Drug development is one of the most significant processes in the pharmaceutical industry.
Various computational methods have dramatically reduced the time and cost of drug …

Linear discriminant analysis (LDA) is a versatile statistical method for reducing redundant
and noisy information from an original sample to its essential features. Particularly, LDA is a …

Machine learning (ML) based prediction of molecular properties across chemical compound
space is an important and alternative approach to efficiently estimate the solutions of highly …

Artificial Intelligence/Machine Learning (AI/ML) algorithms may speed up the design of
DADNP systems formed by Antibacterial Drugs (AD) and Nanoparticles (NP). In this work …

Predicting the activity of new chemical compounds over pathogenic microorganisms with
different metabolic reaction networks (MRN s) is an important goal due to the different …

Hepatitis C constitutes an unresolved global health problem. This infectious disease is
caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life …

Determining the target proteins of new anticancer compounds is a very important task in
Medicinal Chemistry. In this sense, chemists carry out preclinical assays with a high number …

Epigenetics has become a focus of interest in drug discovery. In this sense, bromodomain-
containing proteins have emerged as potential epigenetic targets in cancer research and …

G-protein-coupled receptors (GPCRs), also known as 7-transmembrane receptors, are the
single largest class of drug targets. Consequently, a large amount of preclinical assays …

Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and
pharmaceutical chemistry need and consider it a huge goal to define target proteins of new …