Datasets › dockstring
dockstring
Regression dataset for molecular docking scores (predicted molecule-protein binding affinity). Contains ~250,000 molecules against 58 protein targets.
Benchmarks archive 2025-07-28
All 4 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Graph Regression | ESR2 | ESA (Edge set attention, no positional encodings) R2 0.697±0.000 | An end-to-end attention-based approach for learning on graphs | davidbuterez/edge-set-attention | 9 | Compare |
| Graph Regression | F2 | ESA (Edge set attention, no positional encodings) R2 0.891±0.000 | An end-to-end attention-based approach for learning on graphs | davidbuterez/edge-set-attention | 9 | Compare |
| Graph Regression | KIT | PNA R2 0.843±0.000 | Principal Neighbourhood Aggregation for Graph Nets | rusty1s/pytorch_geometric +7 | 9 | Compare |
| Graph Regression | PARP1 | ESA (Edge set attention, no positional encodings) R2 0.925±0.000 | An end-to-end attention-based approach for learning on graphs | davidbuterez/edge-set-attention | 9 | Compare |
Papers archive 2025-07-28
9 shown of 9 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 18. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| An end-to-end attention-based approach for learning on graphs | 1 | 4 | 16 Feb 2024 | not harvested |
| Pure Transformers are Powerful Graph Learners | 2 | 4 | 6 Jul 2022 | ran 7 of 7 samples (0 unverified; 7 pointer-only for licence) |
| DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks | 1 | 4 | 11 Nov 2021 | ran 0 of 3 samples (3 unverified) |
| Do Transformers Really Perform Bad for Graph Representation? | 5 | 4 | 9 Jun 2021 | not harvested |
| How Attentive are Graph Attention Networks? | 8 | 4 | 30 May 2021 | ran 6 of 16 samples (10 unverified; 1 pointer-only for licence) |
| Principal Neighbourhood Aggregation for Graph Nets | 8 | 4 | 12 Apr 2020 | ran 33 of 55 samples (22 unverified; 48 pointer-only for licence) |
| How Powerful are Graph Neural Networks? | 19 | 4 | 1 Oct 2018 | ran 3 of 10 samples (7 unverified; 5 pointer-only for licence) |
| Graph Attention Networks | 93 | 4 | 30 Oct 2017 | ran 50 of 106 samples (56 unverified; 43 pointer-only for licence) |
| Semi-Supervised Classification with Graph Convolutional Networks | 55 | 4 | 9 Sep 2016 | ran 31 of 58 samples (27 unverified; 22 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Apache-2.0 license
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- dockstring
- ESR2
- F2
- KIT
- PARP1
- PGR
6 variant names, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections