Diffusion models have emerged as a powerful new family of deep generative models with
record-breaking performance in many applications, including image synthesis, video …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of
proteins and their interactions, enabling a huge range of applications in protein modelling …

Deep-learning methods have revolutionized protein structure prediction and design but are
presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which …

Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing
interest in the screening of multi-billion chemical compound libraries. However, the success …

Activity and property prediction models are the central workhorses in drug discovery and
materials sciences, but currently, they have to be trained or fine-tuned for new tasks. Without …

Traditional drug design requires a great amount of research time and developmental
expense. Booming computational approaches, including computational biology, computer …

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

Large language models have made significant strides in natural language processing,
enabling innovative applications in molecular science by processing textual representations …

Virtual screening, which identifies potential drugs from vast compound databases to bind
with a particular protein pocket, is a critical step in AI-assisted drug discovery. Traditional …