Recent efforts to synthetically expand drug‐like chemical libraries have led to the
emergence of unprecedently large virtual databases. This surge of make‐on‐demand …

Polymers, with the capacity to tunably alter properties and response based on manipulation
of their chemical characteristics, are attractive components in biomaterials. Nevertheless …

Molecular optimization is a fundamental goal in the chemical sciences and is of central
interest to drug and material design. In recent years, significant progress has been made in …

A pervasive challenge in drug design is determining how to expand a ligand─ a small
molecule that binds to a target biomolecule─ in order to improve various properties of the …

We introduce GAUCHE, an open-source library for GAUssian processes in CHEmistry.
Gaussian processes have long been a cornerstone of probabilistic machine learning …

Deep learning models that leverage large datasets are often the state of the art for modelling
molecular properties. When the datasets are smaller (< 2000 molecules), it is not clear that …

The present contribution introduces a novel computational protocol called PyRMD2Dock,
which combines the Ligand-Based Virtual Screening (LBVS) tool PyRMD with the popular …

Deep learning is accelerating drug discovery. However, current approaches are often
affected by limitations in the available data, in terms of either size or molecular diversity …

The discovery of therapeutic molecules is fundamentally a multi-objective optimization
problem. One formulation of the problem is to identify molecules that simultaneously exhibit …

Self-driving labs (SDLs) have emerged as a strategy for accelerating materials and chemical
research. While such systems autonomously select and perform physical experiments, this …