def write_restraints(inp, initial_confs, start, end, start_xvg, end_xvg, tpr, top, includes, n, ndx_file, Nchains):
# Get the atoms involved with the residues to use for dihedrals (might be more than one atom in the index
# per residue, since it's probably generated by make_ndx)
ndx_atoms = res_selection.read_ndx(ndx_file)
# Map them to each affected residue so we just get the residue numbers back
selection = res_selection.res_select(start, ndx_atoms)
n = int(n) # number of points in the string, including start and end point
use_interpolation = False
if initial_confs is None or len(initial_confs) == 0:
use_interpolation = True
# Read the starting and ending dihedrals for later interpolation
startpts = readxvg.readxvg(start_xvg, selection)
endpts = readxvg.readxvg(end_xvg, selection)
else:
# Have to generate the dihedrals ourselves from the given initial structures
# Note: when we get an initial_confs[] array, we use it for all points and
# the start/end input parameters are completely ignored
# TODO: assert that len(initial_confs) == n otherwise?
ramaprocs = {}
# Run g_rama (in parallel) on each structure and output to a temporary .xvg
FNULL = open(os.devnull, 'w') # dont generate spam from g_rama
for i in range(n):
# TODO: check for and use g_rama_mpi.. like everywhere else
ramaprocs[i] = Popen(['g_rama', '-f', initial_confs[i], '-s', tpr, '-o', '0%3d.xvg' % i],
stdout=FNULL, stderr=FNULL)
# Go through the output from the rama sub-processes and read the xvg outputs
stringpts = {} # Will have 4 levels: stringpoint, residue, chain, phi/psi value
for i in range(n):
# Start array indexed by residue
xvg_i = os.path.join(inp.getOutputDir(), '0%3d.xvg' % i)
# Make sure the corresponding g_rama task has ended
ramaprocs[i].communicate()
# Read back and parse like for the start/end_xvg above
stringpts[i] = readxvg.readxvg(xvg_i, selection)
# Rewrite the topology to include the res itp files instead of the original per-chain itps (if any)
# There will be one topol_x.top per string point
sys.stderr.write('%s' % includes)
for k in range(n):
with open(top) as in_topf:
in_top = in_topf.read()
for mol in range(Nchains):
if len(includes) > 0:
includename = includes[mol].split('/')[-1]
in_top = re.sub(includename, 'res_%d_chain_%d.itp' % (k, mol), in_top)
with open('topol_%d.top' % k,'w') as out_top:
# sys.stderr.write('%s'%in_top)
out_top.write(in_top)
# Generate/copy and write-out the dihedrals for each point
for k in range(n):
for mol in range(Nchains):
# TODO: use with statement for restraint_itp as well
restraint_itp = open('res_%d_chain_%d.itp' % (k, mol), 'w')
if Nchains > 1:
with open(includes[mol]) as moltop_f:
moltop = moltop_f.read()
restraint_itp.write(moltop)
# write the initial part of the topology file
# Note: gromacs 4.6+ required
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al type phi dphi kfac\n")
if len(includes) > 0:
protein = molecule(includes[mol])
# replace the chain names with the chain names
else:
with open('topol_%d.top' % k, 'w') as out_top:
protein = molecule(top)
with open(top,'r') as in_itp_f:
in_itp = in_itp_f.read().split('; Include Position restraint file')
out_top.write(in_itp[0])
out_top.write('#include "res_%d_chain_%d.itp"\n' % (k, mol))
out_top.write(in_itp[1])
# Create a lookup-table for the protein topology that maps residue to dihedrally relevant
# backbone atom indices for N, CA and C.
dih_atoms = {}
for a in protein:
if (a.atomname == 'CA' or a.atomname == 'N' or a.atomname == 'C'):
try:
dih_atoms[a.resnr][a.atomname] = a.atomnr;
except KeyError:
dih_atoms[a.resnr] = { a.atomname: a.atomnr }
# Use the lookup-table built above and get the dihedral specification atoms needed for each
# residue in the selection. This is O(n) in residues, thanks to the dih_atoms table.
for r in selection:
# Get the atom numbers to use for the phi and psi dihedrals (4 atoms each)
# phi is C on the previous residue, and N, CA, C on this
phi = [ dih_atoms[r - 1]['C'], dih_atoms[r]['N'], dih_atoms[r]['CA'], dih_atoms[r]['C'] ]
# psi is N, CA and C on this residue and N on the next
psi = [ dih_atoms[r]['N'], dih_atoms[r]['CA'], dih_atoms[r]['C'], dih_atoms[r + 1]['N'] ]
# Write phi, psi angles and the associated k factor into a row in the restraint file
# Note: in the Gromacs 4.6+ format, the k-factor is here. Before, it was in the .mdp as
# dihre_fc.
# Also see reparametrize.py
if use_interpolation:
# k is from 0 to n-1, so map it so we get a factor from 0 to 1
phi_val = startpts[r][mol][0] + k * (endpts[r][mol][0] - startpts[r][mol][0]) / (n - 1)
psi_val = startpts[r][mol][1] + k * (endpts[r][mol][1] - startpts[r][mol][1]) / (n - 1)
else:
# Use the values extracted from the initial_confs[] structures above
phi_val = stringpts[k][r][mol][0]
psi_val = stringpts[k][r][mol][1]
# Since we need different force constants in different stages, we need to put
# a searchable placeholder in the file here and replace it later. KFAC is normally
# a %8.4f number.
restraint_itp.write("%5d%5d%5d%5d%5d %8.4f%5d KFAC\n"
%(phi[0], phi[1], phi[2], phi[3], 1, phi_val, 0))
restraint_itp.write("%5d%5d%5d%5d%5d %8.4f%5d KFAC\n"
%(psi[0], psi[1], psi[2], psi[3], 1, psi_val, 0))
restraint_itp.close()
def reparametrize(diheds, selection, start_conf, start_xvg, end_conf, end_xvg, top):
Nswarms = len(diheds[0])
rsel = res_selection.res_select('%s'%start_conf,'%s'%selection)
# calculate average drift in collective variables space
sys.stderr.write('Residue selection: %s' %rsel)
newpts = []
for interp in range(len(diheds)):
avg = []
for r in rsel:
driftList = []
for i in range(len(diheds[interp])):
vec=[]
xvg = open(diheds[interp][i],'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
vec+=[phi_val,psi_val]
driftList.append(vec)
# driftList has phi,psi values for residue in every swarm
avg+=[scale((1/float(Nswarms)),reduce(mapadd,driftList))]
newpts+=avg
# extract initial and target dihedral values
initpt = []
for r in rsel:
xvg = open(start_xvg,'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
initpt+=[phi_val,psi_val]
targetpt = []
for r in rsel:
xvg = open(end_xvg,'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
targetpt+=[phi_val,psi_val]
