Questions of Cartesian_ddG calculation in PyRosetta

Hi Ajasja,

Thank you so so much for your kindly reply. First of all, I would like to say sorry that I am new to both Rosetta and PyRosetta so you may find my questions are a bit silly. I checked the reference you sent to me but seems that both of them are only suitable for Rosetta, while I want to do the job in PyRosetta.

Regarding the questions in your PS section. I found that the energy before and after the relax was different. s0 is a positive number while s1 is a negative number. I don’t know whether in my python code the relax takes into account the coord constraints, but according to the official tutorial the command “relax.constrain_relax_to_start_coords(True)” helps me do it? Also, may I ask you what do you mean by “using two different scoring functions?”, do you mean that I can set up a scorefxn1=”ref2015_cart” for cartesian_relax, while setting up another scorefxn2=’ref2015′ for the scoring calculation?

For your suggestion, May I ask how you keep everything else fixed while having a flexible backbone around the mutation? Do I have to do the minimization for the mutated pose? The “mutate_residue()” function is attached below, does the “Packer“ help me do the job already?

Really sorry to bother you again and again, looking forward to hearing from you!

Best,

Kai San

def mutate_residue(

pack_or_pose, mutant_position, mutant_aa, pack_radius=0., pack_scorefxn=None

):

"""Replace the residue at a single position in a Pose with a new amino acid

and repack any residues within user-defined radius of selected residue's

center using.

Args:

pack_or_pose (pyrosetta.rosetta.core.pose.Pose OR pyrosetta.distributed.packed_pose.PackedPose):

the `Pose` instance to use.

mutant_position (int): Pose-numbered position of the residue to mutate.

mutant_aa (str): The single letter name for the desired amino acid.

pack_radius (float): Radius used to define neighboring residues.

pack_scorefxn (pyrosetta.ScoreFunction): `ScoreFunction` to use when repacking the `Pose`.

Defaults to the standard `ScoreFunction`.

"""

import pyrosetta

import pyrosetta.distributed.packed_pose as packed_pose



wpose = packed_pose.to_pose(pack_or_pose)



if not wpose.is_fullatom():

raise IOError("mutate_residue only works with fullatom poses")



# create a standard scorefxn by default

if not pack_scorefxn:

pack_scorefxn = pyrosetta.get_score_function()



# the numbers 1-20 correspond individually to the 20 proteogenic amino acids

from pyrosetta.rosetta.core.chemical import aa_from_oneletter_code



mutant_aa = int(aa_from_oneletter_code(mutant_aa))

aa_bool = pyrosetta.Vector1([aa == mutant_aa for aa in range(1, 21)])



# mutation is performed by using a PackerTask with only the mutant

# amino acid available during design

task = pyrosetta.standard_packer_task(wpose)

task.nonconst_residue_task(mutant_position).restrict_absent_canonical_aas(aa_bool)



# prevent residues from packing by setting the per-residue "options" of the PackerTask

task = restrict_non_nbrs_from_repacking(wpose, mutant_position, task, pack_radius)



# apply the mutation and pack nearby residues

from pyrosetta.rosetta.protocols.minimization_packing import PackRotamersMover



packer = PackRotamersMover(pack_scorefxn, task)

packer.apply(wpose)