Human cytochrome P450 (CYP) proteins metabolize 75% of small-molecule pharmaceuticals, which makes structurebased modeling of CYP metabolism and inhibition, bolstered by the current availability of X-ray crystal structures of CYP globular catalytic domains, an attractive prospect. Accounting for this broad metabolic capacity is a combination of the existence of multiple different CYP proteins and the capacity of a single CYP protein to metabolize multiple different small molecules. It is thought that structural plasticity and flexibility contribute to this latter property; therefore, incorporating diverse conformational states of a particular CYP is likely an important consideration in structurebased CYP metabolism and inhibition modeling. While all-atom explicit-solvent molecular dynamics simulations can be used to generate conformational ensembles under biologically relevant conditions, existing CYP crystal structures are of the globular domain only, whereas human CYPs contain N-terminal transmembrane and linker peptides that anchor the globular catalytic domain to the endoplasmic reticulum. To determine whether this can cause significant differences in the sampled binding site conformations, microsecond scale all-atom explicit-solvent molecular dynamics simulations of the CYP2D6 globular domain in an aqueous environment were compared with those of the full-length protein anchored in a POPC lipid bilayer. While bilayer-anchoring damped some structural fluctuations in the globular domain relative to the aqueous simulations, none of the affected residues included binding site pocket residues. Furthermore, clustering of molecular dynamics snapshots based on either pairwise binding site pocket RMSD or volume differences demonstrated a lack of separation of snapshots from the two simulation conditions into different clusters. These results suggest the substantially simpler and computationally cheaper aqueous simulation approach can be used to generate a relevant conformational ensemble of the CYP2D6 binding site for structure-based metabolism and inhibition modeling.