Fig. 3 AIMNet predictions with different number of iterative passes t evaluated on the DrugBank subset of the COMP6-SFCl benchmark. AIMNet predictions.

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Presentation transcript:

Fig. 3 AIMNet predictions with different number of iterative passes t evaluated on the DrugBank subset of the COMP6-SFCl benchmark. AIMNet predictions with different number of iterative passes t evaluated on the DrugBank subset of the COMP6-SFCl benchmark. (A) Comparison of AIMNet performance at different t values with ANI-1x model trained on exactly the same dataset for relative conformer energies (ΔE), total energies (E), and atomic forces (F). (B) AIMNet accuracy in prediction of total energies (E), relative conformer energies (ΔE), atomic forces (F), charges (q), and volumes (V) at different t values. Relative RMSE is calculated as ratio of RMSE at given t divided by RMSE at t = 3 (the values used to train model). Roman Zubatyuk et al. Sci Adv 2019;5:eaav6490 Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).