BBS, along with machine-learning and database experts from the Global Security division and others at LLNL, is in a strategic business partnership with the American Heart Association to computationally predict interactions between drugs and human proteins. Such interactions are the basis of both drug effectiveness – do drugs “hit” their targets? – and adverse side effects – do drugs have deleterious effects via “off-target” proteins? Predictions will also be tested experimentally. A computational pipeline and a database of calculated interactions are being created.
In silico prediction of drug-protein binding is computationally expensive. Computational and experimental results are being used to train machine-learning models, which can make large-scale screening of novel drug candidates – even molecules that have yet to be synthesized – computationally feasible. This will assist in increasing the success rate of drug-discovery efforts and in accelerating drug development. More info