Abstract Structure-based drug design (SBDD) aims to design small-molecule ligands that
bind with high affinity and specificity to pre-determined protein targets. Generative SBDD …

Drug development is a complex and time-consuming endeavor that traditionally relies on the
experience of drug developers and trial-and-error experimentation. The advent of artificial …

Drug discovery is essential in human diseases but faces challenges because of the vast
chemical space. Molecular generation models have become powerful tools to accelerate …

Recent advancements in machine learning potentials (MLPs) have significantly impacted
the fields of chemistry, physics, and biology by enabling large-scale first-principles …

Designing ligand-binding proteins, such as enzymes and biosensors, is essential in
bioengineering and protein biology. One critical step in this process involves designing …

Lipid nanoparticles (LNPs) are an essential component of messenger RNA (mRNA)
vaccines and genome editing therapeutics. Ionizable amino lipids, which play the most …

Latent representation alignment has become a foundational technique for constructing
multimodal large language models (MLLM) by mapping embeddings from different …

Generative models in drug discovery have recently gained attention as efficient alternatives
to brute-force virtual screening. However, most existing models do not account for …

Generative drug design facilitates the creation of compounds effective against pathogenic
target proteins. This opens up the potential to discover novel compounds within the vast …

Biocatalysis is increasingly being adopted in industry for producing important chemicals in a
selective and efficient manner. Engineering an enzyme can often confer it with an altered …