JCIM | Fang Lei Team at XtalPi Combines AI and Computational Chemistry to Discover Novel Active Hit Compounds Targeting PI5P4K-β

In recent years, computer-aided drug design (CADD) and artificial intelligence-driven drug design (AIDD) have been increasingly applied in areas such as drug discovery and design. Against this backdrop, XtalPi has developed the intelligent and automated innovative drug discovery platform ID4Inno, which includes two major computational systems: the high-precision computational chemistry platform ID4Gibbs and the artificial intelligence drug discovery platform ID4Idea. The platform encompasses three modules: intelligent computation, automated experimentation, and expert experience. It explores a broader chemical space with higher efficiency and lower costs, significantly reducing the number of wet lab experiments and accelerating the Design−Make−Test−Analyze (DMTA) cycle in drug discovery. Recently, the team led by Lei Fang from XtalPi published a research paper titled “Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-β Case Study” in the Journal of Chemical Information and Modeling, a core journal of computational chemistry published by the American Chemical Society.