# something with 1 indexing makes this padding necessary.
paddingpt=[0]*len(initpt)
newpts.insert(0,initpt)
newpts.append(targetpt)
newpts.append(paddingpt)
sys.stderr.write('The new list of points is: %s\n' %newpts)
for pt in newpts:
sys.stderr.write('%s %s\n'%(pt[0],pt[1]))
adjusted=rep_pts(newpts)
# TODO implement a dist_treshold=1.0
iters=[adjusted]
for i in range(100):
iters.append(rep_pts(iters[i]))
adjusted=iters[-1]
# delete the padding point
adjusted=adjusted[:-1]
sys.stderr.write('The adjusted points are:\n')
for pt in adjusted:
sys.stderr.write('%s %s\n'%(pt[0],pt[1]))
# calculate reparam distance
# TODO measure the distance between the reparametrized points and the input points
# write the topology for the next iteration
# treat the reparam values as a stack
for k in range(1,len(adjusted)-1):
for chain in range(Nchains):
restraint_itp=open('topol_%d_chain_%d.top'%(k,chain),'w')
in_itp=open(include[k][chain], 'w')
moltop=restraint_itp.split('[ dihedral_restraints ]')[0]
restraint_itp.write('%s'%moltop)
sys.stderr.write("Writing restraints for interpolant point %d chain %d\n"%(k,chain))
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al type label phi dphi kfac power\n")
pathpoint=adjusted[k] # just a list of phi/psi angles
protein=molecule('%s'%include[k][chain])
# keep track of the position in the path point
pos=0
for r in rsel:
# there may be multiple residues matching the resnr, e.g., dimers
phi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'CA' or a.atomname == 'N' or a.atomname == 'C')) or
(a.resnr == int(r)-1 and a.atomname == 'C')]
psi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'N' or a.atomname == 'CA' or a.atomname == 'C')) or
(a.resnr == int(r)+1 and a.atomname == 'N')]
# get phi and psi values from the reparametrization vector
phi_val=stack[pos+chain]
psi_val=stack[pos+chain+1]
# write phi, psi angles
restraint_itp.write("%5d%5d%5d%5d%5d%5d %8.4f%5d%5d%5d\n"
%(phi[0],phi[1],phi[2],phi[3],1,1,phi_val,0,1,2))
restraint_itp.write("%5d%5d%5d%5d%5d%5d %8.4f%5d%5d%5d\n"
%(psi[0],psi[1],psi[2],psi[3],1,1,psi_val,0,1,2))
#restraint_itp.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(phi[i*4].atomnr,phi[i*4+1].atomnr,
# phi[i*4+2].atomnr,phi[i*4+3].atomnr,1,1,phi_val,0,1,2))
#restraint_itp.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(psi[i*4].atomnr,psi[i*4+1].atomnr,
# psi[i*4+2].atomnr,psi[i*4+3].atomnr,1,1,psi_val,0,1,2))
# delete the already added values from the stack
pos+=2*Nchains
restraint_itp.close()
def reparametrize(use_posres, fix_endpoints, cvs, ndx_file, Nchains,
start_conf, start_xvg, end_conf, end_xvg, last_resconfs, top,
includes):
Nswarms = len(cvs[0])
ndx_atoms = res_selection.read_ndx(ndx_file)
# For dihedrals, we map the atoms to residues for a single chain, and the readxvg etc. will read the entire file and
# select the same residues in each chain. But for the position restraints which use the atom indices directly, we have
# to first expand the index so it covers all chains.
# TODO: have to figure out or input atoms per chain in the .gro's so we can repeat the atom-selection Nchains times
# for the posres case. The ndx file is for atoms inside the chain, but the .gro will contain global numbering.
# We can detect the chain-repeat in rwgro, by looking for repeating first residue name.
# Hardcode a repeat for testing for now.
if use_posres == 0:
# Map atoms to residues for the dihedral selection
rsel = res_selection.res_select('%s' % start_conf, ndx_atoms)
#sys.stderr.write('Residue selection: %s' %rsel)
# else:
# selected_atoms = []
# for ch in range(5):
# for i in range(len(ndx_atoms)):
# selected_atoms += [ ndx_atoms[i] + ch * 5566 ]
# Calculate the average drift in CV space
# newpts is a per-swarm-point list of CV points (each a list of the CV dimension length)
newpts = []
# Note: the cvs[][] array is indexed after the number of stringpoints that actually were swarm-processed,
# so depending on the fix_endpoints option it may or may not exactly match the path[] which always include
# all points. If we only read in N-2 points here, the start/end will be added to newpts in the code further below.
for pathpt in range(len(cvs)):
swarmpts = []
for i in range(len(cvs[pathpt])):
if use_posres == 1:
zpt = rwgro.readgro_flat(cvs[pathpt][i], ndx_atoms)
#sys.stderr.write('Read pathpt %d swarm %d (%s), got %d CVs\n' % (pathpt, i, cvs[pathpt][i], len(zpt)))
else:
zpt = readxvg.readxvg_flat(cvs[pathpt][i], rsel)
swarmpts.append(zpt)
zptsum = reduce(mapadd, swarmpts)
avgdrift = scale((1 / float(Nswarms)), zptsum)
newpts.append(avgdrift)
# Read in the fixed start and end CV values, for the fix_endpoints case (otherwise the start/end will
# be allowed to drift just like the other points, and they will already then be a part of the newpts array)
if fix_endpoints == 1:
if use_posres == 1:
# TODO: the start/end_conf are full Systems so the atom numbering aliases for the ndx_atoms array :/
# Currently fixed in readgro_flat temporary, hardcoded for the GLIC Protein number.
initpt = rwgro.readgro_flat(start_conf, ndx_atoms)
targetpt = rwgro.readgro_flat(end_conf, ndx_atoms)
else:
initpt = readxvg.readxvg_flat(start_xvg, rsel)
targetpt = readxvg.readxvg_flat(end_xvg, rsel)
sys.stderr.write('Length of initpt %d, targetpt %d\n' %
(len(initpt), len(targetpt)))
# Insert the start/end in the beginning and last of newpts
newpts.insert(0, initpt)
newpts.append(targetpt)
# something with 1 indexing makes this padding necessary. TODO: check if this is needed anymore
paddingpt = [0] * len(newpts[0])
newpts.append(paddingpt)
# Do the actual reparameterization
# newpts is a 2D list, first level is one per stringpoint, second is the linear list of CVs
# rep_pts returns the maximum spread of the CV distances between points in [0] and the adjusted
# points in [1]
# Initial iteration
rep_it1 = ext_rep_pts(newpts)
adjusted = rep_it1[1] # get the points only, ignore the spread result
# Keep iterating, feeding the result of the previous result into rep_pts again
# Note that with long CV vectors (> 4000 dimensions) iterations takes a long time
# (at least 45 min for 25 iterations on a single-core 3.5 GHz) when using the python rep_pts.
# We can abort early when the maximum spread between points in the updated string goes
# below a threshold
iters = [adjusted]
i = 0
maxspread = 100.0
# Do max 150 iterations even if we don't reach our goal
while i < 150 and maxspread > 0.012:
sys.stderr.write('Rep iter %d: \n' % i)
sys.stderr.flush()
rep_it = ext_rep_pts(iters[i])
maxspread = rep_it[0]
sys.stderr.write(' maxspread was %f\n' % maxspread)
# Remember the adjusted points
iters.append(rep_it[1])
i = i + 1
sys.stderr.write('Final maximum spread %f after %d iterations.\n' %
(maxspread, i))
# Get the final iteration's result
adjusted = iters[-1]
# delete the padding point
adjusted = adjusted[:-1]
newpts = newpts[:-1]
#sys.stderr.write('Pts before repa:\n %s\n' % newpts)
#sys.stderr.write('The adjusted pts:\n %s\n' % adjusted)
