Disease modeling and target identification are the most crucial initial steps in drug
discovery, and influence the probability of success at every step of drug development …

Stimuli-responsive polymers can respond to internal stimuli, such as reactive oxygen
species (ROS), glutathione (GSH), and pH, biological stimuli, such as enzymes, and external …

The efficacy and safety of drugs are widely known to be determined by their interactions with
multiple molecules of pharmacological importance, and it is therefore essential to …

The emergence of large-scale phenotypic, genetic, and other multi-model biochemical data
has offered unprecedented opportunities for drug discovery including drug repurposing …

Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

The incorporation of data analytics in the healthcare industry has made significant progress,
driven by the demand for efficient and effective big data analytics solutions. Knowledge …

Exiting computational models for drug–target binding affinity prediction have much room for
improvement in prediction accuracy, robustness and generalization ability. Most deep …

Drug discovery is adapting to novel technologies such as data science, informatics, and
artificial intelligence (AI) to accelerate effective treatment development while reducing costs …

Predicting drug–target affinity (DTA) is beneficial for accelerating drug discovery. Graph
neural networks (GNNs) have been widely used in DTA prediction. However, existing …

Computational drug repositioning is an effective way to find new indications for existing
drugs, thus can accelerate drug development and reduce experimental costs. Recently …