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
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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 firstname.lastname@example.org Subject: Re: [modeller_usage] Good Quality Score To: Brian Tsui email@example.com Cc: "firstname.lastname@example.org" email@example.com Message-ID: 4E31FC3F.firstname.lastname@example.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