OGB

PCQM4Mv2

Graph Regression PyG dataset page ↗PyG ↗

Structure

3,746,619Graphs
14Nodes
15Edges
9Node Feature Dim
3Edge Feature Dim

Coverage

111Results
1Variants
16Papers
Graph regression Predict each molecule’s HOMO-LUMO energy gap, a continuous quantum-chemical property calculated with density functional theory. The default 2D graph conversion uses OGB’s nine categorical atom and three categorical bond fields from SMILES. Evaluated by MAE.

Dataset details

Task

Predict each molecule’s HOMO-LUMO energy gap, a continuous quantum-chemical property calculated with density functional theory. Mean absolute error in electron volts is the official metric.

Data

PCQM4Mv2 contains 3,746,619 PubChemQC molecules. Training molecules also have DFT-optimized 3D structures, while SMILES describe the final optimized connectivity; test labels are held by OGB-LSC.

Features

The default 2D graph conversion uses OGB’s nine categorical atom and three categorical bond fields from SMILES. Coordinates are optional additional inputs for training molecules and are unavailable in the same form for blind test molecules.

Splits and evaluation

Molecules are ordered and split by PubChem compound identifier into 90% train, 2% validation, 4% test-dev, and 4% test-challenge. Despite an original intention to use scaffolds, the released split is CID-based because of a preprocessing bug.

Quirks and pitfalls

PCQM4Mv2 corrected an approximately 10% mismatch in PCQM4M between initial SMILES and gaps computed after geometry optimization, so the versions are not interchangeable. The CID split is not a scaffold split. Test-dev and test-challenge are distinct blind sets, and using supplied training coordinates creates an input-availability asymmetry.

Sources

OGB coverage note: We have not copied the official OGB leaderboard yet. Where possible, we locate the corresponding papers on arXiv and parse their reported results, so some entries may be missing. We plan to integrate the complete leaderboard soon.

SOTA Progression

new SOTA matches SOTA at that time other proposed result other baseline result

Leaderboard

#ModelHOMO-LUMO gap MAE (eV) ↓MAE (↓), ValidatePaper
1
DeMol
0.0603
—
2
TGT-At
0.0671
—
3
TGT-At (+RDKit)
0.0683
—
4
UniMol
0.0693
—
5
Uni-Mol+ (+RDKit)
0.0705
—
6
GPS
0.0720
—
7
Transformer-M
0.0772
—
8
GPS
0.0778
—
9
GoMS_GT
0.0780
—
10
Transformer-M
0.0782
—
11
Transformer-M
0.0787
—
12
GEM-2
0.0793
—
13
MPNNs
0.0800
—
14
GEM-2 (+RDKit)
0.0806
—
15
GEM-2
0.0806
—
16
GPTrans-L
0.0809
—
17
GPTrans-B
0.0813
—
18
GPTrans-S
0.0823
—
19
ET+RRWP
0.0832
—
20
GPTrans-T
0.0833
—
21
GRIT 2-QiQRW
0.0838
—
22
ET
0.0840
—
23
GRIT (our run)
0.0842
—
24
GPS-Deep
0.0852
—
25
GraphGPS_DEEP
0.0852
—
26
GraphGPS Medium
0.0858
—
27
GTs
0.0858
—
28
GPS-medium
0.0858
—
29
GraphGPS_BASE
0.0858
—
30
EGT-Larger
0.0859
—
31
GRIT
0.0859
—
32
OSAN
0.0862
—
33
EGT
0.0862
—
34
GraphGPS
0.0862
—
35
Graphormer
0.0864
—
36
GRPE-Large
0.0867
—
37
GRPE_LARGE
0.0867
—
38
EGT-Large
0.0869
—
39
EGT
0.0869
—
40
Graphormer
0.0870
—
41
EGT-Large
0.0872
—
42
GRPE-Large
0.0876
—
43
GRPE
0.0876
—
44
EGT-Medium
0.0881
—
45
IDMPNN
0.0882
—
46
GraphormerV2-L
0.0883
—
47
GRPE-Standard
0.0890
—
48
GRPE
0.0890
—
49
GRPE_BASE
0.0890
—
50
GRPE-Standard
0.0898
—
SOTA performance set a new SOTA at the time matched the SOTA at the time