Highlights•Chemical graph theory and descriptors in drug discovery.•Chemical fingerprint
and similarity analysis.•Machine learning models for virtual screening.•Future challenges …

Computer-aided drug discovery/design methods have played a major role in the
development of therapeutically important small molecules for over three decades. These …

Recently, a novel class of degree-based topological molecular descriptors was proposed,
the so-called Sombor indices. Within this study, the predictive and discriminative potentials …

Highlights•We review machine learning methods/tools relevant to ligand-based virtual
screening.•Machine learning methods classify compounds and predict new active …

SwissSimilarity is a new web tool for rapid ligand-based virtual screening of small to
unprecedented ultralarge libraries of small molecules. Screenable compounds include …

A philosophy for defining what constitutes a virtual high-throughput screen is discussed, and
the choices that influence decisions at each stage of the computational funnel are …

High-throughput and virtual screening are important components of modern drug discovery
research. Typically, these screening technologies are considered distinct approaches, as …

Molecular Informatics utilises many ideas and concepts to find relationships between
molecules. The concept of similarity, where molecules may be grouped according to their …

In the 1970s, Density Functional Theory (DFT) was borrowed from physics and adapted to
chemistry by a handful of visionaries. Now chemical DFT is a diverse and rapidly growing …

The chemical space is the ensemble of all possible molecules, which is believed to contain
at least 1060 organic molecules below 500 Da of possible interest for drug discovery. This …