mirror of
https://github.com/rdkit/rdkit.git
synced 2026-06-04 21:54:27 +08:00
* remove all of the "from __future__" imports * remove the first batch of rdkit.six imports/uses * next step of rdkit.six removal * removing xrange, range, and some maps * next round of removals * next round of cleanups * fix inchi test * last bits of "from rdkit.six" are gone * and the last of the six stuff is gone * strange importlib problem
This directory contains scripts for carrying out the calculations and analyis from the publications: 1) A. Vulpetti, U. Hommel, G. Landrum, R. Lewis and C. Dalvit, "Design and NMR-based screening of LEF, a library of chemical fragments with different Local Environment of Fluorine" J. Am. Chem. Soc. 131 (2009) 12949-12959. http://dx.doi.org/10.1021/ja905207t 2) A. Vulpetti, G. Landrum, S. Ruedisser, P. Erbel and C. Dalvit, "19F NMR Chemical Shift Prediction with Fluorine Fingerprint Descriptor" J. of Fluorine Chemistry (2010). http://dx.doi.org/10.1016/j.jfluchem.2009.12.024 The scripts require that the RDKit (www.rdkit.org) be installed and properly configured. The scripts assume that input db.sdf files only contain molecules having either CF or CF3 moieties. Commands to run: 1) Generation of Fluorine Fingerprint (F-FP-L) ------------------------------------------------------------------------------------------ python CreateFps.py db.sdf db.layers.pkl > dupes.layers.txt 2) Butina Clustering using Fluorine Fingerprint (F-FP-L) ------------------------------------------------------------------------------------------ python ClusterFps.py db.layers.pkl > clusters.layers.txt 3) Cliff Analysis using Fluorine Fingerprint Similarity vs a specified property in propField ------------------------------------------------------------------------------------------- python DistancePlot.py db.sdf cliff.txt 4) KNN prediction of a property specified in propField using F-FP-L (L= maximum path length in atoms) ------------------------------------------------------------------------------------------- python DistancePredict.py --max=L+1 --sim="[0.9,0.8,0.7]" --nbrs=nbrs.txt training.sdf test.sdf prediction.txt In the event you use the scripts for publication please reference the original publications: 1) A. Vulpetti, U. Hommel, G. Landrum, R. Lewis and C. Dalvit, "Design and NMR-based screening of LEF, a library of chemical fragments with different Local Environment of Fluorine" J. Am. Chem. Soc. 131 (2009) 12949-12959. http://dx.doi.org/10.1021/ja905207t 2) A. Vulpetti, G. Landrum, S. Ruedisser, P. Erbel and C. Dalvit, "19F NMR Chemical Shift Prediction with Fluorine Fingerprint Descriptor" J. of Fluorine Chemistry (2010). http://dx.doi.org/10.1016/j.jfluchem.2009.12.024