# Possibility to test skipping reparametrize by uncommenting the next row.
# The stringpoints will drift along the string and probably end up in the
# endpoints or a minima along the string.
#adjusted = newpts
# calculate reparam distance
sys.stderr.write('Length of the adjusted vector: %d\n' % len(adjusted))
# TODO Nchains should depend on the specific residue (?)
# Given as function argument now.
#Nchains = len(initpt) / (2 * len(rsel))
# write the CV control data for the next iteration
# The output file expected for the posres case is rep_resconf_%d.gro for each stringpoint.
# For dihedrals its res_%d_chain_%d.itp for each stringpoint and chain.
#
for k in range(len(adjusted)):
# Not necessary to do this output for the start/end-points in the fix_endpoints case, the data is
# just bypassed in the caller script
if fix_endpoints == 1 and (k == 0 or k == (len(adjusted) - 1)):
continue
if use_posres == 1:
# Open the output resconf which will go into the next iteration as minimization target
with open('rep_resconf_%d.gro' % k, 'w') as rep_resconf:
# Open and read the previous (input) resconf, which has basically tagged along since the last
# reparametrization step (or was set initially at swarm-start)
with open(last_resconfs[k], 'r') as in_resconf_f:
in_resconf = in_resconf_f.readlines()
# TODO: maybe this chunk of code could be done by the rwgro module for us.
# Copy the first 2 rows (title and number of atoms) straight over
rep_resconf.write(in_resconf[0])
rep_resconf.write(in_resconf[1])
# Go through the atoms row-by-row and update the xyz coordinates for the atoms the reparametrize
# step moved
# Note: we are only copying over positions here. The velocities are not needed as the use for these files
# will only be as a base for the next iterations position restraint coordinates.
pathpoint = adjusted[
k] # the 1-D list of CVs (positions): x,y,z * nbr atoms in index
if len(pathpoint) != (1555 *
3): # assert on GLIC length (TODO)
sys.stderr.write('adjusted[] entry of wrong length %d\n' %
len(pathpoint))
cvpos = 0
for line in in_resconf[2:][:-1]:
resname = line[
0:
8] # python-ranges are inclusive the first index and exclusive the second...
atname = line[8:15]
atomnr = int(line[15:20])
x = float(line[20:28])
y = float(line[28:36])
z = float(line[36:44])
if atomnr in ndx_atoms:
# Update to new coords
x = pathpoint[cvpos]
y = pathpoint[cvpos + 1]
z = pathpoint[cvpos + 2]
cvpos += 3
# Write out the row, updated or not
rep_resconf.write('%s%s%5d%8.3f%8.3f%8.3f\n' %
(resname, atname, atomnr, x, y, z))
# Copy the last row which was the cell dimensions
rep_resconf.write(in_resconf[len(in_resconf) - 1])
else:
for chain in range(Nchains):
with open('res_%d_chain_%d.itp' % (k, chain),
'w') as restraint_itp:
with open(includes[k][chain], 'r') as in_itpf:
in_itp = in_itpf.read()
moltop = in_itp.split('[ dihedral_restraints ]')[0]
restraint_itp.write('%s' % moltop)
sys.stderr.write(
"Writing restraints for stringpoint %d chain %d\n" %
(k, chain))
# Note: this format is for Gromacs 4.6+
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write(
"; ai aj ak al type phi dphi kfac phiB dphiB kfacB\n"
)
pathpoint = adjusted[k] # just a list of phi/psi angles
if Nchains == 1:
protein = molecule(top)
else:
protein = molecule('%s' % includes[k][chain])
# Create a lookup-table for the protein topology that maps residue to dihedrally relevant
# backbone atom indices for N, CA and C.
dih_atoms = {}
for a in protein:
if (a.atomname == 'CA' or a.atomname == 'N'
or a.atomname == 'C'):
try:
dih_atoms[a.resnr][a.atomname] = a.atomnr
except KeyError:
dih_atoms[a.resnr] = {a.atomname: a.atomnr}
# Use the lookup-table built above and get the dihedral specification atoms needed for each
# residue in the selection. This is O(n) in residues, thanks to the dih_atoms table.
pos = 0
for r in rsel:
# Get the atom numbers to use for the phi and psi dihedrals (4 atoms each)
# phi is C on the previous residue, and N, CA, C on this
phi = [
dih_atoms[r - 1]['C'], dih_atoms[r]['N'],
dih_atoms[r]['CA'], dih_atoms[r]['C']
]
# psi is N, CA and C on this residue and N on the next
psi = [
dih_atoms[r]['N'], dih_atoms[r]['CA'],
dih_atoms[r]['C'], dih_atoms[r + 1]['N']
]
# get phi and psi values from the reparametrization vector
phi_val = pathpoint[pos + chain]
psi_val = pathpoint[pos + chain + 1]
# Go to the next residue (phi,phi vals * number of chains apart)
pos += 2 * Nchains
# write phi, psi angles and k-factor
# Note: in the Gromacs 4.6+ format, the k-factor is here. Before, it was in the .mdp as
# dihre_fc.
# Since we need different force constants in different stages, we need to put
# a searchable placeholder in the file here and replace it later
restraint_itp.write(
"%5d%5d%5d%5d%5d %8.4f%5d KFAC\n" %
(phi[0], phi[1], phi[2], phi[3], 1, phi_val, 0))
restraint_itp.write(
"%5d%5d%5d%5d%5d %8.4f%5d KFAC\n" %
(psi[0], psi[1], psi[2], psi[3], 1, psi_val, 0))
def reparametrize(diheds, selection, start_conf, start_xvg, end_conf, end_xvg, top):
Nswarms = len(diheds[0])
rsel = res_selection.res_select('%s'%start_conf,'%s'%selection)
# calculate average drift in collective variables space
sys.stderr.write('Residue selection: %s' %rsel)
newpts = []
for interp in range(len(diheds)):
avg = []
for r in rsel:
driftList = []
for i in range(len(diheds[interp])):
vec=[]
xvg = open(diheds[interp][i],'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
vec+=[phi_val,psi_val]
driftList.append(vec)
# driftList has phi,psi values for residue in every swarm
driftdat=open('dihedrals%d.dat'%interp,'w')
for pt in driftList:
driftdat.write('%f %f\n'%(pt[0],pt[1]))
avg+=[scale((1/float(Nswarms)),reduce(mapadd,driftList))]
newpts+=avg
# extract initial and target dihedral values
initpt = []
for r in rsel:
xvg = open(start_xvg,'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
initpt+=[phi_val,psi_val]
targetpt = []
for r in rsel:
xvg = open(end_xvg,'r')
for line in xvg:
if re.search(r'\-%d\n'%r,line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
targetpt+=[phi_val,psi_val]
