rgbombarelli

3 ms·

1. 1.▲
   by rgbombarelli 10y ago

   It's the water-octanol partition coefficient, a basic molecular descriptor of the physiological distribution of a drug. It is one of the multiple targets one aims to optimize in a novel drug-like compound. https://en.wikiped
2. 2.▲
   by rgbombarelli 10y ago

   Exactly, we have a good understanding that logP is additive (as a matter of fact, one predicts it using group contributions). The AE noticed this and started adding halogens to already high logP molecules. The interesting part is that it st
3. 3.▲
   by rgbombarelli 10y ago

   We did something like that for a more continuous property, like logP, which is easy to predict with cheminformatics. We are working on metrics that reflect drug-likeness better.
4. 4.▲
   by rgbombarelli 10y ago

   You are right about SMILES. We trained on the canonical SMILES output by the RDKit, so as far as our AE is concerned, there is only one way to write SMILES for a given molecule ( http://www.rdkit.org/docs/GettingStartedI
5. 5.▲
   by rgbombarelli 10y ago

   Who says you cannot do deep learning and molecular dynamics? There are a couple of recent examples of neural networks to predicted energies and gradients allowing faster computation and larger time steps in MD simulations. https:/
6. 6.▲
   by rgbombarelli 10y ago

   One of the authors here. Mostly he was just faster than us! Most co-authors are busy right now starting jobs at new places (plus trying to get published at an old school journal for the comfort of chemists out there). Max has done a very go