Predict residence time using MD

I’m not so interested in MD but some days ago I found attractive research of MD.
http://pubs.acs.org/doi/abs/10.1021/acs.jmedchem.6b00632
Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein–Ligand Residence Times

I was interested in the article because, residence times are important for drug discovery, it’s related not only in vivo efficacy but also cell activity.
But, I think it’s difficult to understand SKR (structure kinetics relationship) from SAR of IC50. Basically( this is my opinion…. ), Koff tends to correlate with lipophilicity or Mwt of compounds however if I designed molecule based on the trend, the molecule is not drug-like.
So, predict residence times is useful for drug discovery process.
The author predicted residence times using new scaled-MD method. And they found that key factor of kinetics was the shape of ligands, liner or branched.
In the table 1 showed good correlation between experimental and calculated data.
The method seems to work well.

BTW, to perform accurate predictions, it needs x-ray data and experimental dataset.
Which is faster to make molecules or to calculate molecules and make.
Does it depend on performance of PC or chemist ?
I don’t have answer……

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