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Posts tagged with "In Silico"

  • In Silico

    Farewell to “Watson For Drug Discovery”

    STAT is reporting that IBM has stopped trying to sell their “Watson for Drug Discovery” machine learning/AI tool, according to sources within the company. I have no reason to doubt that – in fact, I’ve sort of been expecting it. But no one seems to have told IBM’s website programming team, because the pages touting… Read More
  • Drug Assays

    Comparing Compound Collections

    A common question – well, it should be a common question, anyway – is “How do I make sure that this compound collection is a useful one to screen?” There are alternative forms that come down to the same issues – if you’re putting together a new focused screening set, what should be in it?… Read More
  • Analytical Chemistry

    A Close Look at Fragments

    Here’s a look from the D. E. Shaw research team at fragment binding, and even if you don’t do fragment-based drug discovery, it’s worth a read. That’s because the mechanisms by which fragments bind to proteins are most likely the fundamental ones by which larger molecules bind as well; this is the reductionist look at… Read More
  • Chemical News

    Predicting – Or Not Predicting – New Materials

    We chemists would love to be able to do just a tiny bit less chemistry now and then and just let models and simulations tell us what would happen instead. Only every once in a while – you wouldn’t want to obtain such a perfectly accurate picture of chemical and physical interactions that there was… Read More
  • Drug Assays

    Virtual Screening – As Big As It Currently Gets

    This new paper on “ultra-large” virtual screening is well worth a look in detail. We find a great many lead compounds in this business by random screening of compound libraries, and virtual screening is (as the name implies) the technique of doing this computationally instead of with hundreds (thousands) of sample plates and tireless ro… Read More
  • In Silico

    The Latest on Protein Folding

    The results of the biannual CASP (Critical Assessment of Structure Prediction) effort have been released. This is a widely-watched competition between different groups (and different programs, methods, hardware, etc.) to see how well protein structures can be predicted de novo from just the protein sequences themselves. In the main category, the or… Read More
  • Chemical News

    Machine Learning: Be Careful What You Ask For

    Let the machine learning wars commence! That’s my impression on reading over the situation I’m detailing today, at any rate. This one starts with this paper in Science, a joint effort by the Doyle group at Princeton and Merck, which used ML techniques to try to predict the success of Buchwald-Hartwig coupling reactions. The idea… Read More
  • Chemical News

    Here’s What’s Been Done Before

    I enjoyed this ACS Med. Chem. Letters perspective on AI and machine learning in medicinal chemistry. It has several good points to make, and it brought up one that I haven’t gone into here before: if you’re mining the literature, you will get what the literature can tell you. At the very best, the high… Read More
  • Drug Assays

    A Magic Methyl, Spotted in the Wild

    You hear medicinal chemists talking about the “magic methyl”, the big effect that a single CH3 group can have on potency or selectivity. Here’s a new J. Med. Chem. paper that shows one in action.That structure looks like a kinase inhibitor if anything ever did, and so it is. But small changes to it can… Read More
  • Drug Assays

    Ligand Efficiency Rethought

    Peter Kenny has a paper out on ligand efficiency that’s required reading for medicinal chemists using (or thinking about) that concept as a design tool. I’d recommend reading it with this recent paper – between the two of them, you’re going to have references to a huge swath of the literature on how to measure… Read More
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