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 …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Cell cycle dysregulation is a characteristic hallmark of malignancies, which results in
uncontrolled cell proliferation and eventual tumor formation. Cyclin-dependent kinase 1 …

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 …

Motivation Identifying drug–target interactions (DTIs) is a crucial step in drug repurposing
and drug discovery. Accurately identifying DTIs in silico can significantly shorten …

Emerging environmental pollutants have become a major environmental challenge due to
the highly toxic effluents produced by industries. Among these emerging pollutants …

This review seeks to provide a timely survey of the scope and limitations of cheminformatics
methods in natural product‐based drug discovery. Following an overview of data resources …

The interplay between life sciences and advancing technology drives a continuous cycle of
chemical data growth; these data are most often stored in open or partially open databases …

Drug toxicity prediction is an important step in ensuring patient safety during drug design
studies. While traditional preclinical studies have historically relied on animal models to …

The accurate identification of Drug–Target Interactions (DTIs) remains a critical turning point
in drug discovery and understanding of the binding process. Despite recent advances in …