Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

New drug production, from target identification to marketing approval, takes over 12 years
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …

Currently, molecular docking is becoming a key tool in drug discovery and molecular
modeling applications. The reliability of molecular docking depends on the accuracy of the …

Structure-based virtual screening (VS) is a widely used approach that employs the
knowledge of the three-dimensional structure of the target of interest in the design of new …

Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …

Conspectus In structure-based drug design, scoring functions are widely used for fast
evaluation of protein–ligand interactions. They are often applied in combination with …

Although deep learning approaches have had tremendous success in image, video and
audio processing, computer vision, and speech recognition, their applications to three …

Classical scoring functions have reached a plateau in their performance in virtual screening
and binding affinity prediction. Recently, machine-learning scoring functions trained on …

With the recent explosion in the size of libraries available for screening, virtual screening is
positioned to assume a more prominent role in early drug discovery's search for active …

Docking tools to predict whether and how a small molecule binds to a target can be applied
if a structural model of such target is available. The reliability of docking depends, however …