TDC.CYP2D6_Substrate_CarbonMangels Leaderboard

Dataset Summary

Dataset Unit Size Task Metric Dataset Split
TDC.CYP2D6_Substrate_CarbonMangels % 664 Binary AUPRC Scaffold

Leaderboard

Rank Model Contact Link #Params AUPRC
1 ContextPred Kexin Huang GitHub, Paper 2,067,053 0.736 ± 0.024
2 DeepMol (AutoML) DeepMol team GitHub, Paper N/A 0.731 ± 0.037
3 MapLight + GNN Jim Notwell GitHub, Paper N/A 0.720 ± 0.002
4 MapLight Jim Notwell GitHub, Paper N/A 0.713 ± 0.009
5 CFA Nan Jiang GitHub, Paper N/A 0.704 ± 0.015
6 AttrMasking Kexin Huang GitHub, Paper 2,067,053 0.704 ± 0.028
7 MiniMol Blazej Banaszewski GitHub, Paper N/A 0.695 ± 0.032
8 Chemprop-RDKit Kyle Swanson GitHub, Paper N/A 0.686 ± 0.031
9 ZairaChem Gemma Turon GitHub, Paper N/A 0.685 ± 0.029
10 RDKit2D + MLP (DeepPurpose) Kexin Huang GitHub, Paper 633,409 0.677 ± 0.047
11 Morgan + MLP (DeepPurpose) Kexin Huang GitHub, Paper 1,477,185 0.671 ± 0.066
12 Chemprop Kyle Swanson GitHub, Paper N/A 0.632 ± 0.037
13 GCN Kexin Huang GitHub, Paper 191,810 0.617 ± 0.039
14 AttentiveFP Kexin Huang GitHub, Paper 300,806 0.574 ± 0.030
15 NeuralFP Kexin Huang GitHub, Paper 480,193 0.572 ± 0.062
16 Euclia ML model Euclia GitHub, Paper 50 0.498 ± 0.015
17 CNN (DeepPurpose) Kexin Huang GitHub, Paper 226,625 0.485 ± 0.037
18 Basic ML Nilavo Boral GitHub, Paper N/A 0.478 ± 0.018

: The higher the better.