text: user4794: How to predict the half-maximal inhibitory concentration (IC50) of my ligands.
  I'm currently using Schrodinger suite software and I don't know how to predict the IC50?
  
  user3061: I don't think it is possible just from the docking scores. Docking scores are designed to give you an estimate of the binding affinity (entalphy), but they do not take entropic contributions into account very well. The best you can do are molecular dynamics simulations to calculate the free energy of binding. Which can be computationally quite costly e.g. with GROMACS or CHARMM.
  You can estimate the IC50 with molecular dynamics simulations as well, but that is not straightforward. E.g. with Umbrella simulations. An example for a potassium channel and a very simple ligand can be found here.
  Another approach would be to build a predictive model. If you have a library of compounds at hand you could use the chemical structures and e.g. the docking scores to estimate the IC50 based on statistics or machine learning. But biology is very messy in general, though if you get a representative dataset with very similar compounds to the one that you have in your dataset then you might be successful. You have to be sure that the binding site and pose are correct though.
  
original_text: 4794: <p>How to predict the half-maximal inhibitory concentration (IC50) of my ligands.</p>
  <p>I'm currently using Schrodinger suite software and I don't know how to predict the IC50?</p>
   3061: <p>I don't think it is possible just from the docking scores. Docking scores are designed to give you an estimate of the binding affinity (entalphy), but they do not take entropic contributions into account very well. The best you can do are molecular dynamics simulations to calculate the free energy of binding. Which can be computationally quite costly e.g. with GROMACS or CHARMM.</p>
  <p>You can estimate the IC50 with molecular dynamics simulations as well, but that is not straightforward. E.g. with Umbrella simulations. An example for a potassium channel and a very simple ligand can be found <a href="https://www.mpibpc.mpg.de/278397/Wacker-Soeren_2008_diploma_thesis_Goe.pdf" rel="nofollow noreferrer">here</a>.</p>
  <p>Another approach would be to build a predictive model. If you have a library of compounds at hand you could use the chemical structures and e.g. the docking scores to estimate the IC50 based on statistics or machine learning. But biology is very messy in general, though if you get a representative dataset with very similar compounds to the one that you have in your dataset then you might be successful. You have to be sure that the binding site and pose are correct though.</p>
  