Best practices for chemical data curation and QSAR model ...
Best practices for chemical data curation and QSAR model ...
Best practices for chemical data curation and QSAR model ...
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A proposed screening protocol <strong>for</strong> structure-based virtual screening<br />
Protein-lig<strong>and</strong><br />
complex(es)<br />
Generate<br />
geometric poses<br />
Generate<br />
Pairwise potential<br />
descriptors<br />
Build <strong>QSAR</strong><br />
classification<br />
<strong>model</strong><br />
Select<br />
acceptable<br />
<strong>model</strong>s<br />
A mix of lig<strong>and</strong>s <strong>and</strong> decoys<br />
from DUD<br />
Docking (e.g. Fred) <strong>and</strong> save<br />
multiple poses <strong>for</strong> each<br />
compound<br />
Target-specific filter<br />
/multi-target filter<br />
Exclude poses predicted as<br />
decoys<br />
Re-ranking<br />
(e.g. MedusaScore*)<br />
Per<strong>for</strong>mance<br />
evaluation<br />
MedusaScore was developed in<br />
Dr. N. Dokholyan’s lab in UNC<br />
J. Chem. Inf. Model. 2008, 48, 1656–1662
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