Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …

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 …

Psychedelics are serotonin 2A receptor agonists that can lead to profound changes in
perception, cognition and mood. In this review, we focus on the basic neurobiology …

Abstract Machine learning has provided a means to accelerate early-stage drug discovery
by combining molecule generation and filtering steps in a single architecture that leverages …

Molecular docking has become an essential part of a structural biologist's and medicinal
chemist's toolkits. Given a chemical compound and the three-dimensional structure of a …

There is considerable interest in screening ultralarge chemical libraries for ligand discovery,
both empirically and computationally,,–. Efforts have focused on readily synthesizable …

We present a comprehensive analysis of all ring systems (both heterocyclic and
nonheterocyclic) in clinical trial compounds and FDA-approved drugs. We show 67% of …

Abstract ChEMBL (https://www. ebi. ac. uk/chembl/) is a manually curated, high-quality, large-
scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like …

Epik version 7 is a software program that uses machine learning for predicting the p K a
values and protonation state distribution of complex, druglike molecules. Using an ensemble …

Abstract Structure-based docking screens of large compound libraries have become
common in early drug and probe discovery. As computer efficiency has improved and …