The script below takes a given PDB file, and mutates a single residue. The residue's position is then optimized, and the unoptimized and optimized energies are reported.
#!python
import sys
import os
#
# mutate_model.py
#
# Usage: modCVS - < mutate_model.py modelname respos resname chain > logfile
#
# Example: modCVS - < mutate_model.py 1t29 1699 LEU A > 1t29.log
#
#
# Creates a single in silico point mutation to sidechain type and at residue position
# input by the user, in the structure whose file is modelname.pdb
# The conformation of the mutant sidechain is optimized by conjugate gradient and
# refined using some MD.
#
def optimize(mdl1):
#conjugate gradient
for step in range(0,len(mdl1.schedule)):
mdl1.schedule.step = step + 1
mdl1.optimize(optimization_method=1,max_iterations=200,min_atom_shift=0.001)
#md
refine(mdl1)
mdl1.optimize(optimization_method=1,max_iterations=200,min_atom_shift=0.001)
#molecular dynamics
def refine(mdl1):
# at T=1000, max_atom_shift for 4fs is cca 0.15 A.
init_vel = True
for (its, equil, temps) in ((200, 20, (150.0, 250.0, 400.0, 700.0, 1000.0)),
(200, 600, (1000.0, 800.0, 600.0, 500.0, 400.0, 300.0))):
for temp in temps:
mdl1.optimize(cap_atom_shift=0.39, md_time_step=4.0, optimization_method=3,
md_return='FINAL', init_velocities=init_vel, temperature=temp,
max_iterations=its, equilibrate=equil)
init_vel = False
#use homologs and dihedral library for dihedral angle restraints
def make_restraints(mdl1, aln):
rsr = mdl1.restraints
rsr.clear()
for typ in ('stereo', 'phi-psi_binormal'):
rsr.make(restraint_type=typ, aln=aln, spline_on_site=True)
for typ in ('omega', 'chi1', 'chi2', 'chi3', 'chi4'):
rsr.make(restraint_type=typ+'_dihedral', spline_range=4.0, spline_dx=0.3,
spline_min_points = 5, aln=aln, spline_on_site=True)
#first argument
modelname, respos, restyp, chain, = sys.argv[1:]
log.verbose()
env = environ(rand_seed=-49837)
env.io.hetatm = True
#soft sphere potential
env.edat.dynamic_sphere=False
#lennard-jones potential (more accuate)
env.edat.dynamic_lennard=True
env.edat.contact_shell = 4.0
env.edat.update_dynamic = 0.39
# Read customized topology file with phosphoserines (or standard one)
env.libs.topology.read(file='$(LIB)/top_heav.lib')
# Read customized CHARMM parameter library with phosphoserines (or standard one)
env.libs.parameters.read(file='$(LIB)/par.lib')
# Read the original PDB file and copy its sequence to the alignment array:
mdl1 = model(env, file=modelname)
ali = alignment(env)
ali.append_model(mdl1, atom_files=modelname, align_codes=modelname)
#set up the mutate residue selection segment
mdl1.pick_atoms(pick_atoms_set=1, selection_from ='ALL', res_types ='ALL',selection_segment = (respos+':'+chain, respos+':'+chain), atom_types = 'ALL', selection_status = 'INITIALIZE')
#perform the mutate residue operation
mdl1.mutate(residue_type=restyp)
#get two copies of the sequence. A modeller trick to get things set up
ali.append_model(mdl1, align_codes=modelname)
# Generate molecular topology for mutant
mdl1.generate_topology(ali, sequence=modelname)
# Transfer all the coordinates you can from the template native structure
# to the mutant (this works even if the order of atoms in the native PDB
# file is not standard):
#here we are generating the model by reading the template coordinates
mdl1.transfer_xyz(ali)
# Build the remaining unknown coordinates
mdl1.build(initialize_xyz=False, build_method='INTERNAL_COORDINATES')
#yes model2 is the same file as model1. It's a modeller trick.
mdl2 = model(env, file=modelname)
#required to do a transfer_res_numb
#ali.append_model(mdl2, atom_files=modelname, align_codes=modelname)
#transfers from "model 2" to "model 1"
mdl1.res_num_from(mdl2,ali)
#It is usually necessary to write the mutated sequence out and read it in before proceeding, because not all sequence related information about MODEL is changed by this command (e.g., internal coordinates, charges, and atom types and radii are not updated).
mdl1.write(file=modelname+restyp+respos+'.tmp')
mdl1.read(file=modelname+restyp+respos+'.tmp')
#set up restraints before computing energy
#we do this a second time because the model has been written out and read in, clearing the previously set restraints
make_restraints(mdl1, ali)
#a non-bonded pair has to have at least as many selected atoms
mdl1.env.edat.nonbonded_sel_atoms=1
mdl1.schedule.make(library_schedule=6)
#only optimize the selected residue (in first pass, just atoms in selected residue, in second pass, include nonbonded neighboring atoms)
#set up the mutate residue selection segment
mdl1.pick_atoms(pick_atoms_set=1, selection_from ='ALL', res_types ='ALL',selection_segment = (respos+':'+chain, respos+':'+chain), atom_types = 'ALL', selection_status = 'INITIALIZE')
mdl1.restraints.unpick_all()
mdl1.restraints.pick()
mdl1.energy()
mdl1.randomize_xyz(deviation=4.0)
mdl1.env.edat.nonbonded_sel_atoms=2
optimize(mdl1)
#feels environment (energy computed on pairs that have at least one member in the selected)
mdl1.env.edat.nonbonded_sel_atoms=1
optimize(mdl1)
mdl1.energy()
#give a proper name
mdl1.write(file=modelname+restyp+respos+'.pdb')
#delete the temporary file
os.remove(modelname+restyp+respos+'.tmp');