# something with 1 indexing makes this padding necessary.
paddingpt=[0]*len(initpt)
newpts.insert(0,initpt)
newpts.append(targetpt)
newpts.append(paddingpt)
sys.stderr.write('The new list of points is: %s\n' %newpts)
for pt in newpts:
sys.stderr.write('%s %s\n'%(pt[0],pt[1]))
adjusted=rep_pts(newpts)
# TODO implement a dist_treshold=1.0
iters=[adjusted]
for i in range(100):
iters.append(rep_pts(iters[i]))
adjusted=iters[-1]
# delete the padding point
adjusted=adjusted[:-1]
sys.stderr.write('The adjusted points are:\n')
for pt in adjusted:
sys.stderr.write('%s %s\n'%(pt[0],pt[1]))
# calculate reparam distance
# TODO measure the distance between the reparametrized points and the input points
# write the topology for the next iteration
# treat the reparam values as a stack
# temporary additional restraints for alanine dipeptide
theta_val=[1.6, 1.48, 1.36, 1.24, 1.12, 1.0, 0.8799999999999999, 0.7599999999999999, 0.6399999999999999, 0.5199999999999998, 0.3999999999999999, 0.2799999999999998, 0.1599999999999997, 0.039999999999999813, -0.0800000000000003, -0.20000000000000018, -0.3200000000000003, -0.4400000000000004, -0.5600000000000005, -0.8]
zeta_val=[-4.3, -3.8, -3.3, -2.8, -2.3, -1.7999999999999998, -1.2999999999999998, -0.7999999999999998, -0.2999999999999998, 0.20000000000000018, 0.7000000000000002, 1.2000000000000002, 1.7000000000000002, 2.2, 2.7, 3.2, 3.7, 4.2, 4.7, 5.7]
top=open(top,'r').read().split('#include dihedral_restraints')
for k in range(1,len(adjusted)-1):
newtop=open('%d.top'%k,'w')
newtop.write('%s'%top[0])
sys.stderr.write("Writing restraints for interpolant index %i\n" %k)
newtop.write("[ dihedral_restraints ]\n")
newtop.write("; ai aj ak al type label phi dphi kfac power\n")
stack=adjusted[k]
protein = res_selection.protein('%s'%start_conf)
for r in rsel:
# there may be multiple residues matching the resnr, e.g., dimers
phi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'CA' or a.atomname == 'N' or a.atomname == 'C')) or
(a.resnr == int(r)-1 and a.atomname == 'C')]
psi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'N' or a.atomname == 'CA' or a.atomname == 'C')) or
(a.resnr == int(r)+1 and a.atomname == 'N')]
# get phi and psi values from the reparametrization vector
numres = len(phi)/4
for i in range(numres):
phi_val=stack[i]
psi_val=stack[i+1]
# write phi, psi angles
# TODO EXPLICIT DIHEDRALS FOR ALANINE DIPEPTIDE
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(5,7,9,15,1,1,phi_val,0,1,2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(7,9,15,17,1,1,psi_val,0,1,2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(1,5,7,9,1,1,theta_val[k],0,1,2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(9,15,17,19,1,1,zeta_val[k],0,1,2))
#newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(phi[i*4].atomnr,phi[i*4+1].atomnr,
# phi[i*4+2].atomnr,phi[i*4+3].atomnr,1,1,phi_val,0,1,2))
#newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(psi[i*4].atomnr,psi[i*4+1].atomnr,
# psi[i*4+2].atomnr,psi[i*4+3].atomnr,1,1,psi_val,0,1,2))
# delete the already added values from the stack
stack = stack[numres*2-1:]
newtop.write('%s'%top[1])
def write_restraints(start, end, start_xvg, end_xvg, top, includes, n, ndx,
Nchains):
start_xvg = open(start_xvg, 'r').readlines()
end_xvg = open(end_xvg, 'r').readlines()
selection = res_selection.res_select(start, ndx)
n = int(n)
# create the path
startpts = {}
endpts = {}
for r in selection:
startpts[r] = []
chain = 0
for line in start_xvg:
if re.search(r'\-%s$' % r, line):
startpts[r].append(
[float(line.split()[0]),
float(line.split()[1])])
chain += 1
for r in selection:
endpts[r] = []
chain = 0
for line in end_xvg:
if re.search(r'\-%s$' % r, line):
endpts[r].append(
[float(line.split()[0]),
float(line.split()[1])])
chain += 1
sys.stderr.write('%s' % includes)
for k in range(1, n - 1):
in_top = open(top).read()
for mol in range(Nchains):
if len(includes) > 0:
includename = includes[mol].split('/')[-1]
in_top = re.sub(includename,
'dihre_%d_chain_%d.itp' % (k, mol), in_top)
out_top = open('topol_%d.top' % k, 'w')
# sys.stderr.write('%s'%in_top)
out_top.write(in_top)
for k in range(1, n - 1):
# make the directory for the restraints
for mol in range(Nchains):
restraint_itp = open('dihre_%d_chain_%d.itp' % (k, mol), 'w')
if Nchains > 1:
moltop = open(includes[mol]).read()
restraint_itp.write(moltop)
# write the initial part of the topology file
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al phi dphi kfac\n")
if len(includes) > 0:
protein = molecule(includes[mol])
# replace the chain names with the chain names
else:
out_top = open('topol_%d.top' % k, 'w')
protein = molecule(top)
in_itp = open(
top, 'r').read().split('; Include Position restraint file')
out_top.write(in_itp[0])
out_top.write('#include "dihre_%d_chain_%d.itp"\n' % (k, mol))
#out_top.write('#include "dihre_%d_chain_%d.itp"\n'%(k,mol))
out_top.write(in_itp[1])
out_top.close()
for r in selection:
phi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'CA' or a.atomname
== 'N' or a.atomname == 'C')) or
(a.resnr == int(r) - 1 and a.atomname == 'C')
]
psi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'N' or a.atomname
== 'CA' or a.atomname == 'C'))
or (a.resnr == int(r) + 1 and a.atomname == 'N')
]
# write phi, psi angles
phi_val = startpts[r][mol][0] + (endpts[r][mol][0] -
startpts[r][mol][0]) / n * k
psi_val = startpts[r][mol][1] + (endpts[r][mol][1] -
startpts[r][mol][1]) / n * k
restraint_itp.write(
"%5d%5d%5d%5d %8.4f%5d%5d\n" %
(phi[0].atomnr, phi[1].atomnr, phi[2].atomnr,
phi[3].atomnr, phi_val, 0, 1))
restraint_itp.write(
"%5d%5d%5d%5d %8.4f%5d%5d\n" %
(psi[0].atomnr, psi[1].atomnr, psi[2].atomnr,
psi[3].atomnr, psi_val, 0, 1))
restraint_itp.close()
def reparametrize(diheds, selection, start_conf, start_xvg, end_conf, end_xvg,
top):
Nswarms = len(diheds[0])
rsel = res_selection.res_select('%s' % start_conf, '%s' % selection)
# calculate average drift in collective variables space
sys.stderr.write('Residue selection: %s' % rsel)
newpts = []
for interp in range(len(diheds)):
avg = []
for r in rsel:
driftList = []
for i in range(len(diheds[interp])):
vec = []
xvg = open(diheds[interp][i], 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
vec += [phi_val, psi_val]
driftList.append(vec)
# driftList has phi,psi values for residue in every swarm
avg += [scale((1 / float(Nswarms)), reduce(mapadd, driftList))]
newpts += avg
# extract initial and target dihedral values
initpt = []
for r in rsel:
xvg = open(start_xvg, 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
initpt += [phi_val, psi_val]
targetpt = []
for r in rsel:
xvg = open(end_xvg, 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
targetpt += [phi_val, psi_val]
