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 …

Deep learning has disrupted nearly every field of research, including those of direct
importance to drug discovery, such as medicinal chemistry and pharmacology. This …

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 …

The application of artificial intelligence (AI) has been considered a revolutionary change in
drug discovery and development. In 2020, the AlphaFold computer program predicted …

We have developed a deep generative model, generative tensorial reinforcement learning
(GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility …

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 …

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 …

De novo design seeks to generate molecules with required property profiles by virtual
design-make-test cycles. With the emergence of deep learning and neural generative …

Abstract Machine learning-based generative models can generate novel molecules with
desirable physiochemical and pharmacological properties from scratch. Many excellent …

In the space of only a few years, deep generative modeling has revolutionized how we think
of artificial creativity, yielding autonomous systems which produce original images, music …