Fragment‐based drug discovery (FBDD) is now established as a complementary approach
to high‐throughput screening (HTS). Contrary to HTS, where large libraries of drug‐like …

Designing functional molecules is the prerogative of experts who have advanced knowledge
and experience in their fields. To democratize automatic molecular design for both experts …

Reinforcement learning is a powerful paradigm that has gained popularity across multiple
domains. However, applying reinforcement learning may come at the cost of multiple …

Recently, we have released the de novo design platform REINVENT in version 2.0. This
improved and extended iteration supports far more features and scoring function …

In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and
Machine Learning (ML) with cheminformatics has proven to be a powerful combination …

Traditional drug discovery is very laborious, expensive, and time-consuming, due to the
huge combinatorial complexity of the discrete molecular search space. Researchers have …

A plethora of AI-based techniques now exists to conduct de novo molecule generation that
can devise molecules conditioned towards a particular endpoint in the context of drug …

Recent years have seen tremendous success in the design of novel drug molecules through
deep generative models. Nevertheless, existing methods only generate drug-like molecules …

Cyclometalated iridium (III) complexes have been used in various optical materials,
including organic light-emitting diodes (OLEDs) and photocatalysts, and a deeper …

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 …