Yingce Xia

Papers Published on Feb 11 · Submitted by akhaliq on Feb 12 Abstract Foundation models have revolutionized natural language processing and artificial intelligence, significantly enhancing how machines comprehend and generate human languages. Inspired by the success of these foundation models, researchers have developed foundation models for individual scientific domains, including small molecules, materials, proteins, DNA, and RNA.

The Global Health Drug Discovery Institute (opens in new tab) (GHDDI) and Microsoft Research have reached a milestone in tuberculosis (TB) drug research with TamGen (opens in new tab), an open-source (opens in new tab), transformer-based chemical language model for developing target-specific drug compounds. Working in collaboration, the joint team successfully identified several promising inhibitors for a TB protease, with the most effective compound showing significant bioactivity.

Abstract Generative drug design facilitates the creation of compounds effective against pathogenic target proteins. This opens up the potential to discover novel compounds within the vast chemical space and fosters the development of innovative therapeutic strategies. However, the practicality of generated molecules is often limited, as many designs focus on a narrow set of drug-related properties, failing to improve the success rate of subsequent drug discovery process.