# something with 1 indexing makes this padding necessary.
paddingpt = [0] * len(initpt)
newpts.insert(0, initpt)
newpts.append(targetpt)
newpts.append(paddingpt)
sys.stderr.write('The new list of points is: %s\n' % newpts)
for pt in newpts:
sys.stderr.write('%s %s\n' % (pt[0], pt[1]))
adjusted = rep_pts(newpts)
# TODO implement a dist_treshold=1.0
iters = [adjusted]
for i in range(100):
iters.append(rep_pts(iters[i]))
adjusted = iters[-1]
# delete the padding point
adjusted = adjusted[:-1]
sys.stderr.write('The adjusted points are:\n')
for pt in adjusted:
sys.stderr.write('%s %s\n' % (pt[0], pt[1]))
# calculate reparam distance
# TODO measure the distance between the reparametrized points and the input points
# write the topology for the next iteration
# treat the reparam values as a stack
for k in range(1, len(adjusted) - 1):
for chain in range(Nchains):
restraint_itp = open('topol_%d_chain_%d.top' % (k, chain), 'w')
in_itp = open(include[k][chain], 'w')
moltop = restraint_itp.split('[ dihedral_restraints ]')[0]
restraint_itp.write('%s' % moltop)
sys.stderr.write(
"Writing restraints for interpolant point %d chain %d\n" %
(k, chain))
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write(
"; ai aj ak al type label phi dphi kfac power\n")
pathpoint = adjusted[k] # just a list of phi/psi angles
protein = molecule('%s' % include[k][chain])
# keep track of the position in the path point
pos = 0
for r in rsel:
# there may be multiple residues matching the resnr, e.g., dimers
phi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'CA' or a.atomname
== 'N' or a.atomname == 'C')) or
(a.resnr == int(r) - 1 and a.atomname == 'C')
]
psi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'N' or a.atomname
== 'CA' or a.atomname == 'C'))
or (a.resnr == int(r) + 1 and a.atomname == 'N')
]
# get phi and psi values from the reparametrization vector
phi_val = stack[pos + chain]
psi_val = stack[pos + chain + 1]
# write phi, psi angles
restraint_itp.write(
"%5d%5d%5d%5d%5d%5d %8.4f%5d%5d%5d\n" %
(phi[0], phi[1], phi[2], phi[3], 1, 1, phi_val, 0, 1, 2))
restraint_itp.write(
"%5d%5d%5d%5d%5d%5d %8.4f%5d%5d%5d\n" %
(psi[0], psi[1], psi[2], psi[3], 1, 1, psi_val, 0, 1, 2))
#restraint_itp.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(phi[i*4].atomnr,phi[i*4+1].atomnr,
# phi[i*4+2].atomnr,phi[i*4+3].atomnr,1,1,phi_val,0,1,2))
#restraint_itp.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(psi[i*4].atomnr,psi[i*4+1].atomnr,
# psi[i*4+2].atomnr,psi[i*4+3].atomnr,1,1,psi_val,0,1,2))
# delete the already added values from the stack
pos += 2 * Nchains
restraint_itp.close()
def reparametrize(diheds, selection, start_conf, start_xvg, end_conf, end_xvg,
top):
Nswarms = len(diheds[0])
rsel = res_selection.res_select('%s' % start_conf, '%s' % selection)
# calculate average drift in collective variables space
sys.stderr.write('Residue selection: %s' % rsel)
newpts = []
for interp in range(len(diheds)):
avg = []
for r in rsel:
driftList = []
for i in range(len(diheds[interp])):
vec = []
xvg = open(diheds[interp][i], 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
vec += [phi_val, psi_val]
driftList.append(vec)
# driftList has phi,psi values for residue in every swarm
driftdat = open('dihedrals%d.dat' % interp, 'w')
for pt in driftList:
driftdat.write('%f %f\n' % (pt[0], pt[1]))
avg += [scale((1 / float(Nswarms)), reduce(mapadd, driftList))]
newpts += avg
# extract initial and target dihedral values
initpt = []
for r in rsel:
xvg = open(start_xvg, 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
initpt += [phi_val, psi_val]
targetpt = []
for r in rsel:
xvg = open(end_xvg, 'r')
for line in xvg:
if re.search(r'\-%d\n' % r, line):
phi_val = float(line.split()[0])
psi_val = float(line.split()[1])
targetpt += [phi_val, psi_val]
# something with 1 indexing makes this padding necessary.
paddingpt = [0] * len(initpt)
newpts.insert(0, initpt)
newpts.append(targetpt)
newpts.append(paddingpt)
sys.stderr.write('The new list of points is: %s\n' % newpts)
for pt in newpts:
sys.stderr.write('%s %s\n' % (pt[0], pt[1]))
adjusted = rep_pts(newpts)
# TODO implement a dist_treshold=1.0
iters = [adjusted]
for i in range(100):
iters.append(rep_pts(iters[i]))
adjusted = iters[-1]
# delete the padding point
adjusted = adjusted[:-1]
sys.stderr.write('The adjusted points are:\n')
for pt in adjusted:
sys.stderr.write('%s %s\n' % (pt[0], pt[1]))
# calculate reparam distance
# TODO measure the distance between the reparametrized points and the input points
# write the topology for the next iteration
# treat the reparam values as a stack
# temporary additional restraints for alanine dipeptide
theta_val = [
1.6, 1.48, 1.36, 1.24, 1.12, 1.0, 0.8799999999999999,
0.7599999999999999, 0.6399999999999999, 0.5199999999999998,
0.3999999999999999, 0.2799999999999998, 0.1599999999999997,
0.039999999999999813, -0.0800000000000003, -0.20000000000000018,
-0.3200000000000003, -0.4400000000000004, -0.5600000000000005, -0.8
]
zeta_val = [
-4.3, -3.8, -3.3, -2.8, -2.3, -1.7999999999999998, -1.2999999999999998,
-0.7999999999999998, -0.2999999999999998, 0.20000000000000018,
0.7000000000000002, 1.2000000000000002, 1.7000000000000002, 2.2, 2.7,
3.2, 3.7, 4.2, 4.7, 5.7
]
top = open(top, 'r').read().split('#include dihedral_restraints')
for k in range(1, len(adjusted) - 1):
newtop = open('%d.top' % k, 'w')
newtop.write('%s' % top[0])
sys.stderr.write("Writing restraints for interpolant index %i\n" % k)
newtop.write("[ dihedral_restraints ]\n")
newtop.write(
"; ai aj ak al type label phi dphi kfac power\n")
stack = adjusted[k]
protein = res_selection.protein('%s' % start_conf)
for r in rsel:
# there may be multiple residues matching the resnr, e.g., dimers
phi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'CA' or a.atomname ==
'N' or a.atomname == 'C')) or
(a.resnr == int(r) - 1 and a.atomname == 'C')
]
psi = [
a for a in protein
if (a.resnr == int(r) and (a.atomname == 'N' or a.atomname ==
'CA' or a.atomname == 'C')) or
(a.resnr == int(r) + 1 and a.atomname == 'N')
]
# get phi and psi values from the reparametrization vector
numres = len(phi) / 4
for i in range(numres):
phi_val = stack[i]
psi_val = stack[i + 1]
# write phi, psi angles
# TODO EXPLICIT DIHEDRALS FOR ALANINE DIPEPTIDE
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n" %
(5, 7, 9, 15, 1, 1, phi_val, 0, 1, 2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n" %
(7, 9, 15, 17, 1, 1, psi_val, 0, 1, 2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n" %
(1, 5, 7, 9, 1, 1, theta_val[k], 0, 1, 2))
newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n" %
(9, 15, 17, 19, 1, 1, zeta_val[k], 0, 1, 2))
#newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(phi[i*4].atomnr,phi[i*4+1].atomnr,
# phi[i*4+2].atomnr,phi[i*4+3].atomnr,1,1,phi_val,0,1,2))
#newtop.write("%5d%5d%5d%5d%5d%5d%8.4f%5d%5d%5d\n"%(psi[i*4].atomnr,psi[i*4+1].atomnr,
# psi[i*4+2].atomnr,psi[i*4+3].atomnr,1,1,psi_val,0,1,2))
# delete the already added values from the stack
stack = stack[numres * 2 - 1:]
newtop.write('%s' % top[1])
def write_restraints(inp, initial_confs, start, end, start_xvg, end_xvg, tpr, top, includes, n, ndx_file, Nchains):
cmdnames = cmds.GromacsCommands()
# Get the atoms involved with the residues to use for dihedrals (might be more than one atom in the index
# per residue, since it's probably generated by make_ndx)
ndx_atoms = res_selection.read_ndx(ndx_file)
# Map them to each affected residue so we just get the residue numbers back
selection = res_selection.res_select(start, ndx_atoms)
n = int(n) # number of points in the string, including start and end point
use_interpolation = False
if initial_confs is None or len(initial_confs) == 0:
use_interpolation = True
# Read the starting and ending dihedrals for later interpolation
startpts = readxvg.readxvg(start_xvg, selection)
endpts = readxvg.readxvg(end_xvg, selection)
else:
