Thanks for answering questions! I'd be curious to know where you got your (presumably massive) data from to train a NN to spit out what seems to be binding affinity between two candidates (drug and target). Do you guys use a NN for each target? I know you may not be able to answer these questions :)
Over the past few years, there's been a huge increase in the amount of data available for this kind of machine learning. We curate our data from a number of private and public sources. For example, as part of my doctoral work (http://en.wikipedia.org/wiki/SCRIPDB), I learned how to parse chemical information out of U.S. Patent data, which is public domain. That said, if you're interested in working on something like this and need a quick million data points, I'd point you to PubChem as a first step: https://pubchem.ncbi.nlm.nih.gov/
I hope your team succeeds, keep up the hard work!