aceqcGEM: A Graph-Based Molecular Representation With Quantum Chemistry Awareness
The advancement of artificial intelligence (AI) has reshaped drug discovery. AI-based models typically rely on molecular representations for prediction. However, the absence of physically grounded information in mainstream molecular representations not only limits the model performance in practical applications but also hinders mechanistic understanding and exploitation by humans. To overcome this issue, we introduce qcGEM, a quantum-chemistry-aware graph-based embedding of molecules that incorporates physical p…
Building quantum chemistry priors into a graph-based molecular embedding gave state-of-the-art results across 83 molecule-related benchmark tasks and offered interpretability at multiple levels.
Evidence
- Peer-reviewedAdvanced Science2026-10-18
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Truvace Impact Record TRV-2026-1954, v1: “qcGEM: A Graph-Based Molecular Representation With Quantum Chemistry Awareness.” Truvace, 2026-10-20. /record/TRV-2026-1954 (accessed at citation time). sha256 549c4e192bf89cdc…
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