abstract Introduction: The use of computational tools in the early stages of drug development
has increased in recent decades. Machine learning (ML) approaches have been of special …

The interest in the application of machine learning techniques (MLT) as drug design tools is
growing in the last decades. The reason for this is related to the fact that the drug design is …

Neglected tropical diseases (NTDs) encompass a group of infectious diseases with a
protozoan etiology, high incidence, and prevalence in developing countries. As a result …

Neglected tropical diseases continue to create high levels of morbidity and mortality in a
sizeable fraction of the world's population, despite ongoing research into new treatments …

Leishmaniasis is a vector-borne zoonotic disease caused by protozoan parasites of the
genus Leishmania, which are responsible for numerous clinical manifestations, such as …

In general perturbation methods starts with a known exact solution of a problem and add
“small” variation terms in order to approach to a solution for a related problem without known …

Background: The widespread application of fluorine in drug design benefits from distinctive
properties. Incorporation of fluorine can positively modulate certain pharmacokinetics …

In silico prediction of antileishmanial activity using quantitative structure–activity relationship
(QSAR) models has been developed on limited and small datasets. Nowadays, the …

Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is
a challenging task; despite the numerous efforts realized to predict/measure BBB passage …

Leishmaniasis affects mainly rural areas and the poorest people in the world. A
computational study of the antileishmanial activity of organic selenium and tellurium …