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 …

De novo drug design is a stationary way to build novel ligands in the confined pocket of
receptor by assembling the atoms or fragments, while molecular dynamics (MD) simulation …

Predicting protein–ligand binding affinities (PLAs) is a core problem in drug discovery.
Recent advances have shown great potential in applying machine learning (ML) for PLA …

Abstract We present ProteinShake, a Python software package that simplifies
datasetcreation and model evaluation for deep learning on protein structures. Users …

Predicting protein–ligand binding affinity is a central issue in drug design. Various deep
learning models have been published in recent years, where many of them rely on 3D …

Motivation The identification of compound–protein interactions (CPIs) is an essential step in
the process of drug discovery. The experimental determination of CPIs is known for a large …

Flexible modeling of the protein–ligand complex structure is a fundamental challenge for in
silico drug development. Recent studies have improved commonly used docking tools by …

Motivation Computational approaches for identifying the protein–ligand binding affinity can
greatly facilitate drug discovery and development. At present, many deep learning-based …

The accurate prediction of drug-target affinity (DTA) is a crucial step in drug discovery and
design. Traditional experiments are very expensive and time-consuming. Recently, deep …

Nanomedicine is a field of medicine that uses nanotechnology to develop new diagnostic
tools and therapies for a wide range of medical conditions. It encompasses a variety of …