# Have to generate the dihedrals ourselves from the given initial structures
# Note: when we get an initial_confs[] array, we use it for all points and
# the start/end input parameters are completely ignored
# TODO: assert that len(initial_confs) == n otherwise?
ramaprocs = {}
# Run g_rama (in parallel) on each structure and output to a temporary .xvg
FNULL = open(os.devnull, 'w') # dont generate spam from g_rama
for i in range(n):
# TODO: check for and use g_rama_mpi.. like everywhere else
cmd = cmdnames.rama.split() + ['-f', initial_confs[i], '-s', tpr,
'-o', '0%3d.xvg' % i]
ramaprocs[i] = Popen(cmd, stdout=FNULL, stderr=FNULL)
# Go through the output from the rama sub-processes and read the xvg outputs
stringpts = {} # Will have 4 levels: stringpoint, residue, chain, phi/psi value
for i in range(n):
# Start array indexed by residue
xvg_i = os.path.join(inp.getOutputDir(), '0%3d.xvg' % i)
# Make sure the corresponding g_rama task has ended
ramaprocs[i].communicate()
# Read back and parse like for the start/end_xvg above
stringpts[i] = readxvg.readxvg(xvg_i, selection)
# Rewrite the topology to include the res itp files instead of the original per-chain itps (if any)
# There will be one topol_x.top per string point
sys.stderr.write('%s' % includes)
for k in range(n):
with open(top) as in_topf:
in_top = in_topf.read()
for mol in range(Nchains):
if len(includes) > 0:
includename = includes[mol].split('/')[-1]
in_top = re.sub(includename, 'res_%d_chain_%d.itp' % (k, mol), in_top)
with open('topol_%d.top' % k,'w') as out_top:
# sys.stderr.write('%s'%in_top)
out_top.write(in_top)
# Generate/copy and write-out the dihedrals for each point
for k in range(n):
for mol in range(Nchains):
# TODO: use with statement for restraint_itp as well
restraint_itp = open('res_%d_chain_%d.itp' % (k, mol), 'w')
if Nchains > 1:
with open(includes[mol]) as moltop_f:
moltop = moltop_f.read()
restraint_itp.write(moltop)
# write the initial part of the topology file
# Note: gromacs 4.6+ required
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al type phi dphi kfac\n")
if len(includes) > 0:
protein = molecule(includes[mol])
# replace the chain names with the chain names
else:
with open('topol_%d.top' % k, 'w') as out_top:
protein = molecule(top)
with open(top,'r') as in_itp_f:
in_itp = in_itp_f.read().split('; Include Position restraint file')
out_top.write(in_itp[0])
out_top.write('#include "res_%d_chain_%d.itp"\n' % (k, mol))
out_top.write(in_itp[1])
# Create a lookup-table for the protein topology that maps residue to dihedrally relevant
# backbone atom indices for N, CA and C.
dih_atoms = {}
for a in protein:
if (a.atomname == 'CA' or a.atomname == 'N' or a.atomname == 'C'):
try:
dih_atoms[a.resnr][a.atomname] = a.atomnr;
except KeyError:
dih_atoms[a.resnr] = { a.atomname: a.atomnr }
# Use the lookup-table built above and get the dihedral specification atoms needed for each
# residue in the selection. This is O(n) in residues, thanks to the dih_atoms table.
for r in selection:
# Get the atom numbers to use for the phi and psi dihedrals (4 atoms each)
# phi is C on the previous residue, and N, CA, C on this
phi = [ dih_atoms[r - 1]['C'], dih_atoms[r]['N'], dih_atoms[r]['CA'], dih_atoms[r]['C'] ]
# psi is N, CA and C on this residue and N on the next
psi = [ dih_atoms[r]['N'], dih_atoms[r]['CA'], dih_atoms[r]['C'], dih_atoms[r + 1]['N'] ]
# Write phi, psi angles and the associated k factor into a row in the restraint file
# Note: in the Gromacs 4.6+ format, the k-factor is here. Before, it was in the .mdp as
# dihre_fc.
# Also see reparametrize.py
if use_interpolation:
# k is from 0 to n-1, so map it so we get a factor from 0 to 1
phi_val = startpts[r][mol][0] + k * (endpts[r][mol][0] - startpts[r][mol][0]) / (n - 1)
psi_val = startpts[r][mol][1] + k * (endpts[r][mol][1] - startpts[r][mol][1]) / (n - 1)
else:
# Use the values extracted from the initial_confs[] structures above
phi_val = stringpts[k][r][mol][0]
psi_val = stringpts[k][r][mol][1]
