Molecule Text

Molecule text research focuses on developing computational methods to represent and manipulate molecules using textual descriptions, aiming to bridge the gap between chemical structures and readily accessible textual data. Current efforts center on multimodal large language models (LLMs), often employing transformer architectures and contrastive learning, to integrate molecular graphs and textual information for tasks like molecule generation, property prediction, and retrosynthetic planning. These advancements promise to accelerate drug discovery and materials science by enabling more efficient analysis, design, and optimization of molecules using readily available textual knowledge and AI-driven tools.