Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …

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 …

In drug discovery, drug-target interaction (DTI) plays a crucial role. Identifying DTI in a wet-
lab experiment is time-consuming, labor-intensive, and costly. Using reliable computational …

Virtual screening has emerged as a valuable computational tool for predicting compound–
protein interactions, offering a cost-effective and rapid approach to identifying potential …

The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of
drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in …

Drug–target interaction prediction is a vital stage in drug development, involving lots of
methods. Experimental methods that identify these relationships on the basis of clinical …

Drug discovery is a challenging process with a huge molecular space to be explored and
numerous pharmacological properties to be appropriately considered. Among various drug …

Drug–target protein interaction (DTI) identification is fundamental for drug discovery and
drug repositioning, because therapeutic drugs act on disease-causing proteins. However …

Background Drug-target interaction (DTI) is a vital drug design strategy that plays a
significant role in many processes of complex diseases and cellular events. In the face of …

Abstract Investigating Drug-Target Interactions (DTI) is crucial for drug repositioning and
discovery tasks. However, discovering DTIs through experimental approaches is time …