Geometric deep learning (GDL) is based on neural network architectures that incorporate
and process symmetry information. GDL bears promise for molecular modelling applications …

Artificial intelligence (AI)-based methods continue to make inroads into accelerated
materials design and development. Here, we review AI-enabled advances made in the …

Recent advancements in large language models (LLMs) have led to the development of
highly potent models like OpenAI's ChatGPT. These models have exhibited exceptional …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest
because of its potential to expedite and lower the cost of the drug development process …

Humans use different domain languages to represent, explore, and communicate scientific
concepts. During the last few hundred years, chemists compiled the language of chemical …

Natural products (NPs) are primarily recognized as privileged structures to interact with
protein drug targets. Their unique characteristics and structural diversity continue to marvel …

Organic chemistry is replete with complex relationships: for example, how a reactant's
structure relates to the resulting product formed; how reaction conditions relate to yield; how …

Highlights•GNN has attracted wide attention from the field of designing drug molecules.•The
applications of GNN in molecule scoring, molecule generation and optimization, and …

Organic synthesis methodology enables the synthesis of complex molecules and materials
used in all fields of science and technology and represents a vast body of accumulated …