Drug development is one of the most significant processes in the pharmaceutical industry.
Various computational methods have dramatically reduced the time and cost of drug …

Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some
protagonists point to vast opportunities potentially offered by such tools, others remain …

Molecular design strategies are integral to therapeutic progress in drug discovery.
Computational approaches for de novo molecular design have been developed over the …

Abstract Machine learning (ML) promises to tackle the grand challenges in chemistry and
speed up the generation, improvement and/or ordering of research hypotheses. Despite the …

The therapeutic properties of plants have been recognised since time immemorial. Many
pathological conditions have been treated using plant-derived medicines. These medicines …

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 …

Small-molecule drug discovery can be viewed as a challenging multidimensional problem in
which various characteristics of compounds—including efficacy, pharmacokinetics and …

In de novo drug design, computational strategies are used to generate novel molecules with
good affinity to the desired biological target. In this work, we show that recurrent neural …

Natural products and their molecular frameworks have a long tradition as valuable starting
points for medicinal chemistry and drug discovery. Recently, there has been a revitalization …

Recently, deep generative models have revealed itself as a promising way of performing de
novo molecule design. However, previous research has focused mainly on generating …