"The word 'quantum' immediately brings images of such scientific giants as Heisenberg and Schrodinger to mind. Yet we do not need to be a physicist to apply quantum mechanics on a daily basis…"
Pat Wright · 2013
Today, bioanalysts have a range of computational tools to help with method development and data interpretation. These are designed for the user without specialist computational knowledge and are readily available from either commer-cial sources or as freeware. There is software available for determining pKa, logP, solubility, chromatographic retention, sites of metabolism and mass spectral interpretation. But how many of us take time to understand the reasoning behind the packages we are using and, hence, their limitations? All these software packages, whatever the sup -plier or application, have a significant degree of error associated with them. It is this error that makes them predictive rather than definitive. There are two types of computational tool; data modeling and molecular modeling. The majority of software is based on data modeling. Data modeling establishes the relationship between the property of interest and experi-mentally determined ‘descriptors’, which can be statistically extrapolated to other compounds. In molecular modeling, quantum mechanical methods are used to calculate various molecu-lar properties dependent on its conformation, making molecular modeling a 3D technique.Quantitative structure–property relation-ship (QSPR) or quantitative–activity relation-ship (QSAR) approaches establish relationships between molecular structure (expressed as a ‘descriptor’, which is a numerical value represent -ing chemical information