Quantifying signal changes in nano-wire based biosensors.

In this work, we present a computational methodology for predicting the change in signal (conductance sensitivity) of a nano-BioFET sensor (a sensor based on a biomolecule binding another biomolecule attached to a nano-wire field effect transistor) upon binding its target molecule. The methodology is a combination of the screening model of surface charge sensors in liquids developed by Brandbyge and co-workers [Sørensen et al., Appl. Phys. Lett., 2007, 91, 102105], with the PROPKA method for predicting the pH-dependent charge of proteins and protein-ligand complexes, developed by Jensen and co-workers [Li et al., Proteins: Struct., Funct., Bioinf., 2005, 61, 704-721, Bas et al., Proteins: Struct., Funct., Bioinf., 2008, 73, 765-783]. The predicted change in conductance sensitivity based on this methodology is compared to previously published data on nano-BioFET sensors obtained by other groups. In addition, the conductance sensitivity dependence from various parameters is explored for a standard wire, representative of a typical experimental setup. In general, the experimental data can be reproduced with sufficient accuracy to help interpret them. The method has the potential for even more quantitative predictions when key experimental parameters (such as the charge carrier density of the nano-wire or receptor density on the device surface) can be determined (and reported) more accurately.