Design of Natural‐Product‐Inspired Multitarget Ligands by Machine Learning

A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (−)‐galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targets of (−)‐galantamine, with different polypharmacological profiles. Two of the computer‐generated hits possess an expanded spectrum of bioactivity on targets relevant to the treatment of Alzheimer's disease and are suitable for hit‐to‐lead expansion. These results advocate multitarget drug design by advanced virtual screening protocols based on chemically informed machine learning models.

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