We have presented a fully atomistic multiscale methodology for generating the MPA spectra of ChR2-like transmembrane proteins. This approach combines classical MD with QM/MM MD sampling, followed by fragment-based polarizable embedding to derive adequate polarizable embedding potentials, and PE-TD-DFT for accurate spectroscopic calculations. The entire transmembrane protein system, including the bilipid layer, water, and ions, was explicitly included in the computation of the MPA spectra. A key innovation of this study is the extension of dynamical sampling beyond classical MM MD through MiMiC-QM/MM MD. Using autocorrelation functions, we carefully determined the optimal spacing between snapshots to ensure uncorrelated structures with respect to spectroscopic properties. Leveraging the two RSB moieties in ChR2, we analyzed the effect of sampling on the spectra. The QM-sampled moiety produces an OPA spectra in excellent agreement with the experiment, achieving an error of only 0.17 eV for the first absorption maximum and accurately reproducing the spectral profile. We have linked the differences in the spectra between the QM-and MM-sampled moieties to structural parameters such as BLA and planarity. The lower BLA and higher planarity observed in the QM-sampled moiety result in higher conjugation, which explains the redshift observed in its OPA spectra. In addition, we show a strong correlation of these structural parameters to the first electronic excited state energy. For the first time, we have also generated the theoretical TPA and 3PA spectra for ChR2. Although there is no direct experimental comparison, given the strong alignment with the experimental OPA data, we conclude that the TPA and 3PA spectra presented are similarly reliable. Furthermore, we have quantified the effect of polarizable embedding environments on the spectra. Our results demonstrate the critical role of polarization effects in accurately modelling the spectroscopic behaviour of complex biomolecular systems. Future research can build on these findings to explore the double photocycle model recently proposed for ChR2. In addition, this methodology can be applied to investigate MPA properties in engineered rhodopsin variants or other optogenetic tools, contributing to the design of improved systems for biomedical applications.