Despite the fact that deep learning has achieved remarkable success in various domains
over the past decade, its application in molecular informatics and drug discovery is still …

Highlights•Drug discovery has been advanced to a big data era with a large amount of
public data sources available.•Ten V features (volume, velocity, variety, veracity, validity …

Extensive efforts have been directed at the discovery, investigation and clinical monitoring of
targeted therapeutics. These efforts may be facilitated by the convenient access of the …

Diverse forms of unwanted signal variations in mass spectrometry-based metabolomics data
adversely affect the accuracies of metabolic profiling. A variety of normalization methods …

With tens of thousands of plant species on earth, we are endowed with an enormous wealth
of medicinal remedies from Mother Nature. Natural products and their derivatives represent …

Abstract DrugBank (http://www. drugbank. ca) is a richly annotated database of drug and
drug target information. It contains extensive data on the nomenclature, ontology, chemistry …

Advances in areas that include genomics, systems biology, protein structure determination
and artificial intelligence provide new opportunities for target-based antibacterial drug …

Dual inhibition of serotonin and norepinephrine transporters (hSERT and hNET) gives
greatly improved efficacy and tolerability for treating major depressive disorder (MDD) …

Abstract The Drug-Gene Interaction database (DGIdb) mines existing resources that
generate hypotheses about how mutated genes might be targeted therapeutically or …

The aim of virtual screening (VS) is to identify bioactive compounds through computational
means, by employing knowledge about the protein target (structure-based VS) or known …