Conventional wet laboratory testing, validations, and synthetic procedures are costly and
time-consuming for drug discovery. Advancements in artificial intelligence (AI) techniques …

Background The treatment of complex diseases by taking multiple drugs becomes
increasingly popular. However, drug-drug interactions (DDIs) may give rise to the risk of …

The properties of the drug may be altered by the combination, which may cause unexpected
drug–drug interactions (DDIs). Prediction of DDIs provides combination strategies of drugs …

Development of a new dug is a very lengthy and highly expensive process since only
preclinical, pharmacokinetic, pharmacodynamic and toxicological studies include a multiple …

Drug-target Interactions (DTIs) prediction plays a central role in drug discovery.
Computational methods in DTIs prediction have gained more attention because carrying out …

Abstract Analysis and prediction of drug-target interactions (DTIs) play an important role in
understanding drug mechanisms, as well as drug repositioning and design. Machine …

Background Drug–target interaction (DTI) plays a vital role in drug discovery. Identifying
drug–target interactions related to wet-lab experiments are costly, laborious, and time …

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming
and costly to determine DTI experimentally. Hence, it is necessary to develop computational …

Prediction of new drug-target interactions is critically important as it can lead the researchers
to find new uses for old drugs and to disclose their therapeutic profiles or side effects …

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 …