AI-enabled Libraries

Artificial intelligence (AI)-enabled drug screening is a high-throughput approach that integrates AI technologies with computational chemistry. It is widely applied in fields including protein structure prediction, novel drug development, and molecular design and optimization, thus accelerating the discovery process of drug candidates. The MCE AI-enabled Libraries integrates a variety of advanced technologies including molecular docking, deep learning, and molecular dynamics simulation. Based on high-quality molecular building blocks, it matches appropriate reaction rules and selects optimal compound generation strategies. After excluding unfavorable compounds with high synthetic difficulty, poor drug-likeness, and pan-assay interference compounds (PAINS), the platform constructs an ultra-large compound library characterized by novelty, drug-likeness, diversity, and synthetic accessibility. With hundreds of millions of novel compounds available for selection, the synthesis lead time is only 2–3 weeks, and over 80% of the compounds are delivered on schedule, fulfilling the diverse requirements of different clients.