The Future of Molecular Studies through the Lens of Large Language Models
Jinlu Zhang, Yin Fang, Xin Shao, Huajun Chen, Ningyu Zhang, Xiaohui Fan
Abstract
The rapid advancement of large language models is reshaping research across various fields, offering a novel approach to the complex realm of molecular studies. Our evaluation of GPT-4 and GPT-3.5, focusing on their performance in generating and optimizing molecular structures, highlights GPT-4's strengths in certain aspects of molecular optimization. However, it also revealed challenges in accurately creating complex molecules. Addressing these issues, we propose possible directions for future molecular science research. These suggestions aim to forge new paths for exploring the intricacies of molecular structures, potentially bringing new efficiencies and innovations in the field.