From owner-chemistry@ccl.net Fri Dec  5 11:08:01 2025
From: "Joel Subach mjsubach%x%alumni.ncsu.edu" <owner-chemistry ~ server.ccl.net>
To: CCL
Subject: CCL: Large Ligand Pose Generation for a PDB Large Heptamer not in Complex?
Message-Id: <-55430-251205101657-7807-gKt+0WZk73VhCp15rPCSNw ~ server.ccl.net>
X-Original-From: "Joel  Subach" <mjsubach|,|alumni.ncsu.edu>
Date: Fri, 5 Dec 2025 10:16:53 -0500


Sent to CCL by: "Joel  Subach" [mjsubach++alumni.ncsu.edu]
Hello CCL I hope your well:), towards the above topic, I have a large heptamer 
transmembrane protein PDB file (each monomer 426-residues). I need two 
separate large ligand poses bound to the heptamer (40-heavy atoms/500 Daltons 
and 89-heavy atoms/1000 Daltons) both still not in complex in the PDB. The 
ligand bindings will each be in the heptamers highly dynamic extracellular 
loop(s).

Are there any induced fit docking softwares exhibiting expertise in predicting 
the above two separate large ligand poses considering the above-sizes and 
dynamic loop bindings?

I Induced Fit Docked two-different conformers, one from gypsum_dl and one from 
NovoPro (NovoPro generated one-conformer and I selected the lowest energy 
gyspum_dl conformer considering they were all structurally similar), however, 
all docked models bound differently but exhibited similar energy values and 
similar structural bindings. Accordingly in search of an algorithm exhibiting 
expertise towards best ligand pose generation.

And if you know of a software that can Ensemble Dock and or Incremental Dock 
and or Deep Learning Approach feel free to let me know, the ones I discovered 
thus far can not handle Large Ligands.

Thanks if you have any inputs:)

Joel Subach mjsubach:_:alumni.ncsu.edu


From owner-chemistry@ccl.net Fri Dec  5 14:23:01 2025
From: "Cristian Bologa CBologa() salud.unm.edu" <owner-chemistry#,#server.ccl.net>
To: CCL
Subject: CCL: Large Ligand Pose Generation for a PDB Large Heptamer not in Complex?
Message-Id: <-55431-251205142017-25580-a/dl9aMAUkhXzQ/peQktiw#,#server.ccl.net>
X-Original-From: Cristian Bologa <CBologa(_)salud.unm.edu>
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Sent to CCL by: Cristian Bologa [CBologa*o*salud.unm.edu]
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Have you tried Boltz-2 or Chai-1 to see if you get any reasonable results? =
They are open source alternatives to Alphafold-3
________________________________
> From: owner-chemistry+cbologa=3D=3Dsalud.unm.edu^-^ccl.net <owner-chemistry+c=
bologa=3D=3Dsalud.unm.edu^-^ccl.net> on behalf of Joel Subach mjsubach%x%alum=
ni.ncsu.edu <owner-chemistry^-^ccl.net>
Sent: Friday, December 5, 2025 8:16 AM
To: Cristian Bologa <CBologa^-^salud.unm.edu>
Subject: CCL: Large Ligand Pose Generation for a PDB Large Heptamer not in =
Complex?


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Sent to CCL by: "Joel  Subach" [mjsubach++https://urldefense.com/v3/__http:=
//alumni.ncsu.edu__;!!KXH1hvEXyw!eDKx7dw3voBmUKWHA3Ol7WcEjg5-YQxyERBuJtDgKd=
ImOIrzbBfQiPdpcT1kM0vUZ3RgKRTQgKlWeTNKtBcclCOkc2FS$ ]
Hello CCL I hope your well:), towards the above topic, I have a large hepta=
mer
transmembrane protein PDB file (each monomer 426-residues). I need two
separate large ligand poses bound to the heptamer (40-heavy atoms/500 Dalto=
ns
and 89-heavy atoms/1000 Daltons) both still not in complex in the PDB. The
ligand bindings will each be in the heptamers highly dynamic extracellular
loop(s).

Are there any induced fit docking softwares exhibiting expertise in predict=
ing
the above two separate large ligand poses considering the above-sizes and
dynamic loop bindings?

