Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

In the past, conventional drug discovery strategies have been successfully employed to
develop new drugs, but the process from lead identification to clinical trials takes more than …

Over the last decade, deep learning (DL) methods have been extremely successful and
widely used to develop artificial intelligence (AI) in almost every domain, especially after it …

Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-
molecular targets to modulate their activity, which in turn results in the observed phenotypic …

Motivation: Most bioactive molecules perform their action by interacting with proteins or other
macromolecules. However, for a significant fraction of them, the primary target remains …

The de novo design of molecular structures using deep learning generative models
introduces an encouraging solution to drug discovery in the face of the continuously …

Highlights•Polypharmacology and its exploitation for drug discovery is drawing increasing
interest.•Computational approaches have great potential for predicting the …

Alzheimer's disease (AD) is one of the most complicated progressive neurodegeneration
diseases that involve many genes, proteins, and their complex interactions. No effective …

Here we report PPB2 as a target prediction tool assigning targets to a query molecule based
on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding …

Natural products are continually explored in the development of new bioactive compounds
with industrial applications, attracting the attention of scientific research efforts due to their …