In-cell structural biology aims at extracting structural information about proteins or nucleic
acids in their native, cellular environment. This emerging field holds great promise and is …

Abstract Structure-based virtual screening (SBVS) via docking has been used to discover
active molecules for a range of therapeutic targets. Chemical and protein data sets that …

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

Protein–ligand scoring functions are widely used in structure-based drug design for fast
evaluation of protein–ligand interactions, and it is of strong interest to develop scoring …

NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as
early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of …

The recently reported machine learning-or deep learning-based scoring functions (SFs)
have shown exciting performance in predicting protein–ligand binding affinities with fruitful …

There have been numerous advances in the development of computational and statistical
methods and applications of big data and artificial intelligence (AI) techniques for computer …

The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …

Efficient drug delivery systems (DDSs) play a pivotal role in ensuring pharmaceuticals'
targeted and effective administration. However, the intricate interplay between drug …

We discuss how data unbiasing and simple methods such as protein-ligand Interaction
FingerPrint (IFP) can overestimate virtual screening performance. We also show that IFP is …