,
see L{Biskit.PDBDope}.
@type cons_type: str
@param ranNr: number of random matricies to use (default: 150)
@type ranNr: int
@param log: log file [STDOUT]
@type log: Biskit.LogFile
@param verbose: give progress report [1]
@type verbose: bool | int
@return: conservation score
@rtype: float
"""
try:
recCons = self.rec().profile( cons_type, updateMissing=1 )
except:
if verbose:
log.add('\n'+'*'*30+'\nNO HHM PROFILE FOR RECEPTOR\n'+\
'*'*30+'\n')
recCons = N.ones( self.rec().lenResidues() )
try:
ligCons = self.lig().profile( cons_type, updateMissing=1 )
except:
if verbose:
log.add(\
'\n'+'*'*30+'\nNO HHM PROFILE FOR LIGAND\n'+'*'*30+'\n')
ligCons = N.ones( self.lig().lenResidues() )
if self.rec().profile( 'surfMask' ):
recSurf = self.rec().profile( 'surfMask' )
else:
d = PDBDope(self.rec())
d.addSurfaceMask()
if self.lig().profile( 'surfMask' ):
ligSurf = self.lig().profile( 'surfMask' )
else:
d = PDBDope(self.lig())
d.addSurfaceMask()
surfMask = N.ravel(N.outerproduct( recSurf, ligSurf ))
missing = N.outerproduct( N.equal( recCons, 0), N.equal(ligCons,0))
cont = self.resContacts() * N.logical_not(missing)
consMat = N.outerproduct( recCons, ligCons )
score = cont* consMat
# get a random score
if ranNr != 0:
if self.verbose:
self.log.write('.')
ranMat = mathUtils.random2DArray( cont, ranNr, mask=surfMask )
random_score = N.sum(N.sum( ranMat * consMat ))/( ranNr*1.0 )
return N.sum(N.sum(score))/random_score
else:
return N.sum(N.sum(score))/ N.sum(N.sum(cont))
def foldXEnergy( self, force=1 ):
"""
Calculate E_rec and/or E_lig only if not given::
E_com - (E_rec + E_lig).
@param force: force calc of E_rec and E_lig
@type force: 1|0
@return: dict with the different fold-X energy terms
@rtype: dict
"""
rec, lig = self.rec_model, self.lig_model
## add/update lig/rec fold-X energies if necessary
if not 'foldX' in rec.info or rec.xyzChanged or force:
d = PDBDope( rec )
d.addFoldX()
if not 'foldX' in lig.info or lig.xyzChanged or force:
d = PDBDope( lig )
d.addFoldX()
try:
self.lig_transformed.info = lig.info
except:
pass
m = self.model()
d = PDBDope( m )
d.addFoldX()
e_rec = rec.info['foldX']
e_lig = lig.info['foldX']
e_com = m.info['foldX']
r = {}
for key in e_com:
e = e_com[key] - ( e_lig[key] + e_rec[key] )
r[key] = e
return r
def createHexInp( recPdb, recModel, ligPdb, ligModel, comPdb=None,
outFile=None, macDock=None, silent=0, sol=512 ):
"""
Prepare a Hex macro file for the docking of the receptor(s)
against ligand(s).
@param recPdb: hex-formatted PDB
@type recPdb: str
@param recModel: hex-formatted PDB
@type recModel: str
@param ligPdb: PDBModel, get distances from this one
@type ligPdb: PDBModel
@param ligModel: PDBModel, getdistances from this one
@type ligModel: PDBModel
@param comPdb: reference PDB
@type comPdb: str
@param outFile: base of file name for mac and out
@type outFile: str
@param macDock: None -> hex decides (from the size of the molecule),
1 -> force macroDock, 0-> force off (default: None)
@type macDock: None|1|0
@param silent: don't print distances and macro warnings (default: 0)
@type silent: 0|1
@param sol: number of solutions that HEx should save (default: 512)
@type sol: int
@return: HEX macro file name, HEX out generated bu the macro,
macro docking status
@rtype: str, str, boolean
"""
## files and names
recCode = t.stripFilename( recPdb )[0:4]
ligCode = t.stripFilename( ligPdb )[0:4]
outFile = outFile or recCode + '-' + ligCode
## hex macro name
macName = t.absfile( outFile + '_hex.mac' )
## hex rotation matrix output name
outName_all = t.absfile( outFile + '_hex.out' )
outName_clust = t.absfile( outFile + '_hex_cluster.out')
## add surface profiles if not there
if not recModel.atoms.has_key('relAS'):
#t.flushPrint('\nCalculating receptor surface profile')
rec_asa = PDBDope( recModel )
rec_asa.addSurfaceRacer()
if not ligModel.atoms.has_key('relAS'):
#t.flushPrint('\nCalculating ligand surface profile')
lig_asa = PDBDope( ligModel )
lig_asa.addSurfaceRacer()
## surface masks, > 95% exposed
rec_surf_mask = N.greater( recModel.profile('relAS'), 95 )
lig_surf_mask = N.greater( ligModel.profile('relAS'), 95 )
## maximun and medisn distance from centre of mass to any surface atom
recMax, recMin = centerSurfDist( recModel, rec_surf_mask )
ligMax, ligMin = centerSurfDist( ligModel, lig_surf_mask )
## approxinate max and min center to centre distance
maxDist = recMax + ligMax
