Here, we describe a concept of conjugated models for several properties (activities) linked
by a strict mathematical relationship. This relationship can be directly integrated analytically …

We report the first direct QSPR modeling of equilibrium constants of tautomeric
transformations (logK T) in different solvents and at different temperatures, which do not …

Key requirements for quantitative structure–activity relationship (QSAR) models to gain
acceptance by regulatory authorities include a defined domain of applicability (DA) and …

This paper is focused on modern approaches to machine learning, most of which are as yet
used infrequently or not at all in chemoinformatics. Machine learning methods are …

This paper is an overview of the most significant and impactful interpretation approaches of
quantitative structure–activity relationship (QSAR) models, their development, and …

Quantitative structure reactivity relationships (QSRRs) were investigated for the estimation
of the Mayr nucleophilicity parameter N using data sets with 218 nucleophiles (solvent …

In this work, we present a methodology to interpret the weights and biases of a
computational neural network (CNN) quantitative structure− activity relationship model. The …

Nowadays neither molecular model, no matter how elaborate it may be, is able to
encompass all possible interactions, in which a real chemical/biological system is involved …

Conjugated QSPR models for reactions integrate fundamental chemical laws expressed by
mathematical equations with machine learning algorithms. Herein we present a …

Ketones are one of the most common functional groups, and ketone-containing compounds
are essential in both the nature and the chemical sciences. As such, the acidities (pKa) of …