I Induced Fit Docked two-different conformers, one from gypsum_dl and one f=
rom
NovoPro (NovoPro generated one-conformer and I selected the lowest energy
gyspum_dl conformer considering they were all structurally similar), howeve=
r,
all docked models bound differently but exhibited similar energy values and
similar structural bindings. Accordingly in search of an algorithm exhibiti=
ng
expertise towards best ligand pose generation.

And if you know of a software that can Ensemble Dock and or Incremental Doc=
k
and or Deep Learning Approach feel free to let me know, the ones I discover=
ed
thus far can not handle Large Ligands.

Thanks if you have any inputs:)

Joel Subach mjsubach*_*https://urldefense.com/v3/__http://alumni.ncsu.edu__=
;!!KXH1hvEXyw!eDKx7dw3voBmUKWHA3Ol7WcEjg5-YQxyERBuJtDgKdImOIrzbBfQiPdpcT1kM=
0vUZ3RgKRTQgKlWeTNKtBcclCOkc2FS$



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Have you tried Boltz-2 or Chai-1 to see if you get any reasonable results? =
They are open source alternatives to Alphafold-3
<hr style=3D"display:inline-block;width:98%" tabindex=3D"-1">
<div id=3D"divRplyFwdMsg" dir=3D"ltr"><font face=3D"Calibri, sans-serif" st=
yle=3D"font-size:11pt" color=3D"#000000"><b>From:</b> owner-chemistry+cbolo=
ga=3D=3Dsalud.unm.edu^-^ccl.net &lt;owner-chemistry+cbologa=3D=3Dsalud.unm.ed=
u^-^ccl.net&gt; on behalf of Joel Subach mjsubach%x%alumni.ncsu.edu
 &lt;owner-chemistry^-^ccl.net&gt;<br>
<b>Sent:</b> Friday, December 5, 2025 8:16 AM<br>
<b>To:</b> Cristian Bologa &lt;CBologa^-^salud.unm.edu&gt;<br>
<b>Subject:</b> CCL: Large Ligand Pose Generation for a PDB Large Heptamer =
not in Complex?</font>
<div>&nbsp;</div>
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<br>
<br>
<br>
Sent to CCL by: &quot;Joel&nbsp; Subach&quot; [mjsubach++https://urldefense=
.com/v3/__http://alumni.ncsu.edu__;!!KXH1hvEXyw!eDKx7dw3voBmUKWHA3Ol7WcEjg5=
-YQxyERBuJtDgKdImOIrzbBfQiPdpcT1kM0vUZ3RgKRTQgKlWeTNKtBcclCOkc2FS$ ]<br>
Hello CCL I hope your well:), towards the above topic, I have a large hepta=
mer <br>
transmembrane protein PDB file (each monomer 426-residues). I need two <br>
separate large ligand poses bound to the heptamer (40-heavy atoms/500 Dalto=
ns <br>
and 89-heavy atoms/1000 Daltons) both still not in complex in the PDB. The =
<br>
ligand bindings will each be in the heptamers highly dynamic extracellular =
<br>
loop(s).<br>
<br>
Are there any induced fit docking softwares exhibiting expertise in predict=
ing <br>
the above two separate large ligand poses considering the above-sizes and <=
br>
dynamic loop bindings?<br>
<br>
I Induced Fit Docked two-different conformers, one from gypsum_dl and one f=
rom <br>
NovoPro (NovoPro generated one-conformer and I selected the lowest energy <=
br>
gyspum_dl conformer considering they were all structurally similar), howeve=
r, <br>
all docked models bound differently but exhibited similar energy values and=
 <br>
similar structural bindings. Accordingly in search of an algorithm exhibiti=
ng <br>
expertise towards best ligand pose generation.<br>
<br>
And if you know of a software that can Ensemble Dock and or Incremental Doc=
k <br>
and or Deep Learning Approach feel free to let me know, the ones I discover=
ed <br>
thus far can not handle Large Ligands.<br>
<br>
Thanks if you have any inputs:)<br>
<br>
Joel Subach mjsubach*_*https://urldefense.com/v3/__http://alumni.ncsu.edu__=
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