Medicinal plants have historically proven their value as a source of molecules with
therapeutic potential, and nowadays still represent an important pool for the identification of …

Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …

Molecular machine learning bears promise for efficient molecular property prediction and
drug discovery. However, labelled molecule data can be expensive and time consuming to …

Despite intense interest in expanding chemical space, libraries containing hundreds-of-
millions to billions of diverse molecules have remained inaccessible. Here we investigate …

The discovery of novel materials and functional molecules can help to solve some of
society's most urgent challenges, ranging from efficient energy harvesting and storage to …

This two‐part Review examines how automation has contributed to different aspects of
discovery in the chemical sciences. In this first part, we describe a classification for …

Designing new medicines more cheaply and quickly is tightly linked to the quest of exploring
chemical space more widely and efficiently. Chemical space is monumentally large, but …

We provide an overview of how the underlying philosophy of chemometrics is integrated
throughout metabonomic studies. Four steps are demonstrated:(1) definition of the aim,(2) …

Conspectus One of the simplest questions that can be asked about molecular diversity is
how many organic molecules are possible in total? To answer this question, my research …

The chemical sciences are producing an unprecedented amount of large, high-dimensional
data sets containing chemical structures and associated properties. However, there are …