Dear Mustafa,
As such energy can't discriminate between close decoys, Normalized_dope gives a better idea. You may see the effect of each of the Modeller assessment score through your modeling script this way.
a = automodel(env,
alnfile = '------',
knowns = ('---', '---'),
sequence = 'target',
assess_methods=(assess.DOPE, assess.GA341,assess.normalized_dope))
Use a redirection operator > to save modeling result. Then use the trajectory of these values in your modeling. You will get your answer if you try modeling a known structure target, so that you can affirm model evaluation through GDT scores.
Good Luck,
Ashish
Ashish Runthala,
Lecturer, Structural Biology Cell,
Biological Sciences Group,
BITS, Pilani
Rajasthan, INDIA
----- Original Message -----
From: "modeller usage-request" <>
To: "modeller usage" <>
Sent: Saturday, July 30, 2011 12:47:57 PM GMT +05:30 Chennai, Kolkata, Mumbai, New Delhi
Subject: modeller_usage Digest, Vol 10, Issue 108
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Today's Topics:
1. Re: Good Quality Score (Modeller Caretaker)
2. Regarding Proper Alignment (Ashish Runthala)
3. Re: Regarding Proper Alignment (Modeller Caretaker)
4. Selection of Model (MUSTAFA BUGHIO)
----------------------------------------------------------------------
Message: 1
Date: Thu, 28 Jul 2011 17:18:07 -0700
From: Modeller Caretaker <>
Subject: Re: [modeller_usage] Good Quality Score
To: Brian Tsui <>
Cc: "" <>
Message-ID: <>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
On 7/26/11 8:33 PM, Brian Tsui wrote:
> In the Madhusudhan paper, the cutoff was at least 70% for a SO of 3.5 A.
Do you mean the SO was 70% for a cutoff of 3.5A?
> What number does that correspond to in the salign output?
The percentage of equivalent (i.e. within the cutoff) positions is the
qscorepct member of the SalignData object returned by salign(). Set the
cutoff with the rms_cutoff argument. And make sure you have QUALITY in
the output argument.
> For the quality score, is there an objective number that I can use for
> every alignment to see whether it is good or not?
As I said, only for structure alignments.
> Lastly, for "iterative salign," is it recommended to run the regular
> version first or just jump straight to using the iterative salign? The
> Madhusudhan paper seems to forgo the use of iterative salign if the
> alignment is 70% at a SO of 3.5
I'm assuming you're looking at fig 1 in the paper here. There are three
iterative procedures within that flowchart; one of them is skipped if
the first procedure (simpler alignment using a subset of features) found
a reasonable starting guess for the last procedure (structural
alignment). The second procedure is simply an attempt to improve this
guess if the first failed.
Ben Webb, Modeller Caretaker
--
http://www.salilab.org/modeller/
Modeller mail list: http://salilab.org/mailman/listinfo/modeller_usage
------------------------------
Message: 2
Date: Fri, 29 Jul 2011 12:19:49 +0530 (IST)
From: Ashish Runthala <>
Subject: [modeller_usage] Regarding Proper Alignment
To: modeller <>
Message-ID:
<>
Content-Type: text/plain; charset=utf-8
Dear Modellers,
May somebody tell me the logic of using rms_cutoff=3.5 while comparing and aligning multiple structures. Even when you alter, no difference come up in the generated model. Is this upper bound a relaxed in every modeling case. It may not be so, when same family proteins are aligned. So this strict upper bound on C? distance may leave several large chunks unaligned. Variable gap penalty makes the alignment correct through flexible allowed superposition, but why changing rms_cutoff didn't generate better models, not even 0.1 GDT_TS improvement was not observed.
Thanks
Ashish
Ashish Runthala,
Lecturer, Structural Biology Cell,
Biological Sciences Group,
BITS, Pilani
Rajasthan, INDIA
------------------------------
Message: 3
Date: Fri, 29 Jul 2011 15:43:30 -0700
From: Modeller Caretaker <>
Subject: Re: [modeller_usage] Regarding Proper Alignment
To: Ashish Runthala <>
Cc: modeller <>
Message-ID: <>
Content-Type: text/plain; charset=UTF-8; format=flowed
On 7/28/11 11:49 PM, Ashish Runthala wrote:
> May somebody tell me the logic of using
> rms_cutoff=3.5 while comparing and aligning multiple structures. Even
> when you alter, no difference come up in the generated model.
Changing rms_cutoff will not change the alignment. The cutoff is simply
the distance below which two residues are considered to be structurally
equivalent when aligned, so it will only affect measures such as the
structural overlap (and quality score).
Ben Webb, Modeller Caretaker
--
http://www.salilab.org/modeller/
Modeller mail list: http://salilab.org/mailman/listinfo/modeller_usage
------------------------------
Message: 4
Date: Sat, 30 Jul 2011 12:17:54 +0500
From: MUSTAFA BUGHIO <>
Subject: [modeller_usage] Selection of Model
To:
Message-ID:
<CALHZR253S3mXhzH-=j4a8nM10__Tv+F+G2DNigfJHgZu=>
Content-Type: text/plain; charset="iso-8859-1"
Dear Ben
I wanna repeat the question already asked by some one regarding the
selection of best model criterion. I have developed pentamer Structure
using model-multichain.py command i want to know on what basis i should
select the best model out of 20 models. I have checked both modeller
objective function scores and also Dope score but there i could not observe
any correlation between the two.
Can i get your input in this regard
Regards
--
MUSTAFA BUGHIO
Junior Research Fellow
Lab # P-133
Computational Medicinal Chemistry and Drug Design
Panjwani Center For Molecular Medicine and Drug Research, International
Center for Chemical Sciences, University of Karachi, Karachi 75270
Pakistan, +923313425010
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