[modeller_usage] Fwd: The results of your email commands

["刘君" <>]

I don't understand.

Done.


---------- Forwarded message ----------
From:  <>
Date: 2008/7/22
Subject: The results of your email commands
To: 


The results of your email command are provided below. Attached is your
original message.


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- Done.



---------- 已转发邮件 ----------
From: "刘君" <>
To: 
Date: Tue, 22 Jul 2008 23:55:40 +0800
Subject: Fwd: [modeller_usage] a question on MODELLER usage
I guess how these users' questions and your reply turns to my personal
email. I appreciate your feedback as soon as possible. Or would you
please check your system kernel of your server, or perhaps it's just a
personally operating mistake?

sincerely yours,
snailliujun


---------- Forwarded message ----------
From: Modeller Caretaker <>
Date: 2008/7/18
Subject: Re: [modeller_usage] a question on MODELLER usage
To: Ivan Anishchenko <>
抄送： 


Ivan Anishchenko wrote:
> I deal with a peptide (35 residues long). I know its amino acid sequence
> and a set of mean values for phi- and psi- dihedrals and the respective
> confidence interval for each dihedral angle. The data is obtained from
> the NMR experiments. The aim is to obtain a structure with the
> main-chain dihedrals lying within the corresponding confidence interval
> for every residue. Side chains can take any conformation. How can such
> restraints be described in MODELLER?

1. Read in the initial structure (see the manual for complete_pdb) or
build an extended chain from the AA sequence (model.build_sequence).

2. Add restraints on each dihedral. See Restraints.add. To get the list
of atoms for each dihedral type in each residue, see Residue.phi and
Dihedral.atoms. For example, to constrain every phi angle in the model
'm' to 0 +/- 0.1 radians, using a Gaussian restraint:

for res in m.residues:
   if res.phi is not None:
       atoms = res.phi.atoms
       f = forms.gaussian(group=physical.dihedral,
                          feature=features.dihedral(*atoms),
                          mean=0, stdev=0.1)
       m.restraints.add(f)

3. You may also want to build other sets of restraints, for example
stereochemical restraints. See Restraints.make.

4. Optimize the structure. See conjugate_gradients().

      Ben Webb, Modeller Caretaker
--
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