Abstract Development of new products often relies on the discovery of novel molecules.
While conventional molecular design involves using human expertise to propose …

De novo drug design is a stationary way to build novel ligands in the confined pocket of
receptor by assembling the atoms or fragments, while molecular dynamics (MD) simulation …

Fragment-based drug discovery has been an effective paradigm in early-stage drug
development. An open challenge in this area is designing linkers between disconnected …

In the past few years, de novo molecular design has increasingly been using generative
models from the emergent field of Deep Learning, proposing novel compounds that are …

Proteolysis-targeting chimeras (PROTACs) have emerged as effective tools to selectively
degrade disease-related proteins by using the ubiquitin-proteasome system. Developing …

Anti-cancer drug design has been acknowledged as a complicated, expensive, time-
consuming, and challenging task. How to reduce the research costs and speed up the …

Fragment-based drug discovery is a widely used strategy for drug design in both academic
and pharmaceutical industries. Although fragments can be linked to generate candidate …

This microperspective covers the most recent research outcomes of artificial intelligence (AI)
generated molecular structures from the point of view of the medicinal chemist. The main …

Recently, deep generative models have been regarded as promising tools in fragment-
based drug design (FBDD). Despite the growing interest in these models, they still face …

Deep learning has achieved tremendous success in designing novel chemical compounds
with desirable pharmaceutical properties. In this work, we focus on a new type of drug …