Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …

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 …

Highlights•Providing concepts and generation processes of chemical fingerprints.•
Comparing the algorithms and characteristics among different types of fingerprints.• …

This review seeks to provide a timely survey of the scope and limitations of cheminformatics
methods in natural product‐based drug discovery. Following an overview of data resources …

A new phosphine-free Co (II) complex-catalyzed synthesis of various quinoxalines via
dehydrogenative coupling of vicinal diols with both o-phenylenediamines and 2 …

The use of computational tools to identify biological targets of natural products with
anticancer properties and unknown modes of action is gaining momentum. We employed …

The discovery of macromolecular targets for bioactive agents is currently a bottleneck for the
informed design of chemical probes and drug leads. Typically, activity profiling against …

Using machine learning, targets were identified for β-lapachone. Resorting to biochemical
assays, β-lapachone was validated as a potent, ligand efficient, allosteric and reversible …

Abstract Traditional Chinese Medicine (TCM) has been widely used in the treatment of
various diseases for millennia. In the modernization process of TCM, TCM ingredient …