Re: [modeller_usage] modeller_usage Digest, Vol 10, Issue 108

30 Jul 2011

      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" modeller_usage-request@salilab.org
To: "modeller usage" modeller_usage@salilab.org
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
Send modeller_usage mailing list submissions to
    modeller_usage@salilab.org
To subscribe or unsubscribe via the World Wide Web, visit
    https://salilab.org/mailman/listinfo/modeller_usage
or, via email, send a message with subject or body 'help' to
    modeller_usage-request@salilab.org
You can reach the person managing the list at
    modeller_usage-owner@salilab.org
When replying, please edit your Subject line so it is more specific
than "Re: Contents of modeller_usage digest..."
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 modeller-care@salilab.org
Subject: Re: [modeller_usage] Good Quality Score
To: Brian Tsui btsui17@yahoo.com
Cc: "modeller_usage@salilab.org" modeller_usage@salilab.org
Message-ID: 4E31FC3F.5010601@salilab.org
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
-- 
modeller-care@salilab.org             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	  ashishr@bits-pilani.ac.in
Subject: [modeller_usage] Regarding Proper Alignment
To: modeller modeller_usage@salilab.org
Message-ID:
    30722239.171381311922189682.JavaMail.root@mailserver.bits-pilani.ac.in

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 modeller-care@salilab.org
Subject: Re: [modeller_usage] Regarding Proper Alignment
To: Ashish Runthala ashishr@bits-pilani.ac.in
Cc: modeller modeller_usage@salilab.org
Message-ID: 4E333792.1070802@salilab.org
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
-- 
modeller-care@salilab.org             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 mustafab4@gmail.com
Subject: [modeller_usage] Selection of Model
To: modeller_usage@salilab.org
Message-ID:
    CALHZR253S3mXhzH-=j4a8nM10__Tv+F+G2DNigfJHgZu=BEPjQ@mail.gmail.com
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