Generative molecular design for drug discovery and development has seen a recent
resurgence promising to improve the efficiency of the design-make-test-analyse cycle; by …

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

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

The discovery of functional molecules is an expensive and time-consuming process,
exemplified by the rising costs of small molecule therapeutic discovery. One class of …

Engineering new molecules with desirable functions and properties has the potential to
extend our ability to engineer proteins beyond what nature has so far evolved. Advances in …

Deep generative models for structure-based drug design (SBDD), where molecule
generation is conditioned on a 3D protein pocket, have received considerable interest in …

Designing compounds with desired properties is a key element of the drug discovery
process. However, measuring progress in the field has been challenging due to the lack of …

Finding new molecules with a desired biological activity is an extremely difficult task. In this
context, artificial intelligence and generative models have been used for molecular de novo …

Computationally generating new synthetically accessible compounds with high affinity and
low toxicity is a great challenge in drug design. Machine learning models beyond …

Generating new molecules with specified chemical and biological properties via generative
models has emerged as a promising direction for drug discovery. However, existing …