Machine Learning for the Discovery of Nanomaterial-based Molecular Recognition

Computer program products, computer systems, and computer-implemented methods for making and using computational models for prediction of molecular recognition (MR) between a nanomaterial (NM) MR binder and an analyte. Methods for making a computational model involve selecting a candidate NM MR binder and conducting a physical test to determine whether MR occurs between the candidate NM MR binder and an analyte, and correlating features of the candidate NM MR binder with an experimental result obtained from the physical test to produce predictive information for the computational model. Methods for using the computational model involve receiving features of an untested candidate NM MR binder and analyzing the features to produce a prediction score that represents an expected experimental result of a physical test of the untested candidate MR binder and associating the prediction score with the untested candidate MR binder.