Antibiotic Identified by AI
Pretty well done - especially the experimental validation.  The main conclusions are accurate, but there is some BS around the periphery.  A few notes below.<p>- The secret sauce here was the large, high quality experimental dataset they generated.<p>- Chemprop is meh.<p>- Is a tanimoto similarity < 0.3 really dissimilar?  Depends on the chemical fingerprint parameters they are using in RDkit.  For ECFP4 the expected similarity of two random molecules is about 0.1.  A value of 0.3 about the cutoff you would use for a similarity based virtual screening with ECFP4 fingerprints.<p>- The cheminformatic filtering steps that they did on their hits was well done.<p>- The experimental validation of the target was well done.  A good illustration of all the preclinical work it takes to validate a molecule and mechanism on the way to an IND.<p>- They got very lucky.  Most of the time your compound hits are not all that potent and require extensive med chem optimization.  That was not the case here.