ADL: term"randomized structure"

Richard Wood Richard.Wood at purduecal.edu
Sat Mar 26 09:51:29 PDT 2016


I don't agree with the "within 2.0 A range you can assume that most of the known essential interactions with the target have been
established" comment.  That would mean that a molecule such as geldanamycin could have completely flipped its orientation.

"Several papers showed redocking ligand structures generated from SMILES can reduce docking
accuracy by >20%."

I suspect a person that did that would be an organic chemist.

In my experience, a program like ChemAxon does NOT do a "complete optimization" like say, Gaussian would.

"In fact, pretty much every docking software (including AutoDock) do not alter bond angles
and lengths during the calculation"

If so, how do programs such as SurflexDock do binding site optimizations?  Surely they must read in a force field.

Sorry, I'm a computational chemist, and I take this kind of stuff VERY seriously because there are people with far less training than I have that are more gainfully employed than I am.  There are many people working in pharma that were "trained" by the companies they work for to be "modelers" because they are cheaper.

Richard
________________________________________
From: autodock-bounces at scripps.edu [autodock-bounces at scripps.edu] on behalf of Stefano Forli [forli at scripps.edu]
Sent: Friday, March 25, 2016 1:42 PM
To: autodock at scripps.edu
Subject: Re: ADL: term"randomized structure"

Hi Richard,
just to clarify, if you create your molecule from scratch (e.g., you sketch it from a 2D
programs like ChemDraw) you want to carefully prepare the 3D coordinates, so you *must* do
a complete minimization.

In fact, pretty much every docking software (including AutoDock) do not alter bond angles
and lengths during the calculation, so if your structure is distorted or not optimal, it
will lead to poor/wrong results.
Several papers showed redocking ligand structures generated from SMILES can reduce docking
accuracy by >20%.

About the RMSD cutoff, 2.0 A is widely accepted as the standard for evaluating docking
performance, even though there's strong agreement on RMSD itself being a poor metric for
docking accuracy.
Alternatives get constantly proposed, but despite its limitations, within 2.0 A range you
can assume that most of the known essential interactions with the target have been
established.

Best,

S

On 03/25/2016 06:03 AM, Richard  Wood wrote:
> Generally, unless one uses a 2-D drawing program, most sketching programs will do some kind of "quick and dirty" optimization.  So, when I said, "non-optimized", that is what I was referring to.  Of course, one can also do a full blown optimization and dock that as well.
>
> It is probably best to remove the ligand from a ligand-protein crystal structure and re-dock the ligand to see if one can place it in its correct position.  One can then tweak docking parameters to see if they can reproduce the crystal ligand pose.  You can then calculate the RMSD between your docked ligand and that of the crystal structure ligand.  If one is careful, you can get an RMSD of less than 0.5.  (As an aside, I was at an ACS talk a few years back, and there was a speaker from some pharma company who was re-docking ligands and comparing them to the crystal.  He was proud of the fact that his RMSDs were less than 2.  I told him after his talk that he could do much better than that (he I was a lowly post-doc and he was a "professional modeler"-I still remain far below "professional modeler").)
>
> It's questionable how many people actually do that, however.
>
> Richard
> ________________________________________
> From: autodock-bounces at scripps.edu [autodock-bounces at scripps.edu] on behalf of Stefano Forli [forli at scripps.edu]
> Sent: Thursday, March 24, 2016 8:17 PM
> To: autodock at scripps.edu
> Subject: Re: ADL: term"randomized structure"
>
> Hi,
> a general practice when testing docking programs is to prevent any kind of bias in the
> input structures that can simplify the search and artificially increase re-docking success
> rate.
>
> For this reason, the input structures should be randomized to be different from the
> solution, but still optimized, i.e., all bond angles and lengths must be correct.
>
> The ideal approach would be to generate the 3D coordinates of the ligand starting from
> scratch (e.g., SMILES format) using an external software and dock that.
>
> Although, since during docking bond angles and lengths are not altered, it is sufficient
> to randomize the conformation of the ligand from its experimental coordinates in a
> crystallographic complex, by altering its position, orientation and all the angles in
> rotatable bonds.
>
>
> S
>
>
>
> On 03/24/2016 06:09 PM, Richard  Wood wrote:
>> Non-optimized?
>>
>> Richard
>>
>> ________________________________________
>> From: autodock-bounces at scripps.edu [autodock-bounces at scripps.edu] on behalf of maria timoshik [m.timoshik at yandex.ru]
>> Sent: Thursday, March 24, 2016 2:30 PM
>> To: autodock at scripps.edu
>> Subject: ADL: term"randomized structure"
>>
>> Hello:
>> I've heard that in a very beginning of video tutorial to Vina Dr. Oleg Todd said:
>> "I'll use a randomized structure of a drug molecule".
>> What the term RANDOMIZED STRUCTURE actually mean in this context?
>> Perhaps professional physico-chemists can explain?
>>
>> with regards, Maria
>> ________________________________________________
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>> ________________________________________________
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>
> --
>
>    Stefano Forli, PhD
>
>    Assistant Professor of Integrative
>    Structural and Computational Biology,
>    Molecular Graphics Laboratory
>
>    Dept. of Integrative Structural
>     and Computational Biology, MB-112A
>    The Scripps Research Institute
>    10550  North Torrey Pines Road
>    La Jolla,  CA 92037-1000,  USA.
>
>       tel: +1 (858)784-2055
>       fax: +1 (858)784-2860
>       email: forli at scripps.edu
>       http://www.scripps.edu/~forli/
> ________________________________________________
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> ________________________________________________
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--

  Stefano Forli, PhD

  Assistant Professor of Integrative
  Structural and Computational Biology,
  Molecular Graphics Laboratory

  Dept. of Integrative Structural
   and Computational Biology, MB-112A
  The Scripps Research Institute
  10550  North Torrey Pines Road
  La Jolla,  CA 92037-1000,  USA.

     tel: +1 (858)784-2055
     fax: +1 (858)784-2860
     email: forli at scripps.edu
     http://www.scripps.edu/~forli/
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