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usecasehitident [2013/10/09 21:54]
rkiss
usecasehitident [2014/01/01 16:49]
flack
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 ====== Identify new hits for your target ====== ====== Identify new hits for your target ======
  
-[[http://​youtu.be/​RCLQFoZj0C4|{{:​hello.png?​100|}}]] **[[http://​youtu.be/​RCLQFoZj0C4|Check out how Ed, the chemist identifies new chemical starting points for his project using Mcule >>]]**+[[http://​youtu.be/​RCLQFoZj0C4|{{:​hello.png?​100|}}]] **[[http://​youtu.be/​RCLQFoZj0C4|Check out how Ed, the chemist identifies new chemical starting points for his project using Mcule »]]**
  
 You can identify new inhibitors/​modulators of your target (receptor, enzyme, nucleid acid, etc.) by searching the Mcule database. In Mcule, you can easily build **[[http://​en.wikipedia.org/​wiki/​Virtual_screening|virtual screening]]** workflows by putting together molecular modeling tools like LEGO bricks. Virtual screening workflows are a set of filters and calculations. Filters can eliminate compounds that unlikely binds your target or have other unwanted properties and calculations can rank order the best candidates for example by their estimated binding affinity. You can filter the whole Mcule database (over 5 million compounds) with several tools until you select the most promising compounds (10-1000). You can order the best hits by just a few clicks. You can identify new inhibitors/​modulators of your target (receptor, enzyme, nucleid acid, etc.) by searching the Mcule database. In Mcule, you can easily build **[[http://​en.wikipedia.org/​wiki/​Virtual_screening|virtual screening]]** workflows by putting together molecular modeling tools like LEGO bricks. Virtual screening workflows are a set of filters and calculations. Filters can eliminate compounds that unlikely binds your target or have other unwanted properties and calculations can rank order the best candidates for example by their estimated binding affinity. You can filter the whole Mcule database (over 5 million compounds) with several tools until you select the most promising compounds (10-1000). You can order the best hits by just a few clicks.
  
-**__[[usecasestrbased|Structure-based virtual screening ​>>]]__**+**[[usecasestrbased|Structure-based virtual screening ​»]]**
  
-**__[[usecaseligbased|Ligand-based virtual screening ​>>]]__**+**[[usecaseligbased|Ligand-based virtual screening ​»]]**
  
 -- --
  
-**__[[usecases|Go back to use cases >>]]__**+**[[usecases|Go back to use cases »]]**
usecasehitident.txt · Last modified: 2014/01/01 16:49 by flack