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.

Note that this script if run multiple times will produce the same model each time, because Modeller is deterministic. If you want to build multiple models, change the value of rand_seed (see comments in the script) each time. This may be useful if some models, for example, cannot be optimized due to steric clashes.

import sys
import os

from modeller import *
from modeller.optimizers import MolecularDynamics, ConjugateGradients
from modeller.automodel import autosched

#     Usage:   python modelname respos resname chain > logfile
#     Example: python 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.
#  Note: if the model has no chain identifier, specify "" for the chain argument.

def optimize(atmsel, sched):
    #conjugate gradient
    for step in sched:
        step.optimize(atmsel, max_iterations=200, min_atom_shift=0.001)
    cg = ConjugateGradients()
    cg.optimize(atmsel, max_iterations=200, min_atom_shift=0.001)

#molecular dynamics
def refine(atmsel):
    # at T=1000, max_atom_shift for 4fs is cca 0.15 A.
    md = MolecularDynamics(cap_atom_shift=0.39, md_time_step=4.0,
    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:
            md.optimize(atmsel, 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
   s = Selection(mdl1)
   for typ in ('stereo', 'phi-psi_binormal'):
       rsr.make(s, restraint_type=typ, aln=aln, spline_on_site=True)
   for typ in ('omega', 'chi1', 'chi2', 'chi3', 'chi4'):
       rsr.make(s, restraint_type=typ+'_dihedral', spline_range=4.0,
                spline_dx=0.3, spline_min_points = 5, aln=aln,

#first argument
modelname, respos, restyp, chain, = sys.argv[1:]


# Set a different value for rand_seed to get a different final model
env = Environ(rand_seed=-49837) = True
#soft sphere potential
#lennard-jones potential (more accurate)
env.edat.contact_shell = 4.0
env.edat.update_dynamic = 0.39

# Read customized topology file with phosphoserines (or standard one)'$(LIB)/top_heav.lib')

# Read customized CHARMM parameter library with phosphoserines (or standard one)'$(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
s = Selection(mdl1.chains[chain].residues[respos])

#perform the mutate residue operation
#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

# 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

# Build the remaining unknown coordinates, 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"

#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).


#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

sched = autosched.loop.make_for_model(mdl1)

#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
s = Selection(mdl1.chains[chain].residues[respos])



optimize(s, sched)

#feels environment (energy computed on pairs that have at least one member
#in the selected)
optimize(s, sched)

#give a proper name

#delete the temporary file