Figure summarizes the main findings: our NES approach performs comparably to in silico predictors, with CHARMM36m yielding an average unsigned error (AUE) of 2.92±0.35 pK as compared to 3.09 ± 0.29 pK and 2.71 ± 0.29 pK for PropK a and PypK a , respectively. This performance was also reflected in the Pearson correlation, which was 0.24 ±0.09 with CHARMM36m compared to 0.31 ± 0.14 and 0.22 ± 0.12 with PropK a and PypK a , respectively. On the 20 residue subset evaluated by MOE, MOE exhibited an improved accuracy of 1.79 ± 0.24 pK as compared to to accuracy, no method significantly exceeds a null predictor, which assumes ∆pK a = 0.