The investigation of the nitriles' H-bonding behavior in MD led us to consider the FF-dependent H-bond sampling of other moieties in the simulations. We characterized the Hbond geometries for backbone carbonyls that either participate in secondary structural elements or are located on loops (Figures S32-S41 and Section S9 for details). We found that the average carbonyl H-bond angles and distances (with angles and distances now de�ined as θCOX and dOX, respectively, in analogy to the de�initions in Figure ) in beta sheets are largely invariant to the FF, while the values for carbonyls in alpha helices are smaller and longer with POL MD than FC MD (Table ), the opposite of what was observed for nitrile H-bonds (Table ). For carbonyls on loops, comparing the contour plots in Figures S39-S41 indicates a broader range of dOX's are sampled in POL MD, and the POL MD distributions are consequently worse �it by Gaussian surfaces (Table ). This initial assessment suggests backbone carbonyls are a good target for future benchmarking, particularly since their H-bonding is a ubiquitous feature of proteins and their electric �ields can be inferred via the VSE on the frequencies. In summary, enabled by the new TDM-based VSE analysis, we overcame the issues of nitriles as vibrational electric �ield probes and directly compared experimentally-derived and MD-based electric �ields (FC≡N,TDM's and FC≡N,MD's, respectively) in H-bonding protein environments. Better agreement was observed with the POL AMOEBA FF than with the FC AMBER FF: this is justi�ied by the inclusion of higher order multipoles in AMOEBA, which led to more ordered and head-on H-bonding geometries consistent with stronger solvation electrostatics. Nitriles are commonly found on drugs, and since electrostatic interactions like Hbonding in�luence ligand binding, our results suggest that computational screens of nitrile-containing compounds with methods like docking would be bene�ited by using AMOEBA, albeit at higher computational cost. More broadly, this work complements previous electric �ield tests of nitriles and carbonyls. The nitrile in F62oCNF participates in almost no H-bonds and the MD-derived and TDM-derived electric �ields match well with both FFs, consistent with observations that FC MD could recapitulate nitrile and carbonyl electric �ields in aprotic protein environments. In contrast, we observed that FC≡N,MD's for nitriles in H-bonding environments need POL MD to successfully recapitulate FC≡N,TDM's, consistent with Welborn and Head-Gordon's demonstration that AMOEBA was necessary to recapitulate a carbonyl electric �ield in an Hbonding environment like the active site of ketosteroid isomerase. The electric �ields experienced by H-bonded nitriles as studied herein are likely to be encountered routinely in and around proteins, unlike the bespoke �ields found at enzyme active sites, bringing into question the necessary and suf�icient conditions to accurately sample protein environments in silico. Performing POL MD has traditionally come at substantial computational expense, but recent advances in the OpenMM and Tinker platforms which run the AMOEBA FF allow for integration of GPUs, thereby enabling our simulations (and others) to progress well into the ns regime. Since these technological advances make simulations of proteins with POL MD more feasible, there is an increased need for benchmarking to determine the contexts in which POL MD becomes essential. This work provides some guidance towards that goal, and, in future work, further engineered local perturbations to the nitriles' environments will be reported and analyzed within the framework outlined here to continue exploring AMOEBA's capabilities.