minDist = recMin + ligMin
## molecular separation and search range to be used in the docking
molSep = ( maxDist + minDist ) / 2
molRange = 2 * ( maxDist - molSep )
if not silent:
print 'Docking setup: %s\nRecMax: %.1f RecMin: %.1f\nLigMax: %.1f LigMin: %.1f\nMaxDist: %.1f MinDist: %.1f\nmolecular_separation: %.1f r12_range: %.1f\n'%(outFile, recMax, recMin, ligMax, ligMin, maxDist, minDist, molSep, molRange)
if recMax > 30 and ligMax > 30 and not silent:
print '\nWARNING! Both the receptor and ligand radius is ',
print 'greater than 30A.\n'
## determine docking mode to use
macroDocking = 0
if macDock==None:
if recMax > 35 and not silent:
print '\nReceptor has a radius that exceeds 35A ',
print '-> Macro docking will be used'
macroDocking = 1
else:
macroDocking = macDock
#####################
## write macro file
macOpen= open( macName, 'w')
macOpen.write('# -- ' + macName + ' --\n')
macOpen.write(' \n')
macOpen.write('open_receptor '+ t.absfile(recPdb) +'\n')
macOpen.write('open_ligand '+ t.absfile(ligPdb) +'\n')
if comPdb and comPdb[-4:] == '.pdb':
macOpen.write('open_complex '+comPdb+'\n')
macOpen.write('\n')
head = """
# -------------- general settings ----------------
disc_cache 1 # disc cache on (0 off)
docking_sort_mode 1 # Sort solutions by cluster (0 by energy)
docking_cluster_mode 1 # Display all clusters (0 display best)
docking_cluster_threshold 2.00
# docking_cluster_bumps number
# ------------ molecule orientation --------------
molecule_separation %(separation)i
commit_view """%({'separation': round(molSep)} )
macro ="""
# -------------- macro docking -------------------
macro_min_coverage 25
macro_sphere_radius 15
macro_docking_separation 25
activate_macro_model"""
tail = """
# -------------- docking setup -------------------
docking_search_mode 0 # full rotational search
receptor_range_angle 180 # 0, 15, 30, 45, 60, 75, 90, 180
docking_receptor_samples 720 # 362, 492, 642, 720, 980, 1280
ligand_range_angle 180
docking_ligand_samples 720
twist_range_angle 360 # 0, 15, 30, 60, 90, 180, 360
docking_alpha_samples 128 # 64, 128, 256
r12_step 0.500000 # 0.1, 0.2, 0.25, 0.5, 0.75, 1, 1.5, 2
r12_range %(range)i
docking_radial_filter 0 # Radial Envelope Filter - None
grid_size 0.600 # 0.4, 0.5, 0.6, 0.75, 1.0
# docking_electrostatics 0 # use only surface complimentarity
docking_electrostatics 1 # use electrostatic term for scoring clusters
docking_main_scan 16 #
docking_main_search 26
max_docking_solutions %(nr_sol)i # number of solutions to save
# -------------- post-processing ----------------
docking_refine 0 # None
# docking_refine 1 # Backbone Bumps
# docking_refine 2 # MM energies
# docking_refine 3 # MM minimization
# ---------------- run docking ------------------
activate_docking
# save_docking %(output_clust)s
# save_range 1 512 ./ dock .pdb
# ------------ also save all solutions ----------
docking_sort_mode 0 # Sort solutions by energy (1 by cluster)
save_docking %(output_all)s""" \
%({'range':round(molRange), 'output_all':outName_all,
'nr_sol':int(sol), 'output_clust':outName_clust} )
macOpen.writelines( head )
## macro docking will not work with multiple models, if both are added to
## the hex macro file - macrodocking will be skipped during the docking run
if macroDocking:
macOpen.writelines( macro )
macOpen.writelines( tail )
macOpen.close()
return macName, outName_all, macroDocking
## Load Trajectories - read and sort bound ligand and recepror trajectories
traj_rec_ref = Trajectory( [ ref_rec_file ] )
traj_lig_ref = Trajectory( [ ref_lig_file ] )
traj_rec, traj_rec_ref = castTraj( traj_rec, traj_rec_ref )
traj_lig, traj_lig_ref = castTraj( traj_lig, traj_lig_ref )
refCom = ProteinComplex( traj_rec_ref.ref, traj_lig_ref.ref )
traj_rec = traj_rec_ref.concat( traj_rec )
traj_lig = traj_lig_ref.concat( traj_lig )
## Add surface atom profile
flushPrint('Adding accessible surface profiles...\n')
rec_asa = PDBDope( traj_rec.getRef() )
rec_asa.addASA()
lig_asa = PDBDope( traj_lig.getRef() )
lig_asa.addASA()
## Atom sets to use for analysis
## Sets are(only heavy atoms):
masks_all , mask_all_names = allMasks( traj_rec, traj_lig, refCom )
## Masks restricted to surface atoms
masks_surf , mask_surf_names = surfMasks( traj_rec, traj_lig, refCom )
## pairwise rmsd calculation
rmsd_all_dic = calcAllRmsds( traj_rec, traj_lig, masks_all )
rmsd_surf_dic = calcAllRmsds( traj_rec, traj_lig, masks_surf )