# Since we need different force constants in different stages, we need to put
# a searchable placeholder in the file here and replace it later. KFAC is normally
# a %8.4f number.
restraint_itp.write("%5d%5d%5d%5d%5d %8.4f%5d KFAC\n"
%(phi[0], phi[1], phi[2], phi[3], 1, phi_val, 0))
restraint_itp.write("%5d%5d%5d%5d%5d %8.4f%5d KFAC\n"
%(psi[0], psi[1], psi[2], psi[3], 1, psi_val, 0))
restraint_itp.close()
def write_restraints(start, end, start_xvg, end_xvg, top, includes, n, ndx, Nchains):
start_xvg=open(start_xvg,'r').readlines()
end_xvg=open(end_xvg,'r').readlines()
selection=res_selection.res_select(start,ndx)
n=int(n)
# create the path
startpts={}
endpts={}
for r in selection:
startpts[r]=[]
chain=0
for line in start_xvg:
if re.search(r'\-%s$'%r,line):
startpts[r].append([float(line.split()[0]),float(line.split()[1])])
chain+=1
for r in selection:
endpts[r]=[]
chain=0
for line in end_xvg:
if re.search(r'\-%s$'%r,line):
endpts[r].append([float(line.split()[0]),float(line.split()[1])])
chain+=1
sys.stderr.write('%s'%includes)
for k in range(1,n-1):
in_top=open(top).read()
for mol in range(Nchains):
if len(includes)>0:
includename=includes[mol].split('/')[-1]
in_top=re.sub(includename,'dihre_%d_chain_%d.itp'%(k,mol),in_top)
out_top=open('topol_%d.top'%k,'w')
# sys.stderr.write('%s'%in_top)
out_top.write(in_top)
for k in range(1,n-1):
# make the directory for the restraints
for mol in range(Nchains):
restraint_itp=open('dihre_%d_chain_%d.itp'%(k,mol),'w')
if Nchains>1:
moltop=open(includes[mol]).read()
restraint_itp.write(moltop)
# write the initial part of the topology file
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al phi dphi kfac\n")
if len(includes)>0:
protein=molecule(includes[mol])
# replace the chain names with the chain names
else:
out_top=open('topol_%d.top'%k,'w')
protein=molecule(top)
in_itp=open(top,'r').read().split('; Include Position restraint file')
out_top.write(in_itp[0])
out_top.write('#include "dihre_%d_chain_%d.itp"\n'%(k,mol))
#out_top.write('#include "dihre_%d_chain_%d.itp"\n'%(k,mol))
out_top.write(in_itp[1])
out_top.close()
for r in selection:
phi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'CA' or a.atomname == 'N' or a.atomname == 'C')) or
(a.resnr == int(r)-1 and a.atomname == 'C')]
psi = [a for a in protein if (a.resnr == int(r) and
(a.atomname == 'N' or a.atomname == 'CA' or a.atomname == 'C')) or
(a.resnr == int(r)+1 and a.atomname == 'N')]
# write phi, psi angles
phi_val=startpts[r][mol][0]+(endpts[r][mol][0]-startpts[r][mol][0])/n*k
psi_val=startpts[r][mol][1]+(endpts[r][mol][1]-startpts[r][mol][1])/n*k
restraint_itp.write("%5d%5d%5d%5d %8.4f%5d%5d\n"
%(phi[0].atomnr,phi[1].atomnr,phi[2].atomnr, phi[3].atomnr, phi_val, 0, 1))
restraint_itp.write("%5d%5d%5d%5d %8.4f%5d%5d\n"
%(psi[0].atomnr,psi[1].atomnr,psi[2].atomnr, psi[3].atomnr, psi_val, 0, 1))
restraint_itp.close()
import os
import argparse
import res_selection
parser = argparse.ArgumentParser()
parser.add_argument('-i',required=True, help='The initial .gro file')
parser.add_argument('-n',required=True, help='The number of interpolation steps')
parser.add_argument('-x',required=True, help='The desired index file (.ndx)')
parser.add_argument('-p',required=True, help='A topology file for the restraints, must contain the line "#include dihedral_restraints" where the restraints are to be written')
args = vars(parser.parse_args())
conf=args['i']
ndx=args['x']
n=int(args['n'])
top = open(args['p'],'r').read()
selection = res_selection.res_select(conf,ndx)
protein = res_selection.protein(conf)
top=top.split('#include dihedral_restraints')
print selection
theta_val=[1.6, 1.48, 1.36, 1.24, 1.12, 1.0, 0.8799999999999999, 0.7599999999999999, 0.6399999999999999, 0.5199999999999998, 0.3999999999999999, 0.2799999999999998, 0.1599999999999997, 0.039999999999999813, -0.0800000000000003, -0.20000000000000018, -0.3200000000000003, -0.4400000000000004, -0.5600000000000005, -0.8]
zeta_val=[-4.3, -3.8, -3.3, -2.8, -2.3, -1.7999999999999998, -1.2999999999999998, -0.7999999999999998, -0.2999999999999998, 0.20000000000000018, 0.7000000000000002, 1.2000000000000002, 1.7000000000000002, 2.2, 2.7, 3.2, 3.7, 4.2, 4.7, 5.7]
for k in range(1,n):
newtop=open('%s.top'%k,'w')
# write the initial part of the topology file
newtop.write('%s'%top[0])
xvg = open('%s.xvg'%k,'r').readlines()
#print "Writing restraints for interpolant number %i" %k
def reparametrize(
use_posres,
fix_endpoints,
cvs,
ndx_file,
Nchains,
start_conf,
start_xvg,
end_conf,
end_xvg,
last_resconfs,
top,
includes,
):
Nswarms = len(cvs[0])
ndx_atoms = res_selection.read_ndx(ndx_file)
# For dihedrals, we map the atoms to residues for a single chain, and the readxvg etc. will read the entire file and
# select the same residues in each chain. But for the position restraints which use the atom indices directly, we have
# to first expand the index so it covers all chains.
# TODO: have to figure out or input atoms per chain in the .gro's so we can repeat the atom-selection Nchains times
# for the posres case. The ndx file is for atoms inside the chain, but the .gro will contain global numbering.
# We can detect the chain-repeat in rwgro, by looking for repeating first residue name.
# Hardcode a repeat for testing for now.
if use_posres == 0:
# Map atoms to residues for the dihedral selection
rsel = res_selection.res_select("%s" % start_conf, ndx_atoms)
# sys.stderr.write('Residue selection: %s' %rsel)
# else:
# selected_atoms = []
# for ch in range(5):
# for i in range(len(ndx_atoms)):
# selected_atoms += [ ndx_atoms[i] + ch * 5566 ]
# Calculate the average drift in CV space
# newpts is a per-swarm-point list of CV points (each a list of the CV dimension length)
newpts = []
# Note: the cvs[][] array is indexed after the number of stringpoints that actually were swarm-processed,
# so depending on the fix_endpoints option it may or may not exactly match the path[] which always include
# all points. If we only read in N-2 points here, the start/end will be added to newpts in the code further below.
for pathpt in range(len(cvs)):
swarmpts = []
for i in range(len(cvs[pathpt])):
if use_posres == 1:
zpt = rwgro.readgro_flat(cvs[pathpt][i], ndx_atoms)
# sys.stderr.write('Read pathpt %d swarm %d (%s), got %d CVs\n' % (pathpt, i, cvs[pathpt][i], len(zpt)))
else:
zpt = readxvg.readxvg_flat(cvs[pathpt][i], rsel)
swarmpts.append(zpt)
zptsum = reduce(mapadd, swarmpts)
avgdrift = scale((1 / float(Nswarms)), zptsum)
newpts.append(avgdrift)
# Read in the fixed start and end CV values, for the fix_endpoints case (otherwise the start/end will
# be allowed to drift just like the other points, and they will already then be a part of the newpts array)
if fix_endpoints == 1:
if use_posres == 1:
# TODO: the start/end_conf are full Systems so the atom numbering aliases for the ndx_atoms array :/
# Currently fixed in readgro_flat temporary, hardcoded for the GLIC Protein number.
initpt = rwgro.readgro_flat(start_conf, ndx_atoms)
targetpt = rwgro.readgro_flat(end_conf, ndx_atoms)
else:
initpt = readxvg.readxvg_flat(start_xvg, rsel)
targetpt = readxvg.readxvg_flat(end_xvg, rsel)
sys.stderr.write("Length of initpt %d, targetpt %d\n" % (len(initpt), len(targetpt)))
# Insert the start/end in the beginning and last of newpts
newpts.insert(0, initpt)
newpts.append(targetpt)
# something with 1 indexing makes this padding necessary. TODO: check if this is needed anymore
paddingpt = [0] * len(newpts[0])
newpts.append(paddingpt)
# Do the actual reparameterization
# newpts is a 2D list, first level is one per stringpoint, second is the linear list of CVs
# rep_pts returns the maximum spread of the CV distances between points in [0] and the adjusted
# points in [1]
# Initial iteration
rep_it1 = ext_rep_pts(newpts)
