Table 1 Summary of molecular representation methods developed in recent years
From: Recent advances in molecular representation methods and their applications in scaffold hopping
Type | Model | Year | Link | Ref. |
|---|---|---|---|---|
Molecular Fingerprints & Descriptors | MolMapNet | 2021 | ||
FP-ADMET | 2021 | |||
BoostSweet | 2022 | N.A. | ||
FP-BERT | 2022 | |||
MapLight | 2023 | |||
CrossFuse-XGBoost | 2024 | |||
Language Model | Mol2vec | 2018 | ||
Mol-BERT | 2021 | |||
MOLFORMER | 2022 | |||
MTL-BERT | 2022 | |||
DeepSA | 2023 | |||
MolRoPE-BERT | 2023 | N.A. | ||
t-SMILES | 2024 | |||
INTransformer | 2024 | |||
Graph | GROVER | 2020 | ||
Attentive FP | 2020 | |||
MolGNet | 2021 | |||
ReLMole | 2022 | |||
GEM | 2022 | https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/pretrained_compound/ChemRL/GEM | ||
GraphMVP | 2022 | |||
FunQG | 2023 | |||
MolCAP | 2023 | |||
SME | 2023 | |||
HiMol | 2023 | |||
PharmHGT | 2023 | |||
IFGN | 2023 | |||
KANO | 2023 | |||
KPGT | 2023 | |||
MMGX | 2024 | |||
R-MAT | 2024 | |||
SMPT | 2024 | |||
TOML-BERT | 2024 | |||
Gram matrix | 2024 | |||
GSL-MPP | 2024 | |||
MolFormer | 2024 | |||
High-dimensional Features | UniMol | 2023 | ||
GeminiMol | 2024 | |||
PhenoModel | 2024 | |||
Ouroboros | 2025 | |||
Multimodal | FP-GNN | 2022 | ||
ImageMol | 2022 | |||
CLAMP | 2023 | |||
CGIP | 2023 | |||
UniMAP | 2023 | N.A. | ||
MoleSG | 2024 | |||
MMFDL | 2024 | |||
COATI | 2024 | |||
DLF-MFF | 2024 | |||
VideoMol | 2024 | |||
MvMRL | 2024 | |||
PremuNet | 2024 | |||
ISMol | 2024 | |||
Contractive Learning | GraphCL | 2020 | ||
MoCL | 2021 | |||
iMolCLR | 2022 | |||
MolCLR | 2022 | |||
ATMOL | 2022 | |||
SMICLR | 2022 | |||
3DGCL | 2023 | |||
CasANGCL | 2023 | |||
FraSICL | 2023 | |||
MOCO | 2024 | N.A. | ||
MolFeSCue | 2024 | |||
3D-MOL | 2024 | |||
UniCorn | 2024 | N.A. |