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. Author manuscript; available in PMC: 2022 Jan 4.
Published in final edited form as: J Comput Aided Mol Des. 2021 Jan 4;35(1):1–35. doi: 10.1007/s10822-020-00363-5

Figure 10. Correlation plots for GDCC (combined OA and exo-OA) and exo-OA ranked submissions.

Figure 10.

Shown are correlation plots comparing calculated and experimental values for (Left to Right) AMOEBA/DDM/BAR, RESP/GAFF/MMPBSA-Cor, B2PLYPD3/SMD_QZ-R, and xtb-GNF/Machine Learning/CORINA MD ranked predictions for GDCC (top row) and exo-OA (bottom row). The AMOEBA/DDM/BAR approach performed particularly well by a variety of metrics, as did RESP/GAFF/MMPBSA-Cor. The former had the slope closest to 1 and its RMS error was among the lowest, whereas the latter performed better on error and correlation metrics but had a slope which was systematically incorrect. (See Table 3)