Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …

As the number of determined and predicted protein structures and the size of druglike 'make-
on-demand'libraries soar, the time-consuming nature of structure-based computer-aided …

De novo drug design aims to generate molecules from scratch that possess specific
chemical and pharmacological properties. We present a computational approach utilizing …

The design of molecules requires multi-objective optimizations in high-dimensional
chemical space with often conflicting target properties. To navigate this space, classical …

Deep generative models for de novo molecular generation using discrete data, such as the
simplified molecular-input line-entry system (SMILES) strings, have attracted widespread …

Antimicrobial peptides (AMPs) are one of the elements of innate immunity that have a crucial
role in fighting infections. These molecules are produced by all kinds of cells and can …

Drug discovery and development constitute a laborious and costly undertaking. The success
of a drug hinges not only good efficacy but also acceptable absorption, distribution …

Abstract Generative Artificial Intelligence can be an important asset in the drug discovery
process to meet the demand for novel medicines. This work outlines the optimization and …

Two-dimensional Layered double hydroxides (LDHs) are highly used in the biomedical
domain due to their biocompatibility, biodegradability, controlled drug loading and release …

Generative molecular models generate novel molecules with desired properties by
searching chemical space. Traditional combinatorial optimization methods, such as genetic …