Highlights•We provide a critical review of the current state of the activity cliff research.•We
comment on and integrate the opinions of experts working on activity cliffs.•The negative …

Understanding structure–activity relationships (SARs) for a given set of molecules allows
one to rationally explore chemical space and develop a chemical series optimizing multiple …

In recent years, structure− activity relationships (SARs) have increasingly been studied
through mining of large compound data sets, leading to a renaissance of the activity …

Analysis of marketed drugs and commercial vendor libraries used in high-throughput
screening suggests that the medicinally relevant chemical space may be expanded to …

Identifying potential protein-ligand interactions is central to the field of drug discovery as it
facilitates the identification of potential novel drug leads, contributes to advancement from …

Systematic description of structure–activity relationships (SARs) of data sets and structure–
property relationships (SPRs) is of paramount importance in medicinal chemistry and other …

We here present a streamlined, explainable graph convolutional neural network (gCNN)
architecture for small molecule activity prediction. We first conduct a hyperparameter …

The chemoinformatics field continues to evolve at the interface between computer science
and chemistry. Chemical information and computational approaches in pharmaceutical …

In this work, we analyze the structure–activity relationships (SAR) of epigenetic inhibitors
(lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined …

Chemical libraries and compound data sets are among the main inputs to start the drug
discovery process at universities, research institutes, and the pharmaceutical industry. The …