ML_Screening

Through an active learning approach, machine learning algorithms are utilized to learn from the virtual screening results of a sampled subset of an ultra-large compound library. This enables rapid filtering and removal of potentially inactive molecules from the remainder of the ultra-large library, thereby significantly accelerating the overall virtual screening process.