The phenomenal advances of machine learning in the context of drug design and discovery
have led to the development of a plethora of molecular descriptors. In fact, many of these …

The accurate modeling and prediction of small molecule properties and bioactivities depend
on the critical choice of molecular representation. Decades of informatics-driven research …

Through the representation of small molecule structures as numerical descriptors and the
exploitation of the similarity principle, chemoinformatics has made paramount contributions …

Molecular descriptors encode a wide variety of molecular information and have become the
support of many contemporary chemoinformatic and bioinformatic applications. They grasp …

The conversion of chemical structures into computer-readable descriptors, able to capture
key structural aspects, is of pivotal importance in the field of cheminformatics and computer …

To systematically compare bioactive and theoretically derived compound conformations, we
have analyzed 18 different sets of active small molecules with experimentally determined …

Within drug discovery, the goal of AI scientists and cheminformaticians is to help identify
molecular starting points that will develop into safe and efficacious drugs while reducing …

The concept of drug-likeness helps to optimise pharmacokinetic and pharmaceutical
properties, for example, solubility, chemical stability, bioavailability and distribution profile. A …

P= f (S) where P is any medicinal or toxicological property of a molecule and S represents
the relevant aspects of the structure that are responsible for the property of interest …

Improved understanding of the forces that determine drug specificity to their targets is
important for drug design and discovery, as well as for gaining knowledge about molecular …