Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

REINVENT 4 is a modern open-source generative AI framework for the design of small
molecules. The software utilizes recurrent neural networks and transformer architectures to …

Generative deep learning is accelerating de novo drug design, by allowing the generation of
molecules with desired properties on demand. Chemical language models–which generate …

Over the past decade, the amount of biomedical data available has grown at unprecedented
rates. Increased automation technology and larger data volumes have encouraged the use …

Molecular docking is a structure-based computational method that generates the binding
pose and affinity between ligands and targets. There are many powerful docking programs …

Recent research on artificial intelligence indicates that machine learning algorithms can
auto-generate novel drug-like molecules. Generative models have revolutionized de novo …

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

The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, there has been a …

Molecular discovery is a multi-objective optimization problem that requires identifying a
molecule or set of molecules that balance multiple, often competing, properties. Multi …