The Role of Transformers in Generative AI for Drug Discovery and Development

This chapter explores the use of transformers with self-attention mechanisms in generative AI for drug discovery and development. It discusses their ability to predict secondary and tertiary protein structures and the advantages they offer in capturing long-range dependencies and constructing context dynamically. The chapter also mentions the need for fine-tuning transformer models for molecular data and proposes the use of GPT-4 for augmenting researchers in finding and synthesizing content.