Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

Effective molecular representation learning is crucial for advancing molecular property
prediction and drug design. Mainstream molecular representation learning approaches are …

Multimodal Large Language Models (MLLMs) have seen growing adoption across various
scientific disciplines. These advancements encourage the investigation of molecule-text …

Scientific research faces high costs and inefficiencies with traditional methods, but the rise of
deep learning and large language models (LLMs) offers innovative solutions. This survey …

Accurately predicting drug-target binding affinity is crucial for advancing drug discovery.
Recent molecular pre-training models and biological large models provide general …

The process of drug development is inherently lengthy and costly, often taking over a
decade and requiring substantial financial investment. Deep learning models offer a …