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Thermal Shift Assay for Inhibitors of 15-Hydroxyprostaglandin Dehydrogenase PDF Print
Written by Sarkis Dallakian   

Here are the results of a new PubChem BioAssay AID: 2427 with 42 compounds (22 active, 2 inactive and 18 inconclusive).

AutoDock did a perfect job here giving favourable binding energy for active compounds compared to inactives. As a result, we have a prefect ROC curve here. I made the makers bigger so you can see that all actives are on a vertical x=0 line and all inactives lay on a horizontal y=1 line.

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Last Updated on Thursday, 29 September 2011 09:32
 
qHTS Assay for Inhibitors of Dna Helicase PDF Print
Written by Sarkis Dallakian   

I've got another email from My NCBI (Subject: What's new for 'BioAssay - Limits: Protein 3D Structure). It was about AID: 2353 - qHTS Assay for Inhibitors of RecQ-Like Dna Helicase 1 with 23 active and 1272 tested compounds. There are 2 Links for Protein Structure corresponding to open and closed conformations. I run virtual screening for both of them, which produced similar results.

This looks more like an ROC curve you'll see in publications. In contrast to my previous results, this has fewer active compounds. One would think that AutoDock did a better job here since ROC curves are above the diagonal. However, as you can see from the plots on the left, lowest binding energies are coming from inactive compounds. The image below shows molecular surface for 2WWY (chain A) in green and lowest binding energy conformation for CID: 5328760 (-6.03 kcal/mol) and CID: 11957460 (-10.37 kcal/mol). The first one being the most active in the assay shows a weaker (virtual) binding compared to the second one, which although has the best computed binding energy is not active in the assay. The favourable binding energy is partally because of the size; CID: 11957460 is one of the largest in this assay. So the question is: what kind of changes needs to be done to virtual screening to make it agree more with experiment?

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Last Updated on Thursday, 29 September 2011 09:33
 
Open Babel Partial Charges PDF Print
Written by Sarkis Dallakian   

When preparing ligands for docking PyRx users can select between PyBabel (MGLTools) and Open Bable partial charges using Edit -> Preferences menu. See PyRx Screencast - Open Bable for details. PyRx is using PyBabel charges, by default. I run the dataset from my previous blog post, using Open Bable, to see if I can get better results. The figure below show the new results.

This shows that PyBable charges perform better for this virtual screening. The reason might be that AutoDock is calibrated using PyBable charges. Another reason might be that I use Open Bable for ligands only and not for the target. Whatever the reason, the new database table plotting tool is a very useful tool when it comes to comparing different virtual screening. 

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Last Updated on Thursday, 29 September 2011 09:34
 
Pre-Release 0.5 Updates PDF Print
Written by Sarkis Dallakian   

I've added instructions on how to update to the latest version from Source Code and how to submit a feature equest to Downloads page. The major new feature in 0.5 is database table plotting feature that can be used for BioAssays and ROC Curves. To compare ROC curves generated by two different docking algorithms, I run the dataset from my previous blog post through AutoDock Vina. There are third party packages available for AutoDock Vina such as PaDEL-ADV, VcPpt, MakeVinaCommand and PyMOL plugin. The new version of ADT also has features for working with output files generated by Vina. To explore an option for adding a new Wizard to PyRx for AutoDock Vina, I run AutoDock Vina on our cluster, using a script from Vina Manual. Here are the results:

This is just a proof of concept to show that you can use PyRx to analyse results from different docking programmes.

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Last Updated on Thursday, 29 September 2011 09:35
 
BioAssays and ROC Curves PDF Print
Written by Sarkis Dallakian   

I've got an email from My NCBI about new BioAssay - Limit: Protein 3D Structure. AID: 2158 has Compounds Active: 287Tested: 572; it's exaclty that I was looking for. Based on this data, I've implemented new features that will available in upcoming 0.5 release. Interested users can check it out right away. The new feature allows you to plot Binding Energies to provide a bird's-eye view of docking results. In addition, if you have corresponding BioAssay available, you can also plot ROC Curve next to Docking Results. ROC curves appear in many recent publications that prompted me to add this feature to PyRx. Google search on ROC Curve brought me to Receiver operating characteristic - Wikipedia. This page confused me more than it helped me, so I started searching for ROC curve further. I came across Let’s ROC that had the following article mentioned in the comments: Triballeau, N. et al. J Med Chem. 2005, 48, 2534-2547. This article is very well written and it helped me to better understand the use of ROC curves in Virtual Screenings.

This plot shows Docking Results and ROC Curve generated for AID: 2158 BioAssay. Note that results with lowest Binding Energy, as predicted by AutoDock, are active compounds. It might seem that overall AutoDock doesn't do well because some of the points on ROC curve are below the diagonal. However, this all depends on the dataset chosen. If the dataset had only a few active compounds, then chances are, that it would have produced an ideal ROC curve. In that sence, ROC curve, by itself, is not informative, unless you have a plot of Docking Results like the way PyRx does.

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Last Updated on Thursday, 29 September 2011 09:34
 
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