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Additional file 1 of Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities

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posted on 2021-02-16, 04:59 authored by Beihong Ji, Xibing He, Yuzhao Zhang, Jingchen Zhai, Viet Hoang Man, Shuhan Liu, Junmei Wang
Additional file 1: Table S1. Lists the name, entry code, resolution, released date and deposition author for each receptor studied in this paper. Table S3. Lists the RMSE, MAE, R2 and PI values before and after calibration of the Glide docking scores under the conditions of different CSE function and fingerprint. Table S4. Lists the difference of metrics for the measurement of docking performance before and after the calibration, i.e., dRMSE, dMAE, dR2 and dPI for the Glide scoring function. Table S5. Lists and Figure S1. Shows the RMSE, MAE, R2 and PI values before and after calibration of the AutoDock Vina docking scores under the conditions of different CSE functions and fingerprints. Table S6. Shows RMSE, MAE, R2 and PI values before and after calibration of Glide docking scores for compounds in the external test sets from DUD-E database. Figure S2. Shows the comparison of RMSE, MAE, R2 and PI values before and after the calibration of the Glide docking scores for A2AR and CFX external test sets using the best hybrid scoring function (FP2 fingerprint with CSE = S4). Table S7. Displays AUC, EF1 % and EF10 % values before and after calibration of Glide docking scores for compounds in the external test sets from DUD-E database. Figure S3. Shows ROC curves before and after calibration of the Glide docking scores for A2AR and CFX external test sets.

Funding

National Science Foundation National Institutes of Health

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