Docking validation study: classic example, thrombine

The Figure on the left represents a docking study of more than 200 molecules with known activity on thrombin. The protein is a well known target ....

We have extracted the binding data from the BindingDB database and docked all the molecules onto a single (of a few available) 3D structure (2cn0 from the pdb databank).

The figure represents graphically the results of the research. The calculated and the measured activities are well correlated. Strong binders are indeed identified as strong binders (left bottom part of the graph). The accuracy of the predictions is quite good (see our discussion on the quality of the biological data here and here).

The results of the calculations can be conveniently summarized in terms of confidentiality matrix. Normally a first screen of novel compounds is performed at a certain concentration to distinguish between the active and non-active compounds. Let's take a standard, 1muM (~-35kJ/M) activity, as a separation cut-off. Then the confidence matrix has the following elements:

• Experimentally active, Predicted active: 29 molecules
• Experimentally n-active, Predicted active: 15 molecules (false positives)
  
• Experimentally active, Predicted n-active: 8 molecules (false negatives)
  
• Experimentally n-active, Predicted n-active: 156 molecules