The task of predicting the interactions between drugs and targets plays a key role in the
process of drug discovery. There is a need to develop novel and efficient prediction …

Over the last decade, increasing interest has been attracted towards the application of
artificial intelligence (AI) technology for analyzing and interpreting the biological or genetic …

Since the last published update in 2014, the SuperPred webserver has been continuously
developed to offer state-of-the-art models for drug classification according to ATC classes …

Natural products (NPs) are single chemical compounds, substances or mixtures produced
by a living organism-found in nature. Evolutionarily, NPs have been used as healing agents …

Abstract The Na–K–2Cl cotransporter NKCC1 and the neuron-specific K–Cl cotransporter
KCC2 are considered attractive CNS drug targets because altered neuronal chloride …

Alzheimer's Disease (AD) is the most common form of dementia, affecting almost 50 million
of people around the world, characterized by a complex and age-related progressive …

The novel nature of SARS-CoV-2 calls for the development of efficient de novo drug design
approaches. In this study, we propose an end-to-end framework, named CogMol (Controlled …

Most small molecule drugs interact with unintended, often unknown, biological targets and
these off-target interactions may lead to both preclinical and clinical toxic events. Undesired …

In silico target fishing, whose aim is to identify possible protein targets for a query molecule,
is an emerging approach used in drug discovery due its wide variety of applications. This …

Identification of potential targets for known bioactive compounds and novel synthetic
analogs is of considerable significance. In silico target fishing (TF) has become an …