The fragmentation approach is simple for solute-solvent systems. For example, a water cluster can easily be fragmented into individual water molecules, and the parameters (i.e., multipoles and polarizabilities) are then derived for each molecule in isolation through a quantum-mechanical calculation. In systems that contain molecules that are too large to perform a single quantum-mechanical calculation for the derivation of the embedding parameters, the molecular fractionation with conjugate caps (MFCC) method is used to split the complete system into several smaller fragments, which each has a much smaller computational cost. Using the MFCC approach for deriving atom-centered parameters of proteins was introduced by Söderhjelm and Ryde. This approach has been shown to produce highquality embedding potentials for proteins as well as nucleic acids and lipids. Using such an approach, the computational cost is significantly reduced compared to carrying out a full quantum-mechanical calculation, but even so, the calculation of the embedding-potential parameters still carries a significant computational cost when there is a large number of fragments in the environment. The large cost of computing embedding parameters is particularly problematic when the fragments contain many atoms such as in protein environments, where an average capped amino-acid fragment produced in the MFCC approach contains about 30 atoms, with the number of atoms ranging from 19 atoms (in glycine) to 36 atoms (in tryptophan). This becomes even more significant when taking into account configurational sampling, which requires the embedding-potential parameters to be calculated for many configurations of the system. To reduce the computational cost associated with the calculation of embedding-potential parameters, we here present a set of transferable amino-acid-specific parameters, consisting of atom-centered point charges and isotropic dipole-dipole polarizabilities, tailored for use in large-scale PE-based calculations that include proteins. We will denote our parameter set as the cost-effective polarizable protein potential (CP 3 ). The CP 3 parameters are validated by comparing electric potentials (EPs) of a diverse set of structures, ranging in size from tripeptides to an insulin monomer protein, to high-quality quantum-mechanical references. Moreover, we also evaluate the performance of the CP 3 in realistic PE-based calculations on chromophores embedded in protein environments.