Compare shape and electrostatic similarity of molecules #RDKit #espsim #python

There are lots of way to define molecular similarity, for example fingerprint based, descriptor based, graph based, shape based etc. etc… In the 2D world, circular fingerprint based similarity is used in many case. However, 3D based similarity approach is also useful for drug design. As you now, OpenEye provides useful software named ‘ROCS’. ROCSContinue reading “Compare shape and electrostatic similarity of molecules #RDKit #espsim #python”

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Probabilistic Random Forest approach to predict experimental value #RDKit #chemoinformatics #machine_learning

To build predictive model, input value(X) and target value(y) is required. But in the drug discovery area target value always has experimental error. So any experimental value (target value) may have uncertainly and it makes difficult to build predictive model. Recently Ola Engkvist group who is in AZ published interesting article in Jounral of chemoinformatics.Continue reading “Probabilistic Random Forest approach to predict experimental value #RDKit #chemoinformatics #machine_learning”