The de novo design of drug molecules is recognized as a time-consuming and costly process, and computational approaches have been applied in each stage of the drug discovery pipeline. Variational ...

A review from Xidian University shows that advanced computational algorithms—from neural networks and matrix methods to recommendation engines and ...

Finding target molecules with specific chemical properties plays a decisive role in drug development. We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for ...

While AI-driven approaches tout increased speed and lower costs, commercial interests compromise scientific collaboration.

Every protein in the body is encased in a water shell that directs protein structure, provides vital stability and steers ...

A major scientific advance in protein modeling developed by Microsoft Research AI for Science, has been published in Science.

Revolution Medicines' proprietary data will train a bespoke version of NeuralPLexer, an AI model for protein-ligand ...

Revolution Medicines has zeroed in on Iambic Therapeutics’ AI drug discovery platform, striking a multi-year technology and research collaboration that gives Iambic the chance to earn up to $25 mil | ...

Rett syndrome is a devastating rare genetic childhood disorder primarily affecting girls. Merely 1 out of 10,000 girls are ...

Generative Chemistry: Navigating Vast Chemical Space in Drug Discovery Explore the tremendous potential that generative chemistry offers drug discovery.

The availability of the new technologies, combined with many genetic strategies, has changed the way that researchers approach antibacterial drug discovery.

Upstart Chinese drug innovators are joining their foreign competitors in deploying more artificial intelligence (AI) tools to reduce the costs of discoveries in an effort to shorten the route to ...