NPGPT: Natural Product-Like Compound Generation with GPT-based Chemical Language Models

arXiv:2411.12886 · q-bio.BM, cs.LG, q-bio.QM, stat.ML · Submitted 2024-11-19 · Read on arXiv

q-bio.BM, cs.LG, q-bio.QM, stat.ML

Submitted: 2024-11-19

Updated: 2024-11-19

Journal ref: The Journal of Supercomputing, 81: 352, 2025

DOI: 10.1007/s11227-024-06860-w

Code: https://github.com/ohuelab/npgpt

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

Sources

• SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules
• ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
• Decoupled Weight Decay Regularization

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