The potential from the polarizabilities and multipoles (static and induced) is often referred to as the embedding potential. The obtention of high-quality embedding potentials is crucial for the calculation of accurate spectroscopic properties. Fragment-based polarizable embedding derives the classical embedding potential directly from QM calculations on the individual fragments that make up the environment. In this work, the biological system is divided into three regions: water (both the water above or below the membranes as well as water molecules inside the channel), the lipid bilayer and the protein. The water region is fragmented into individual water molecules, and the embedding parameters like multiples and polarizabilities are then QM-derived for each water molecule in isolation. A more advanced fragmentation method is needed for the bilipid layer or the protein. In this work, the molecular fractionation with conjugate caps (MFCC) method has been employed, where the system is divided into small fragments, which in turn are capped with groups of atoms from neighboring fragments. Two neighboring caps are merged to form a so-called concap fragment to remove the double counting introduced by the capping. 64,67 Due to the system being quite large, the MFCC approach was adopted only for the protein and water molecules within 20 Å from the RSB core. The embedding potential parameters (atom-centered charges, dipoles, quadrupole and anisotropic dipole-dipole polarizabilities) we generated with PyFraMe 68 based on the Lo-Prop method. The fragment calculations were performed at the CAM-B3LYP 70 /loprop-6-31+G* level of theory (where loprop-6-31+G* is an ANO-type recontraction of 6-31+G*) using the Dalton program and the LoProp for Dalton Python script. The lipids were modeled using parameters from the averaged lipid embedding potential (ALEP). Ions and water molecules were modeled with averaged solvent embedding potential (SEP) parameters. We will label this approach as mfcc.