adjusted = rep_it1[1] # get the points only, ignore the spread result
# Keep iterating, feeding the result of the previous result into rep_pts again
# Note that with long CV vectors (> 4000 dimensions) iterations takes a long time
# (at least 45 min for 25 iterations on a single-core 3.5 GHz) when using the python rep_pts.
# We can abort early when the maximum spread between points in the updated string goes
# below a threshold
iters = [adjusted]
i = 0
maxspread = 100.0
# Do max 150 iterations even if we don't reach our goal
while i < 150 and maxspread > 0.012:
sys.stderr.write("Rep iter %d: \n" % i)
sys.stderr.flush()
rep_it = ext_rep_pts(iters[i])
maxspread = rep_it[0]
sys.stderr.write(" maxspread was %f\n" % maxspread)
# Remember the adjusted points
iters.append(rep_it[1])
i = i + 1
sys.stderr.write("Final maximum spread %f after %d iterations.\n" % (maxspread, i))
# Get the final iteration's result
adjusted = iters[-1]
# delete the padding point
adjusted = adjusted[:-1]
newpts = newpts[:-1]
# sys.stderr.write('Pts before repa:\n %s\n' % newpts)
# sys.stderr.write('The adjusted pts:\n %s\n' % adjusted)
# Possibility to test skipping reparametrize by uncommenting the next row.
# The stringpoints will drift along the string and probably end up in the
# endpoints or a minima along the string.
# adjusted = newpts
# calculate reparam distance
sys.stderr.write("Length of the adjusted vector: %d\n" % len(adjusted))
# TODO Nchains should depend on the specific residue (?)
# Given as function argument now.
# Nchains = len(initpt) / (2 * len(rsel))
# write the CV control data for the next iteration
# The output file expected for the posres case is rep_resconf_%d.gro for each stringpoint.
# For dihedrals its res_%d_chain_%d.itp for each stringpoint and chain.
#
for k in range(len(adjusted)):
# Not necessary to do this output for the start/end-points in the fix_endpoints case, the data is
# just bypassed in the caller script
if fix_endpoints == 1 and (k == 0 or k == (len(adjusted) - 1)):
continue
if use_posres == 1:
# Open the output resconf which will go into the next iteration as minimization target
with open("rep_resconf_%d.gro" % k, "w") as rep_resconf:
# Open and read the previous (input) resconf, which has basically tagged along since the last
# reparametrization step (or was set initially at swarm-start)
with open(last_resconfs[k], "r") as in_resconf_f:
in_resconf = in_resconf_f.readlines()
# TODO: maybe this chunk of code could be done by the rwgro module for us.
# Copy the first 2 rows (title and number of atoms) straight over
rep_resconf.write(in_resconf[0])
rep_resconf.write(in_resconf[1])
# Go through the atoms row-by-row and update the xyz coordinates for the atoms the reparametrize
# step moved
# Note: we are only copying over positions here. The velocities are not needed as the use for these files
# will only be as a base for the next iterations position restraint coordinates.
pathpoint = adjusted[k] # the 1-D list of CVs (positions): x,y,z * nbr atoms in index
if len(pathpoint) != (1555 * 3): # assert on GLIC length (TODO)
sys.stderr.write("adjusted[] entry of wrong length %d\n" % len(pathpoint))
cvpos = 0
for line in in_resconf[2:][:-1]:
resname = line[0:8] # python-ranges are inclusive the first index and exclusive the second...
atname = line[8:15]
atomnr = int(line[15:20])
x = float(line[20:28])
y = float(line[28:36])
z = float(line[36:44])
if atomnr in ndx_atoms:
# Update to new coords
x = pathpoint[cvpos]
y = pathpoint[cvpos + 1]
z = pathpoint[cvpos + 2]
cvpos += 3
# Write out the row, updated or not
rep_resconf.write("%s%s%5d%8.3f%8.3f%8.3f\n" % (resname, atname, atomnr, x, y, z))
# Copy the last row which was the cell dimensions
rep_resconf.write(in_resconf[len(in_resconf) - 1])
else:
for chain in range(Nchains):
with open("res_%d_chain_%d.itp" % (k, chain), "w") as restraint_itp:
with open(includes[k][chain], "r") as in_itpf:
in_itp = in_itpf.read()
moltop = in_itp.split("[ dihedral_restraints ]")[0]
restraint_itp.write("%s" % moltop)
sys.stderr.write("Writing restraints for stringpoint %d chain %d\n" % (k, chain))
# Note: this format is for Gromacs 4.6+
restraint_itp.write("[ dihedral_restraints ]\n")
restraint_itp.write("; ai aj ak al type phi dphi kfac phiB dphiB kfacB\n")
pathpoint = adjusted[k] # just a list of phi/psi angles
if Nchains == 1:
protein = molecule(top)
else:
protein = molecule("%s" % includes[k][chain])
# Create a lookup-table for the protein topology that maps residue to dihedrally relevant
# backbone atom indices for N, CA and C.
dih_atoms = {}
for a in protein:
if a.atomname == "CA" or a.atomname == "N" or a.atomname == "C":
try:
dih_atoms[a.resnr][a.atomname] = a.atomnr
except KeyError:
dih_atoms[a.resnr] = {a.atomname: a.atomnr}
# Use the lookup-table built above and get the dihedral specification atoms needed for each
# residue in the selection. This is O(n) in residues, thanks to the dih_atoms table.
pos = 0
for r in rsel:
# Get the atom numbers to use for the phi and psi dihedrals (4 atoms each)
# phi is C on the previous residue, and N, CA, C on this
phi = [dih_atoms[r - 1]["C"], dih_atoms[r]["N"], dih_atoms[r]["CA"], dih_atoms[r]["C"]]
# psi is N, CA and C on this residue and N on the next
psi = [dih_atoms[r]["N"], dih_atoms[r]["CA"], dih_atoms[r]["C"], dih_atoms[r + 1]["N"]]
# get phi and psi values from the reparametrization vector
phi_val = pathpoint[pos + chain]
psi_val = pathpoint[pos + chain + 1]
# Go to the next residue (phi,phi vals * number of chains apart)
pos += 2 * Nchains
# write phi, psi angles and k-factor
# Note: in the Gromacs 4.6+ format, the k-factor is here. Before, it was in the .mdp as
# dihre_fc.
# Since we need different force constants in different stages, we need to put
# a searchable placeholder in the file here and replace it later
restraint_itp.write(
"%5d%5d%5d%5d%5d %8.4f%5d KFAC\n" % (phi[0], phi[1], phi[2], phi[3], 1, phi_val, 0)
)
restraint_itp.write(
"%5d%5d%5d%5d%5d %8.4f%5d KFAC\n" % (psi[0], psi[1], psi[2], psi[3], 1, psi_val, 0)
)