Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …

Abstract Development of new products often relies on the discovery of novel molecules.
While conventional molecular design involves using human expertise to propose …

Drug discovery is the process of new drug identification. This process is driven by the
increasing data from existing chemical libraries and data banks. The knowledge graph is …

Application of deep learning techniques for de novo generation of molecules, termed as
inverse molecular design, has been gaining enormous traction in drug design. The …

Molecular design strategies are integral to therapeutic progress in drug discovery.
Computational approaches for de novo molecular design have been developed over the …

De novo drug design is a computational approach that generates novel molecular structures
from atomic building blocks with no a priori relationships. Conventional methods include …

Artificial intelligence (AI) is booming. Among various AI approaches, generative models
have received much attention in recent years. Inspired by these successes, researchers are …

By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the
host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics …

Generative models are becoming a tool of choice for exploring the molecular space. These
models learn on a large training dataset and produce novel molecular structures with similar …

In the past few years, we have witnessed a renaissance of the field of molecular de novo
drug design. The advancements in deep learning and artificial intelligence (AI) have …