Drug discovery based on artificial intelligence has been in the spotlight recently as it
significantly reduces the time and cost required for develo** novel drugs. With the …

Through the revolutionization of artificial intelligence (AI) technologies in clinical research,
significant improvement is observed in diagnosis of cancer. Utilization of these AI …

Convolutional neural networks (CNNs) have been used to extract information from various
datasets of different dimensions. This approach has led to accurate interpretations in several …

The prediction of drug-target interactions (DTIs) is a vital step in drug discovery. The success
of machine learning and deep learning methods in accurately predicting DTIs plays a huge …

In rational drug design, the concept of molecular similarity searching is frequently used to
identify molecules with similar functionalities by looking up structurally related molecules in …

Identifying native-like protein–ligand complexes (PLCs) from an abundance of docking
decoys is critical for large-scale virtual drug screening in early-stage drug discovery lead …

Small molecules have been providing medical breakthroughs for human diseases for more
than a century. Recently, identifying small molecule inhibitors that target microRNAs …

Prediction on drug–target interaction has always been a crucial link for drug discovery and
repositioning, which have witnessed tremendous progress in recent years. Despite many …

Background Drug discovery processes, such as new drug development, drug synergy, and
drug repurposing, consume significant yearly resources. Computer-aided drug discovery …

Membrane proteins mediate a wide spectrum of biological processes, such as signal
transduction and cell communication. Due to the arduous and costly nature inherent to the …