A compound I synthesized was briefly an exciting lead as an anti-asthma drug. Turns out the reaction had not gone to completion and a precursor was covalently binding the target.
Note lesson here for deep learning, in @Dereklowe’s analysis.https://twitter.com/curiouswavefn/status/1166740485827747840 …
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I got a lot of flak from my boss. “We hired you to do AI, not spend all your time fixing published work!” The fantasy that fairy dust can somehow save you from the hard work of figuring out what data mean is perennial.
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Isn’t in silico drug discovery just an extrapolation of ignorance?
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Mostly, but it sometimes works.
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I always say that if you simply start with the premise that >90% of published compounds or HTS hits are crap, you'll save yourself a lot of time.
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