Monoamine oxidase B (MAO-B) is a potential biomarker for Parkinson's disease (PD), a neurodegenerative disease associated with the loss of motor activities in human subjects. The disease state is associated with dopamine deprival, and so the inhibitors of MAO-B can serve as therapeutic drugs for PD. Since the expression level of MAO-B directly correlates to the disease progress, the distribution and population of this enzyme can be employed to monitor disease development. One of the approaches available for estimating the population is two-photon imaging. The ligands used for two-photon imaging should have high binding affinity and binding specificity toward MAO-B along with significant two-photon absorption cross sections when they are bound to the target. In this article, we study using a multiscale modeling approach, the binding affinity and spectroscopic properties (one- and two-photon absorption) of three (Flu1, Flu2, Flu3) of the currently available probes for monitoring the MAO-B level. We report that the binding affinity of the probes can be explained using the molecular size and binding cavity volume. The experimentally determined one-photon absorption spectrum is well reproduced by the employed QM/MM approaches, and the most accurate spectral shifts, on passing from one probe to another, are obtained at the coupled-cluster (CC2) level of theory. An important conclusion from this study is also the demonstration that intrinsic molecular two-photon absorption strengths (δ2PA) increase in the order δ2PA (Flu1) > δ2PA (Flu2) > δ2PA (Flu3). This is in contrast with experimental data, which predict similar values of two-photon absorption cross sections for Flu1 and Flu3. We demontrate, based on the results of electronic-structure calculations for Flu1 that this discrepancy cannot be explained by an explicit account for neighboring residues (which could lead to charge transfer between a probe and neighboring aromatic amino acids thus boosting δ2PA). In summary, we show that the employed multiscale approach not only can optimize two-photon absorption properties and verify binding affinity, but it can also help in detailed analyses of experimental data.