Introduction: Neural networks are becoming a very popular method for solving machine
learning and artificial intelligence problems. The variety of neural network types and their …

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

It is widely accepted that modern QSAR began in the early 1960s. However, as long ago as
1816 scientists were making predictions about physical and chemical properties. The first …

In silico tools to investigate absorption, distribution, metabolism, excretion, and
pharmacokinetics (ADME-PK) properties of new chemical entities are an integral part of the …

Abstract The field of Quantitative Structure-Activity Relationship (QSAR) relies heavily on
molecular descriptors. Among various guidelines suggested by Organisation for Economic …

Matched molecular pair analysis (MMPA) is a tool to extract knowledge of medicinal
chemistry from existing experimental data, and it relates changes in activities or properties to …

To avoid adverse side effects of chemicals, pharmaceuticals, and their transformation
products (TPs) in the environment, substances should be designed to fully mineralize in the …

Lead optimization is a crucial step in the drug discovery process, which aims to design
potential drug candidates from biologically active hits. During lead optimization, active hits …

In recent years, the development of high-throughput screening (HTS) technologies and their
establishment in an industrialized environment have given scientists the possibility to test …

Introduction: The concept of 'chemical space'reveals itself in two forms: the discrete set of all
possible molecules, and multi-dimensional descriptor space encompassing all the possible …