Predicting Human Serum Albumin binding

http://pubs.acs.org/doi/pdf/10.1021/ci3006098

I have enjoyed reading this morning the publication of Hall, Jorgensen and Whitehead on Automated Ligand- and Structure-Based Protocol for in Silico Prediction of Human Serum Albumin Binding (J. Chem. Inf. Model, ASAP, DOI:10.1021/ci3006098). I have battled a couple of times with acidic compounds which had high albumin binding. This paper was a good summary of several of the approaches to QSAR models and combinations docking and the tricky problem of site selection (3 principle bind site, 3 others and a couple of structures with another 2 - 8 in total). I am pleased they have made the work flow available at a KNIME module with Schroedinger plug ins. They used Induced Fit Docking (IFD) to place molecules into the respective sites with some success by the look of it. I must admit docking Warfarin in does look a nightmare with two lysines and a arginine to bind to.
As we are interested in Knowledge Based Design from Matched Molecular Pair Analysis (MMPA) these sort of QSAR models and docking approaches have a synergy. Can the output of MMPA, the power to suggest molecules to make that will improve a property, be combined with a prediction to improve further the decision of what to make next with high probability of what the make next?