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--- subsets [2016/12/27 20:44] – rkiss
+++ subsets [2016/12/27 21:07] – rkiss
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 ==== Property based filtering ====
-For the drug-like and fragment subsets the [[http://www.sciencedirect.com/science/article/pii/S0169409X00001290|rule-of-5]] and [[http://www.sciencedirect.com/science/article/pii/S1359644603028319|rule-of-3]] physicochemical property filters are applied allowing max 1 violation. Additionally, we used a few more rules:
+For the drug-like and fragment subsets the [[http://www.sciencedirect.com/science/article/pii/S0169409X00001290|rule-of-5]] and [[http://www.sciencedirect.com/science/article/pii/S1359644603028319|rule-of-3]] physicochemical property filters are applied allowing max 1 violation. Additionally, we applied the following filtering criteria to skip some rather "strange" compounds:
   * number of components < = 1
   * MW > = 100
@@ Line 20: / Line 21: @@
   * number of halogens < = 7
   * number of inorganic atoms = 0
-We used these rules to leave out more "strange compounds" which may be included more likely in the diverse sets as they differ from the regular compounds.
 ==== Diversity selection ====
-The Mcule database contains ~5.7M stock compounds and ~30.3M virtual compounds. Diversity selection was carried out in a way to prefer the stock compounds over the virtual ones. As a result, the chemical space is represented by stock compounds where possible. More over, the downloadable files contains the compounds in diversity order i.e. the first N compounds represent the most dissimilar N compounds, so you can choose yourself the number of compounds to represent the whole Ro3 and Ro5 subsets.
+Diversity selection was set up to prefer in-stock compounds over virtual ones. As a result, the chemical space is represented by in-stock compounds where possible.
+The [[https://mcule.com/database/|downloadable files]] contain the compounds in diversity order i.e. the first N compounds represent the most dissimilar N compounds. This means that if you want to further narrow down the number of compounds you can keep the first X compounds of the files and they will be the most dissimilar ones.
-Structural similarity was measured by Tanimoto coefficient (TC) between FP2 linear fingerprints generated by OpenBabel. The combinations of the following algorithms were applied to extract the most dissimilar subsets:
+Structural similarity was measured by Tanimoto coefficient (TC) between FP2 linear fingerprints generated by [[http://jcheminf.springeropen.com/articles/10.1186/1758-2946-3-33|OpenBabel]]. The combinations of the following algorithms were applied to extract the most dissimilar subsets:
   * we used sphere exclusion to eliminate highly similar compounds to reduce the input size where needed
   * then [[diversitysel|stepwise elimination]] was applied to obtain the most dissimilar compounds