AIDD- platform

A comprehensive computational screening solution for active compounds has been established, integrating multiple AI models and computational chemistry methods into an iterative screening pipeline. The process begins with the preparation of small molecule databases and receptor structures, followed by predictive kinase selectivity profiling and molecular dynamics simulations of protein-ligand complexes. It further incorporates ADMET property evaluation, compound diversity analysis, and culminates in expert-guided selection of promising candidates for subsequent biological activity testing. By leveraging state-of-the-art machine learning and computational chemistry approaches at each step, this pipeline significantly improves the hit rate in early drug screening, enhances the likelihood of discovering novel bioactive molecules, and reduces the overall cost of early-stage drug discovery.